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Journal articles on the topic 'Network devices'
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1
Hamza, Muhammad, Syed Mashhad M. Geelani, Qamar Nawaz, Asif Kabir, and Isma Hamid. "Clustering of IoT Devices Using Device Profiling and Behavioral Analysis to Build Efficient Network Policies." April 2021 40, no. 2 (April 1, 2021): 335–45. http://dx.doi.org/10.22581/muet1982.2102.08.
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The Internet of Things (IoT) has emerged as a new paradigm, and billions of devices are connected with the internet. IoT is being penetrated in major domains of daily life like health care, agriculture, industry, smart homes and monitoring of the environment. The operator of such complex, huge and diverse heterogeneous networks may not even be fully aware of their IoT devices working, activity, behavior and resource utilization etc. The efficient management of IoT devices becomes a challenge for network managers to ensure smooth network operation. Network traffic analysis of IoT devices is a necessary and rudimentary tool to understand the behavior of devices. In this paper firstly, we identify insights of device network traffic, discuss the activity patterns of some IoT devices and present a visual description of the pattern of IoT devices. Secondly, after analyzing the device's behavior, we build and demonstrate a profile of each device based on its activity cycle and traffic patterns information. Thirdly, the K-Means clustering algorithm is used to make clusters of IoT devices using their profile information. The clustering algorithm groups similar devices in a single group. The obtained results clearly describe the patterns of devices which help the network managers to make appropriate network policies for efficient secure network management.
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Ahmad, Hamza Sajjad, Muhammad Junaid Arshad, and Muhammad Sohail Akram. "Device Authentication and Data Encryption for IoT Network by Using Improved Lightweight SAFER Encryption With S-Boxes." International Journal of Embedded and Real-Time Communication Systems 12, no. 3 (July 2021): 1–13. http://dx.doi.org/10.4018/ijertcs.2021070101.
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To send data over the network, devices need to authenticate themselves within the network. After authentication, the device will be able to send the data in-network. After authentication, secure communication of devices is an important task that is done with an encryption method. IoT network devices have a very small circuit with low resources and low computation power. By considering low power, less memory, low computation, and all the aspect of IoT devices, an encryption technique is needed that is suitable for this type of device. As IoT networks are heterogeneous, each device has different hardware properties, and all the devices are not on one scale. To make IoT networks secure, this paper starts with the secure authentication mechanism to verify the device that wants to be a part of the network. After that, an encryption algorithm is presented that will make the communication secure. This encryption algorithm is designed by considering all the important aspects of IoT devices (low computation, low memory, and cost).
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Rodriguez Medel, Abel, and Jose Marcos C. Brito. "Random-Access Accelerator (RAA): A Framework to Speed Up the Random-Access Procedure in 5G New Radio for IoT mMTC by Enabling Device-To-Device Communications." Sensors 20, no. 19 (September 25, 2020): 5485. http://dx.doi.org/10.3390/s20195485.
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Mobile networks have a great challenge by serving the expected billions of Internet of Things (IoT) devices in the upcoming years. Due to the limited simultaneous access in the mobile networks, the devices should compete between each other for resource allocation during a Random-Access procedure. This contention provokes a non-depreciable delay during the device’s registration because of the great number of collisions experienced. To overcome such a problem, a framework called Random-Access Accelerator (RAA) is proposed in this work, in order to speed up network access in massive Machine Type Communication (mMTC). RAA exploits Device-To-Device (D2D) communications, where devices with already assigned resources act like relays for the rest of devices trying to gain access in the network. The simulation results show an acceleration in the registration procedure of 99%, and a freed space of the allocated spectrum until 74% in comparison with the conventional Random-Access procedure. Besides, it preserves the same device’s energy consumption compared with legacy networks by using a custom version of Bluetooth as a wireless technology for D2D communications. The proposed framework can be taken into account for the standardization of mMTC in Fifth-Generation-New Radio (5G NR).
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Sun, Wei, Hao Zhang, Li-jun Cai, Ai-min Yu, Jin-qiao Shi, and Jian-guo Jiang. "A Novel Device Identification Method Based on Passive Measurement." Security and Communication Networks 2019 (June 23, 2019): 1–11. http://dx.doi.org/10.1155/2019/6045251.
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Nowadays, with the continuous integration of production network and business network, more and more Industrial Internet of Things and Internal Office Network have been interconnected and evolved into a large-scale enterprise-level intraindustry network. Terminal devices are the basic units of internal network. Accurate identification of the type of device corresponding to the IP address and detailed description of the communication behavior of the device are of great significance for conducting network security risk assessment, hidden danger investigation, and threat warning. Traditional cyberspace surveying and mapping techniques take the form of active measurement, but they cannot be transplanted to large-scale intranet. Resources or specific targets in internal networks are often protected by firewalls, VPNs, gateways, and other technologies, so they are difficult to analyze and determine by active measurement. In this paper, a passive measurement method is proposed to identify and characterize devices in the network through real traffic data. Firstly, a new graph structure mining method is used to determine the server-like devices and host-like devices; then, the NAT-like devices are determined by quantitative analysis of traffic; finally, by qualitative analysis of the NAT-like device traffic, it is determined whether there are server-like devices behind the NAT-like device. This method will prove to be useful in identifying all kinds of devices in network data traffic, detecting unauthorized NAT-like devices and whether there are server-like devices behind the NAT-like devices.
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Hasan Al-Bowarab, Mustafa, Nurul Azma Zakaria, Zaheera Zainal Abidin, and Ziadoon Kamil Maseer. "Review on Device-to-Device Communication in Cellular based Network Systems." International Journal of Engineering & Technology 7, no. 3.20 (September 1, 2018): 435. http://dx.doi.org/10.14419/ijet.v7i3.20.20587.
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In a traditional cellular-network based system, the devices are not allowed to be interconnected directly in the certified mobile bandwidth, and all communications are carried out via the base station (BS). At present, device terminal broadcasting allows devices in the distributed network to act as transmitting relays to each other and reach a massive ad hoc network of networks that is different from the previous cellular architecture that faces technical challenges. Therefore, this article explores the application of a cellular-based two-layer network system that includes a base station (BS) cellular layer, such as cellular-to-device communication and communication between devices. In the proposed two-tier cellular-based network system, user data is transmitted through other users' devices to implement the privacy protection that is lacking in prior communication between devices in cellular systems. To ensure a negligible impact on the performance of current communication between devices, a two-layer network is assimilated to autonomous interference management schemes and associated resource allocation schemes. The findings from this review provide an overview of the major challenges in two-tier networks and propose a two-tier cellular-based system in which user data is routed through other users' devices to implement privacy protection.
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Yi-Wei Ma, Yi-Wei Ma, Jiann-Liang Chen Yi-Wei Ma, Yu-Liang Tang Jiann-Liang Chen, and Kuan-Hung Lai Yu-Liang Tang. "Towards Adaptive Network Resource Orchestration for Cognitive Radio Networks." 網際網路技術學刊 23, no. 5 (September 2022): 1087–97. http://dx.doi.org/10.53106/160792642022092305017.
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<p>This work proposes an adaptive resource orchestration system for a Wireless Local Area Network (WLAN) that is based on the operating principle of Cognitive Radio (CR) technology. By collecting environmental parameters, including the retransmission rate and the channel occupancy rate, the proposed system has “knowledge” of overall transmission behavior and can regulate transmission resources. An Adaptive Connection Assignment (ACA) mechanism is proposed for end devices; it find out target end devices with poor transmission performance, analyzes their alternative Access Point (AP) availability and causes them to change connections to improve transmission performance. An Adaptive Channel Utilization (ACU) mechanism is designed for APs to identify a target AP that is suffering from interference, to analyze its alternative channel availability and to require it to change its working channel to improve transmission efficiency. Results of simulations of various scenarios indicate that the throughput of end devices is increased by 15 to 24%, the throughput of APs is increased by 6 to 47% and the retransmission rate of APs is reduced by 0.4 to 5.3%.</p> <p> </p>
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Rondeau, Christopher M., J. Addison Betances, and Michael A. Temple. "Securing ZigBee Commercial Communications Using Constellation Based Distinct Native Attribute Fingerprinting." Security and Communication Networks 2018 (July 11, 2018): 1–14. http://dx.doi.org/10.1155/2018/1489347.
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This work provides development of Constellation Based DNA (CB-DNA) Fingerprinting for use in systems employing quadrature modulations and includes network protection demonstrations for ZigBee offset quadrature phase shift keying modulation. Results are based on 120 unique networks comprised of seven authorized ZigBee RZSUBSTICK devices, with three additional like-model devices serving as unauthorized rogue devices. Authorized network device fingerprints are used to train a Multiple Discriminant Analysis (MDA) classifier and Rogue Rejection Rate (RRR) estimated for 2520 attacks involving rogue devices presenting themselves as authorized devices. With MDA training thresholds set to achieve a True Verification Rate (TVR) of TVR = 95% for authorized network devices, the collective rogue device detection results for SNR ≥ 12 dB include average burst-by-burst RRR ≈ 94% across all 2520 attack scenarios with individual rogue device attack performance spanning 83.32% < RRR < 99.81%.
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Laguidi, Ahmed, Tarik Hachad, and Lamiae Hachad. "Mobile network connectivity analysis for device to device communication in 5G network." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (February 1, 2023): 680. http://dx.doi.org/10.11591/ijece.v13i1.pp680-687.
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<p><span>Since long term evolved release 14 (LTE R14), the device to device (D2D) communications have become a promising technology for in-band or out-band mobile communication networks. In addition, D2D communications constitute an essential component of the fifth-generation mobile network (5G). For example, to improve capability communication, reduce the power dissipation, reduce latency within the networks and implement new applications and services. However, reducing the congestion in D2D communications and improving the mobile network connectivity are the essential problems to propose these new applications or services. This paper presents new solutions to reduce the congestion of devices around a base station and improve the performance of the D2D network; in terms of the number of connected devices or user equipment (UE). The simulation results show that our proposed solution can improve the network capacity by doubling the number of connected devices (or UE) and reducing the congestion. For this reason, our proposition makes it possible to reduce the financial cost by reducing the cost of deploying equipment. For example, instead of using two base stations, we can use only one station to connect the same number of devices.</span></p>
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Ogogo, Wycliffe Lamech. "Real-Time Monitoring of Network Devices: Its Effectiveness in Enhancing Network Security." East African Journal of Information Technology 3, no. 1 (March 4, 2021): 1–6. http://dx.doi.org/10.37284/eajit.3.1.153.
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The business world has been significantly affected by network intrusion leading to infringement of privacy and unprecedented economic losses. Therefore, real-time monitoring of network devices is important due to the enhanced and complex network systems in organizations and associated cyber threats. Real-time monitoring provides adequate alerts and updates regarding specific networks and their performance as soon as they occur. Constant monitoring of devices also makes it possible for organizations to detect any possible challenges that the networks may be encountering. This paper examines the effectiveness of real-time monitoring of network devices in a bid to enhance network security. The study was an empirical review of recently published research papers, journals, internet sites, and books with relevant content. The findings of this study revealed that Real-time device monitoring has many potential advantages to organizations by securing their systems thereby enhancing their overall performance.
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A., Dr Sathesh. "OPTIMIZED MULTI-OBJECTIVE ROUTING FOR WIRELESS COMMUNICATION WITH LOAD BALANCING." Journal of Trends in Computer Science and Smart Technology 2019, no. 02 (December 23, 2019): 106–20. http://dx.doi.org/10.36548/jtcsst.2019.2.004.
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The rapid advancements in the wireless communication networks have increased the popularity of portable or mobile devices and the network framed with these mobile devices. These mobile networks framed using the volunteering portable devices are decentralized and have dynamic topologies experiencing sudden changes in the network structure. The main reason causing the topology changes are the limited energy availability of the device and their mobility. Improper trafficking of the tasks and improper selection of the portable devices causes maximum energy consumption resulting in the link failures and changes in the topology of the network. So the paper puts forward the hybridized optimization technique to handle the multi-objective problem faced by these decentralized networks. The proposed method is validated using the network simulator-2 to evince throughput, energy consumption and the network longevity achieved by the proposed method.
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Kumar, Vipin, Navneet Malik, Jimmy Singla, N. Z. Jhanjhi, Fathi Amsaad, and Abdul Razaque. "Light Weight Authentication Scheme for Smart Home IoT Devices." Cryptography 6, no. 3 (July 20, 2022): 37. http://dx.doi.org/10.3390/cryptography6030037.
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In today’s world, the use of computer networks is everywhere, and to access the home network we use the Internet. IoT networks are the new range of these networks in which we try to connect different home appliances and try to give commands from a remote place. Access to any device over an insecure network invites various types of attacks. User authentication can be performed using some password or biometric technique. However, when it comes to authenticating a device, it becomes challenging to maintain data security over a secure network such as the Internet. Many encryptions and decryption algorithms assert confidentiality, and hash code or message authentication code MAC is used for authentication. Traditional cryptographic security methods are expensive in terms of computational resources such as memory, processing capacity, and power consumption. They are incompatible with the Internet of Things devices that have limited resources. Although automatic Device-to-Device communication enables new potential applications, the limited resources of the networks’ machines and devices impose various constraints. This paper proposes a home device authentication scheme when these are accessed from a remote place. An authentication device is used for the home network and controller device to control home appliances. Our scheme can prevent various attacks such as replay attacks, server spoofing, and man-in-the-middle attack. The proposed scheme maintains the confidentiality and authenticity of the user and devices in the network. At the same time, we check the system in a simulated environment, and the results show that the network’s performance does not degrade much in terms of delay, throughput, and energy consumed.
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Naz, Naila, Muazzam A. Khan, Suliman A. Alsuhibany, Muhammad Diyan, Zhiyuan Tan, Muhammad Almas Khan, and Jawad Ahmad. "Ensemble learning-based IDS for sensors telemetry data in IoT networks." Mathematical Biosciences and Engineering 19, no. 10 (2022): 10550–80. http://dx.doi.org/10.3934/mbe.2022493.
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<abstract><p>The Internet of Things (IoT) is a paradigm that connects a range of physical smart devices to provide ubiquitous services to individuals and automate their daily tasks. IoT devices collect data from the surrounding environment and communicate with other devices using different communication protocols such as CoAP, MQTT, DDS, etc. Study shows that these protocols are vulnerable to attack and prove a significant threat to IoT telemetry data. Within a network, IoT devices are interdependent, and the behaviour of one device depends on the data coming from another device. An intruder exploits vulnerabilities of a device's interdependent feature and can alter the telemetry data to indirectly control the behaviour of other dependent devices in a network. Therefore, securing IoT devices have become a significant concern in IoT networks. The research community often proposes intrusion Detection Systems (IDS) using different techniques. One of the most adopted techniques is machine learning (ML) based intrusion detection. This study suggests a stacking-based ensemble model makes IoT devices more intelligent for detecting unusual behaviour in IoT networks. The TON-IoT (2020) dataset is used to assess the effectiveness of the proposed model. The proposed model achieves significant improvements in accuracy and other evaluation measures in binary and multi-class classification scenarios for most of the sensors compared to traditional ML algorithms and other ensemble techniques.</p></abstract>
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Ouaissa, Mariya, and A. Rhattoy. "A New Scheme of Group-based AKA for Machine Type Communication over LTE Networks." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 2 (April 1, 2018): 1169. http://dx.doi.org/10.11591/ijece.v8i2.pp1169-1181.
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Machine Type Communication (MTC) is considered as one of the most important approaches to the future of mobile communication has attracted more and more attention. To reach the safety of MTC, applications in networks must meet the low power consumption requirements of devices and mass transmission device. When a large number of MTC devices get connected to the network, each MTC device must implement an independent access authentication process according to the 3GPP standard, which will cause serious traffic congestion in the Long Term Evolution (LTE) network. In this article, we propose a new group access authentication scheme, by which a huge number of MTC devices can be simultaneously authenticated by the network and establish an independent session key with the network respectively. Experimental results show that the proposed scheme can achieve robust security and avoid signaling overload on LTE networks
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Bystrova, I. V., and B. P. Podkopaev. "Fault Isolation in Network of State Automates." Journal of the Russian Universities. Radioelectronics 23, no. 1 (February 28, 2020): 18–29. http://dx.doi.org/10.32603/1993-8985-2020-23-1-18-29.
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Introduction. In the paper a fault isolation problem in the devices combining digital unit by functional diagnostics methods is considered. Networks of state automates are accepted as mathematical models of the devices. Assumed, that functional diagnostics devices for each network component are preliminarily constructed in an optimal way and they consist of a control automata and of a fault discriminator of unit dimension.Aim. To develop functional diagnostics method based on theoretical analysis allowing to decide fault isolation problem in networks of state automation and to reduce computational complexity and hardware redundancy.Materials and methods. An analysis of mathematical description of a network of state automation and functional diagnostics devices for each network component was presented in terms of algebraic theory of functional diagnosis of dynamic systems. A possibility to transform the set of known functional diagnostics devices of the network was demonstrated. The possibility provided a localization of the network component with an error, if the component was unique.Results. A searching procedure of the analytical equations determining supervision automata and fault discriminator for the whole network was proposed. The case when initial functional diagnostics devices for each network component were defined by scalar functions was considered. The obtained result was generalized to the case, when mentioned devices were defined by vector functions. The application of the described method was demonstrated in the example of construction functional diagnostics devices for simplified fragment of the device for forming priorities of mutual aircraft navigation system.Conclusion. Estimation of results by an order criterion was obtained. It was established that with an increase in the number of network components, the reduction of intentioned redundancy by functional diagnostics devices compared with the original version increased significantly.
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Oser, Pascal, Rens W. van der Heijden, Stefan Lüders, and Frank Kargl. "Risk Prediction of IoT Devices Based on Vulnerability Analysis." ACM Transactions on Privacy and Security 25, no. 2 (May 31, 2022): 1–36. http://dx.doi.org/10.1145/3510360.
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Internet of Things (IoT) devices are becoming more widespread not only in areas such as smart homes and smart cities but also in research and office environments. The sheer number, heterogeneity, and limited patch availability provide significant challenges for the security of both office networks and the Internet in general. The systematic estimation of device risks, which is essential for mitigation decisions, is currently a skill-intensive task that requires expertise in network vulnerability scanning, as well as manual effort in firmware binary analysis. This article introduces SAFER, 1 the Security Assessment Framework for Embedded-device Risks, which enables a semi-automated risk assessment of IoT devices in any network. SAFER combines information from network device identification and automated firmware analysis to estimate the current risk associated with the device. Based on past vulnerability data and vendor patch intervals for device models, SAFER extrapolates those observations into the future using different automatically parameterized prediction models. Based on that, SAFER also estimates an indicator for future security risks. This enables users to be aware of devices exposing high risks in the future. One major strength of SAFER over other approaches is its scalability, achieved through significant automation. To demonstrate this strength, we apply SAFER in the network of a large multinational organization, to systematically assess the security level of hundreds of IoT devices on large-scale networks. Results indicate that SAFER successfully identified 531 out of 572 devices leading to a device identification rate of 92.83 %, analyzed 825 firmware images, and predicted the current and future security risk for 240 devices.
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Kuriakose, Jeril, and Sandeep Joshi. "A Comparative Review of Moveable Sensor Location Identification." International Journal of Robotics Applications and Technologies 3, no. 2 (July 2015): 20–37. http://dx.doi.org/10.4018/ijrat.2015070102.
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The evolutions in proficient resources, route discovery protocols, simplicity in hardware design, and other aspects have enabled the wireless sensor networks to have a steady rise in the recent decade. Lately, people started favouring moveable devices in the place of static devices, which brought moveable sensor network into focus. Location information continuously plays a key role in Mobile wireless sensor network (MWSN) and exact location identification has continuously been a test for moveable sensor devices. Installing GPS receivers for every device would also solidify network installation cost for a large network. The unavailability of GPS in covered and underground surrounding has put the installation of GPS into problem. This makes the sensor devices to detect its location coordinates or location reference without using GPS, and is achieved with the help of a special device that knows its location coordinates and protocols, called anchor device. The authors' goal is to confer diverse location identification techniques used by moveable sensor devices to detect their location information. Complications and future issues have also been deliberated.
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Fagbola, Funmilola Ikeolu, and Hein S. Venter. "Smart Digital Forensic Readiness Model for Shadow IoT Devices." Applied Sciences 12, no. 2 (January 12, 2022): 730. http://dx.doi.org/10.3390/app12020730.
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Internet of Things (IoT) is the network of physical objects for communication and data sharing. However, these devices can become shadow IoT devices when they connect to an existing network without the knowledge of the organization’s Information Technology team. More often than not, when shadow devices connect to a network, their inherent vulnerabilities are easily exploited by an adversary and all traces are removed after the attack or criminal activity. Hence, shadow connections pose a challenge for both security and forensic investigations. In this respect, a forensic readiness model for shadow device-inclusive networks is sorely needed for the purposes of forensic evidence gathering and preparedness, should a security or privacy breach occur. However, the hidden nature of shadow IoT devices does not facilitate the effective adoption of the most conventional digital and IoT forensic methods for capturing and preserving potential forensic evidence that might emanate from shadow devices in a network. Therefore, this paper aims to develop a conceptual model for smart digital forensic readiness of organizations with shadow IoT devices. This model will serve as a prototype for IoT device identification, IoT device monitoring, as well as digital potential evidence capturing and preservation for forensic readiness.
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Hossain, Nazmul, Md Zobayer Hossain, and Md Alam Hossain. "An Ontological Security Framework to Secure the SDN based IoT Networks." American Journal of Agricultural Science, Engineering and Technology 5, no. 1 (November 18, 2021): 4–18. http://dx.doi.org/10.54536/ajaset.v5i1.55.
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The IoT (Internet of Things) is now a trendy technology with its numerous apps in multiple areas. It includes a heterogeneous amount of Internet and mutually linked devices. Since the IoT network is characterized by tiny assets that produce less energy and are more flexible, this number of machines is difficult to monitor. SDN (Software Defined Network) is a new network model that facilitates the creation and introduction of fresh networking abstractions, simplifies the management of network and facilitates network development. In this paper, by leveraging the fundamental characteristics represented by Software Defined Networks (SDN), we present an ontological security architecture for IoT networks. Our security architecture restricts access to independently verified IoT devices via the network. To secure the flows in the IoT network infrastructure, we introduced an extra layer and provide a lightweight protocol to authenticate IoT systems. Such an advanced strategy to protection containing IoT device authentication and allowing approved flows can assist secure IoT networks against malicious IoT devices and threats.
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Yuan, Jie, Erxia Li, Chaoqun Kang, Fangyuan Chang, and Xiaoyong Li. "Review of the D2D Trusted Cooperative Mechanism in Mobile Edge Computing." Information 10, no. 8 (August 15, 2019): 259. http://dx.doi.org/10.3390/info10080259.
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Mobile edge computing (MEC) effectively integrates wireless network and Internet technologies and adds computing, storage, and processing functions to the edge of cellular networks. This new network architecture model can deliver services directly from the cloud to the very edge of the network while providing the best efficiency in mobile networks. However, due to the dynamic, open, and collaborative nature of MEC network environments, network security issues have become increasingly complex. Devices cannot easily ensure obtaining satisfactory and safe services because of the numerous, dynamic, and collaborative character of MEC devices and the lack of trust between devices. The trusted cooperative mechanism can help solve this problem. In this paper, we analyze the MEC network structure and device-to-device (D2D) trusted cooperative mechanism and their challenging issues and then discuss and compare different ways to establish the D2D trusted cooperative relationship in MEC, such as social trust, reputation, authentication techniques, and intrusion detection. All these ways focus on enhancing the efficiency, stability, and security of MEC services in presenting trustworthy services.
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Mhetre, Nalini A., Arvind V. Deshpande, and Parikshit Narendra Mahalle. "Device Classification-Based Context Management for Ubiquitous Computing using Machine Learning." International Journal of Engineering and Advanced Technology 10, no. 5 (June 30, 2021): 135–42. http://dx.doi.org/10.35940/ijeat.e2688.0610521.
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Ubiquitous computing comprises scenarios where networks, devices within the network, and software components change frequently. Market demand and cost-effectiveness are forcing device manufacturers to introduce new-age devices. Also, the Internet of Things (IoT) is transitioning rapidly from the IoT to the Internet of Everything (IoE). Due to this enormous scale, effective management of these devices becomes vital to support trustworthy and high-quality applications. One of the key challenges of IoT device management is proactive device classification with the logically semantic type and using that as a parameter for device context management. This would enable smart security solutions. In this paper, a device classification approach is proposed for the context management of ubiquitous devices based on unsupervised machine learning. To classify unknown devices and to label them logically, a proactive device classification model is framed using a k-Means clustering algorithm. To group devices, it uses the information of network parameters such as Received Signal Strength Indicator (rssi), packet_size, number_of_nodes in the network, throughput, etc. Experimental analysis suggests that the well-formedness of clusters can be used to derive cluster labels as a logically semantic device type which would be a context for resource management and authorization of resources.
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WEN, HAO, ZHENG-FU HAN, GUANG-CAN GUO, and PEI-LIN HONG. "QKD NETWORKS WITH PASSIVE OPTICAL ELEMENTS: ANALYSIS AND ASSESSMENT." International Journal of Quantum Information 07, no. 06 (September 2009): 1217–31. http://dx.doi.org/10.1142/s0219749909005730.
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Quantum Key Distribution (QKD) networks are the trends toward multiple users' unconditional secure communication. Based on several passive optical devices, such as beam splitter, optical switch or wavelength divided multiplexer, various types of fiber-based QKD networks have been proposed. However, it is still hard to accurately assess these networks. To find the optimal solution, a general assessment that would not involve detailed schemes is quite necessary. In this paper, we introduce an evaluation method and analyze optical-device-based QKD networks including two rational aspects: (i) network connectivity and network bandwidth which reflect the network's flexibility and performance in theory; (ii) network cost that brings pragmatic restriction on the network construction in practice. Applying this model, we compare five typical types of optical-device-based QKD networks. The explicit results demonstrate the above networks' characteristics and some valuable conclusions.
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Mallela, Sree Naga Raja Sekhar. "IOT-5G-Exploring next-generation media consumption in the area of Journalism." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 1448–51. http://dx.doi.org/10.22214/ijraset.2021.38208.
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Abstract: The most common buzzwords in the world is “The Internet of things” (IoT) and IOT describes the network of physical objects, so known as, "things" those are rooted with sensors in the devices, application software, technologies that is used for the resolution of connecting one end to another end and exchanging information with other devices and systems over the Internet. The IoT 5G technologies can also be used in journalism and the primary focus is to increase M2M interaction of mass communication devices. One way it is “ubiquitous computing” can occur using any device, in any location, and in any format. The Internet of Things (IoT) is all about small cost sensors grabbing data to communicate with one device to another device using cloud solutions. Coming to the 5th generation mobile network. We have already started using 4G networks and as we know that, start with 1G, 2G, 3G, and 4G networks. The 5th generation network is going to enable an upcoming new network that will associate virtually every person globally connected and everything organized including IoT devices, objects and machines. Central communication and Journalism is the activity of gathering right information, evaluating, generating, and presenting broadcast information. It is high time to start using IOT Technology using 5th generation high-speed network connectivity devices to communicate or data transfer in the area of journalism. Keywords: IOT – Internet Of Things, 5G- Fifth Generation in data network, JMC – Journalism and Mass Communications, M2M – Machine to Machine, Cloud , Artificial intelligence and Machine Learning.
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Hizriadi, Ainul, Radea Shiddiq, Ivan Jaya, and Santi Prayudani. "Network Device Monitoring System based on Geographic Information System dan Simple Network Management Protocol." JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING 3, no. 2 (January 20, 2020): 216–23. http://dx.doi.org/10.31289/jite.v3i2.3187.
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Network infrastructure monitoring is an important part of an institute to maintain the stability of computer network devices. One of the functions of computer network monitoring is to find out the data traffic generated in network application. Simple Network Management Protocol is one of protocols for monitoring the data traffic in network device. However, network device administrators still have problems when they want to monitor their network infrastructure, such as device location and data traffic information of network device that is only temporarily stored in the monitoring system, and physical location of network device is not contained in the monitoring system. In order to make it easier for them how to monitor network devices, the Researcher intends to combine Geographic Information Systems (GIS) and SNMP into a web-based monitoring application. Geographic Information System application can display the physical location of network devices, whilethe SNMP application using for monitoring the data traffic in network device,finding out the data traffic that can be generated in real time, and displaying data traffic of network device that has been monitored in to graphical form based on the time and network device used.
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Fachrurrozi, Nurwan Reza, Andri Agustav Wirabudi, and Seandy Arandiant Rozano. "Design of network monitoring system based on LibreNMS using Line Notify, Telegram, and Email notification." SINERGI 27, no. 1 (January 18, 2023): 111. http://dx.doi.org/10.22441/sinergi.2023.1.013.
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Institut Teknologi Telkom Jakarta (IT Telkom Jakarta) is an educational institution that supports student activities and provides internet capabilities to implement online learning systems. As the number of students increases with every year, so does the use of the internet and intranet networks and the experienced network problems. A network administrator is a person who is responsible for managing a computer network. Network administrators usually face network problems in monitoring network devices. This is because the process and operation are done manually. This means network administrators need direct access to the location to monitor all resources. Therefore, a network device monitoring system is needed to manage network devices centrally. This research focuses on the problem of monitoring network devices using open-source tools and software. Based on the implementation results, free network monitoring software such as LibreNMS can track and monitor all devices in all conditions and notify the active device condition in case of network failure such as up, down, reboot to the administrator via Line Notify, Telegram, and Email. With this network monitoring system, IT Telkom Jakarta is expected to be able to implement an integrated and well-monitored internet network system. Besides, the results of this study also produce real-time data on bandwidth usage, logging problems, and resource availability. This can significantly improve network availability and security.
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Curran, Kevin, and Paul Canning. "Wireless Handheld Devices Become Trusted Network Devices." Information Systems Security 16, no. 3 (June 12, 2007): 134–46. http://dx.doi.org/10.1080/10658980701401686.
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Lee, Won Hyoung, Ho Young Hwang, and Jo Woon Chong. "Runtime Estimation of the Number of Active Devices in IEEE 802.15.4 Slotted CSMA/CA Networks with Deferred Transmission and No Acknowledgment Using ARMA Filters." Wireless Communications and Mobile Computing 2018 (September 2, 2018): 1–12. http://dx.doi.org/10.1155/2018/5420876.
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We propose a novel method for estimating the number of active devices in an IEEE 802.15.4 network. Here, we consider an IEEE 802.15.4 network with a star topology where active devices transmit data frames using slotted carrier sense multiple access with collision avoidance (CSMA/CA) medium access control (MAC) protocol without acknowledgment. In our proposed method, a personal area network (PAN) coordinator of a network counts the number of events that a transmission occurs and the number of events that two consecutive slots are idle in a superframe duration, and the PAN coordinator broadcasts the information through a beacon frame. Each device can count the number of slots that each device is in the backoff procedure and the number of the first clear channel assessment (CCA) that each device performs whenever it performs the first CCA after the backoff procedure. Then, each device estimates the number of active devices in the network based on these counted numbers and the information from PAN coordinator with the help of an autoregressive moving average (ARMA) filter. We evaluate the performance of our proposed ARMA-based estimation method via simulations where active devices transmit data frames in IEEE 802.15.4 slotted CSMA/CA networks. Simulation results show that our proposed method gives estimation errors of the number of active devices less than 4.501% when the actual number of active devices is varying from 5 to 80. We compare our proposed method with the conventional method in terms of the average and standard deviation for the estimated number of active devices. The simulation results show that our proposed estimation method is more accurate than the conventional method.
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Shan, Chun, Xiao-ping Wu, Yan Liu, Jun Cai, and Jian-zhen Luo. "IBP Based Caching Strategy in D2D." Applied Sciences 9, no. 12 (June 13, 2019): 2416. http://dx.doi.org/10.3390/app9122416.
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Device to Device (D2D) communication is a key technology in 5th generation wireless systems to increase communication capacity and spectral efficiency. Applying caching into D2D communication networks, the device can retrieve content from other devices by establishing D2D communication links. In this way, the backhaul traffic can be significantly reduced. However, most of the existing caching schemes in D2D are proactive caching, which cannot satisfy the requirement of real-time updating. In this paper, we propose an Indian Buffet Process based D2D caching strategy (IBPSC). Firstly, we construct a geographical D2D communication network to provide high quality D2D communications according to physical closeness between devices. Then devices are divided into several social communities. Devices are ranked by their node importance to community in each community. The base station makes caching decisions for devices according to contrition degree. Experimental results show that IBPSC achieves best network performance.
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Dawadi, Babu R., Danda B. Rawat, Shashidhar R. Joshi, and Pietro Manzoni. "Intelligent Approach to Network Device Migration Planning towards Software-Defined IPv6 Networks." Sensors 22, no. 1 (December 26, 2021): 143. http://dx.doi.org/10.3390/s22010143.
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Internet and telecom service providers worldwide are facing financial sustainability issues in migrating their existing legacy IPv4 networking system due to backward compatibility issues with the latest generation networking paradigms viz. Internet protocol version 6 (IPv6) and software-defined networking (SDN). Bench marking of existing networking devices is required to identify their status whether the existing running devices are upgradable or need replacement to make them operable with SDN and IPv6 networking so that internet and telecom service providers can properly plan their network migration to optimize capital and operational expenditures for future sustainability. In this paper, we implement “adaptive neuro fuzzy inference system (ANFIS)”, a well-known intelligent approach for network device status identification to classify whether a network device is upgradable or requires replacement. Similarly, we establish a knowledge base (KB) system to store the information of device internetwork operating system (IoS)/firmware version, its SDN, and IPv6 support with end-of-life and end-of-support. For input to ANFIS, device performance metrics such as average CPU utilization, throughput, and memory capacity are retrieved and mapped with data from KB. We run the experiment with other well-known classification methods, for example, support vector machine (SVM), fine tree, and liner regression to compare performance results with ANFIS. The comparative results show that the ANFIS-based classification approach is more accurate and optimal than other methods. For service providers with a large number of network devices, this approach assists them to properly classify the device and make a decision for the smooth transitioning to SDN-enabled IPv6 networks.
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Rasheed, Zeeshan, Shahzad Ashraf, Naeem Ahmed Ibupoto, Pinial Khan Butt, and Emad Hussen Sadiq. "SDS: Scrumptious Dataflow Strategy for IoT Devices in Heterogeneous Network Environment." Smart Cities 5, no. 3 (September 5, 2022): 1115–28. http://dx.doi.org/10.3390/smartcities5030056.
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Communication technologies have drastically increased the number of wireless networks. Heterogeneous networks have now become an indispensable fact while designing the new networks and the way the data packet moves from device to device opens new challenges for transmitting the packet speedily, with maximum throughput and by consuming only confined energy. Therefore, the present study intends to provide a shrewd communication link among all IoT devices that becomes part of numerous heterogeneous networks. The scrumptious dataflow strategy (SDS) for IoT devices in the heterogeneous network environment is proposed and it would deal with all link selection and dataflow challenges. The SDS would accomplish the targeted output in five steps: Step 1 determines the utility rate of each heterogeneous link. Step 2 develops a link selection attribute (LSA) that gauges the loads of network features used for the link selection process. Step 3 calculates the scores of all heterogeneous networks. Step 4 takes the LSA table and computes the network preference for different scenarios, such as round trip time (RTTP), network throughput, and energy consumption. Step 5 sets the priority of heterogeneous networks based on the scores of network attributes. Performance of the proposed SDS mechanism with state of the art network protocols, such as high-speed packet access (HSPA), content-centric networking (CCN), and dynamic source routing (DSR), was determined by conducting a simulation with NS2 and, consequently, the SDS exhibited its shrewd performance. During comparative analysis, in terms of round trip time, the SDS proved that it utilized only 16.4 milliseconds to reach IoT device 50 and was first among all other protocols. Similarly, for network throughput, at IoT device 50, the throughputs of the SDS are recorded at 40% while the rest of other protocols were dead. Finally, while computing the energy consumption used to reach IoT device 50, the SDS was functional and possessed more than half of its energy compared to the other protocols. The SDS only utilized 302 joules while the rest of the protocols were about to die as they had consumed all of their energy.
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Reinehr Gobatto, Leonardo, Pablo Rodrigues, Mateus Saquetti Pereira de Carvalho Tirone, Weverton Luis da Costa Cordeiro, and José Rodrigo Furlanetto Azambuja. "Programmable Data Planes meets In-Network Computing: A Review of the State of the Art and Prospective Directions." Journal of Integrated Circuits and Systems 16, no. 2 (August 17, 2021): 1–8. http://dx.doi.org/10.29292/jics.v16i2.497.
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Improving network traffic in networks is one of the concerns between networking researchers and network operators since the architecture of modern networks still faces challenges to process large data traffic without the cost of consuming a significant amount of resources not related to computing specifically. On the other hand, network programmability has enabled the development of new applications and network services, from software-defined networking to domain-specific languages created to program network devices and specify their behavior. The development of programmable hardware and hardware accelerators like FPGAs, GPUs, and CPUs help this new paradigm go one step further. Use the artifact of programmability of these devices to solve problems, such as improve the processing of data traffic is the key of in-network computing. It offers the opportunity to execute programs typically running on end-hosts within programmable network devices already incorporated on the network, thus being capable of provides a reduction on the in-network processing load and requires no extra cost, since operations can be concluded using a fewer amount of devices of the network and no extra device are needed. In this paper, we survey in-network computing, as well as we suggest classifying related works to in-network computing according to the hardware accelerator used. Also, we discuss challenges and research directions.
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Burger, Alwyn, Gregor Schiele, and David W. King. "Reconfigurable Embedded Devices Using Reinforcement Learning to Develop Action Policies." ACM Transactions on Autonomous and Adaptive Systems 15, no. 4 (December 31, 2020): 1–25. http://dx.doi.org/10.1145/3487920.
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The size of sensor networks supporting smart cities is ever increasing. Sensor network resiliency becomes vital for critical networks such as emergency response and waste water treatment. One approach is to engineer “self-aware” sensors that can proactively change their component composition in response to changes in work load when critical devices fail. By extension, these devices could anticipate their own termination, such as battery depletion, and offload current tasks onto connected devices. These neighboring devices can then reconfigure themselves to process these tasks, thus avoiding catastrophic network failure. In this article, we compare and contrast two types of self-aware sensors. One set uses Q-learning to develop a policy that guides device reaction to various environmental stimuli, whereas the others use a set of shallow neural networks to select an appropriate reaction. The novelty lies in the use of field programmable gate arrays embedded on the sensors that take into account internal system state, configuration, and learned state-action pairs, which guide device decisions to meet system demands. Experiments show that even relatively simple reward functions develop both Q-learning policies and shallow neural networks that yield positive device behaviors in dynamic environments.
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Cho, Seongsoo, and Bhanu Shrestha. "A Study on Improving M2M Network Security through Abnormal Traffic Control." Applied Sciences 12, no. 21 (October 26, 2022): 10836. http://dx.doi.org/10.3390/app122110836.
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Machine-to-machine (M2M) intelligent network devices are exposed to vulnerable networks and security threats always exist. The devices are composed of low-capacity hardware by their nature and are exposed to various security threats such as worms, viruses and distributed denial of service (DDoS) flooding attacks due to lack of security or antivirus programs installed in the personal computer environment. In this paper, we proposed a network filter that improves the security of M2M intelligent networks by configuring the network security filter in a specific form that can be adapted to M2M intelligent networks. The proposed filter increases user convenience and decreases unnecessary loss. Experimental results show that when the security filter is applied, the response speed of the device improved by more than 50% in an abnormal traffic environment with a cost of less than 10% delay, depending upon the characteristics of the device.
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Tilwari, Valmik, MHD Hindia, Kaharudin Dimyati, Dushantha Jayakody, Sourabh Solanki, Rashmi Sinha, and Effariza Hanafi. "MBMQA: A Multicriteria-Aware Routing Approach for the IoT 5G Network Based on D2D Communication." Electronics 10, no. 23 (November 26, 2021): 2937. http://dx.doi.org/10.3390/electronics10232937.
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With the rapid development of future wireless networks, device-to-device (D2D) technology is widely used as the communication system in the Internet of Things (IoT) fifth generation (5G) network. The IoT 5G network based on D2D communication technology provides pervasive intelligent applications. However, to realize this reliable technology, several issues need to be critically addressed. Firstly, the device’s energy is constrained during its vital operations due to limited battery power; thereby, the connectivity will suffer from link failures when the device’s energy is exhausted. Similarly, the device’s mobility alters the network topology in an arbitrary manner, which affects the stability of established routes. Meanwhile, traffic congestion occurs in the network due to the backlog packet in the queue of devices. This paper presents a Mobility, Battery, and Queue length Multipath-Aware (MBMQA) routing scheme for the IoT 5G network based on D2D communication to cope with these key challenges. The back-pressure algorithm strategy is employed to divert packet flow and illuminate the device selection’s estimated value. Furthermore, a Multiple-Attributes Route Selection (MARS) metric is applied for the optimal route selection with load balancing in the D2D-based IoT 5G network. Overall, the obtained simulation results demonstrate that the proposed MBMQA routing scheme significantly improves the network performance and quality of service (QoS) as compared with the other existing routing schemes.
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Menon, Varun G., Joe Prathap Pathrose, and Jogi Priya. "Ensuring Reliable Communication in Disaster Recovery Operations with Reliable Routing Technique." Mobile Information Systems 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/9141329.
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The purpose of this research paper is to ensure reliable and continuous communication between the rescue officers and other people during disaster recovery and reconstruction operations. Most of the communication infrastructure gets damaged during the disaster and proper communication cannot be established in the area which leads to longer delays in emergency operations and increased damage to life and property. Various methods proposed to enable communication between the people using wireless ad hoc networks do not guarantee reliable delivery of data with fast moving devices. This paper presents a Reliable Routing Technique (RRT) that ensures reliable data delivery at the destination device even when the people with the mobile devices are moving in the network. We make use of the broadcasting property of the wireless network and create a priority list of probable forwarding candidates at each device. With this technique, RRT ensures that if a forwarder device is unable to forward the data packet due to movement of mobile devices, the next priority candidate forwards the data packet to the destination device, thus ensuring reliability of data delivery in the network. Simulation results show that RRT achieves significant performance improvement with better data delivery in ad hoc networks.
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Lee, Minbaek, Meg Noah, June Park, Maeng-Je Seong, Young-Kyun Kwon, and Seunghun Hong. "“Textured” Network Devices: Overcoming Fundamental Limitations of Nanotube/Nanowire Network-Based Devices." Small 5, no. 14 (July 17, 2009): 1642–48. http://dx.doi.org/10.1002/smll.200801500.
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Ullah, Farman, Ghulam Sarwar, and Sungchang Lee. "A Network and Visual Quality Aware N-Screen Content Recommender System Using Joint Matrix Factorization." Scientific World Journal 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/806517.
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We propose a network and visual quality aware N-Screen content recommender system. N-Screen provides more ways than ever before to access multimedia content through multiple devices and heterogeneous access networks. The heterogeneity of devices and access networks present new questions of QoS (quality of service) in the realm of user experience with content. We propose, a recommender system that ensures a better visual quality on user’s N-screen devices and the efficient utilization of available access network bandwidth with user preferences. The proposed system estimates the available bandwidth and visual quality on users N-Screen devices and integrates it with users preferences and contents genre information to personalize his N-Screen content. The objective is to recommend content that the user’s N-Screen device and access network are capable of displaying and streaming with the user preferences that have not been supported in existing systems. Furthermore, we suggest a joint matrix factorization approach to jointly factorize the users rating matrix with the users N-Screen device similarity and program genres similarity. Finally, the experimental results show that we also enhance the prediction and recommendation accuracy, sparsity, and cold start issues.
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Suhartono, Joni. "Merencanakan Keamanan Jaringan Komputer." ComTech: Computer, Mathematics and Engineering Applications 2, no. 1 (June 1, 2011): 467. http://dx.doi.org/10.21512/comtech.v2i1.2784.
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Communication via wireless devices provides many benefits to companies and users, such as portability and flexibility, productivity improvement, and low installation fee. Wireless technology covers a variety of abilities on use and needs. A WLAN device as an example allows users to get mobile from a place to another without wires attached and connection loss. Wirelesss means more flexible, more efficient, and cost reduced. Adhoc network such as Bluetooth allows for data synchronization with network system and sharing application among devices. Bluetooth functions to diminish wires for printers and other supporting devices. Portable devices such as PDA and cell phone allow remote users to synchronize personal databases and provide accesses to email, browsing, and internet access. Thus, security risks are very influential on wireless network. Some of the risks are almost the same as the wired network, few are derived from other cable networks and some others are new.
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Schuba, C. L., J. Goldschmidt, M. F. Speer, and M. Hefeeda. "Scaling network services using programmable network devices." Computer 38, no. 4 (April 2005): 52–60. http://dx.doi.org/10.1109/mc.2005.139.
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Chen, Whai-En, Yi-Bing Lin, Tai-Hsiang Yen, Syuan-Ru Peng, and Yun-Wei Lin. "DeviceTalk: A No-Code Low-Code IoT Device Code Generation." Sensors 22, no. 13 (June 30, 2022): 4942. http://dx.doi.org/10.3390/s22134942.
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The deployment of a client–server-based distributed intelligent system involves application development in both the network domain and the device domain. In the network domain, an application server (typically in the cloud) is deployed to execute the network applications. In the device domain, several Internet of Things (IoT) devices may be configured as, for example, wireless sensor networks (WSNs), and interact with each other through the application server. Developing the network and the device applications are tedious tasks that are the major costs for building a distributed intelligent system. To resolve this issue, a low-code or no-code (LCNC) approach has been purposed to automate code generation. As traditional LCNC solutions are highly generic, they tend to generate excess code and instructions, which will lack efficiency in terms of storage and processing. Fortunately, optimization of automated code generation can be achieved for IoT by taking advantage of the IoT characteristics. An IoT-based distributed intelligent system consists of the device domain (IoT devices) and the network domain (IoT server). The software of an IoT device in the device domain consists of the Device Application (DA) and the Sensor Application (SA). Most IoT LCNC approaches provide code generation in the network domain. Very few approaches automatically generate the DA code. To our knowledge, no approach supports the SA code generation. In this paper, we propose DeviceTalk, an LCNC environment for the DA and the SA code development. DeviceTalk automatically generates the code for IoT devices to speed up the software development in the device domain for a distributed intelligent system. We propose the DeviceTalk architecture, design and implementation of the code generation mechanism for the IoT devices. Then, we show how a developer can use the DeviceTalk Graphical User Interface (GUI) to exercise LCNC development of the device software.
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Alsaffar, Mohammad, Abdulsattar Abdullah Hamad, Abdullah Alshammari, Gharbi Alshammari, Tariq S. Almurayziq, Mohammed Shareef Mohammed, and Wegayehu Enbeyle. "Network Management System for IoT Based on Dynamic Systems." Computational and Mathematical Methods in Medicine 2021 (December 13, 2021): 1–8. http://dx.doi.org/10.1155/2021/9102095.
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The Internet of Things (IoT) has the potential to transform the public sector by combining the leading technical and business trends of mobility, automation, and data analysis to dramatically alter the way public bodies collect data and information. Embedded sensors, actuators, and other devices that capture and transmit information about network activity in real-time are used in the Internet of Things to connect networks of physical objects. The design of a network management system for an IoT network is presented in this paper, which uses the edge computing model. This design is based on the Internet management model, which uses the SNMP protocol to communicate between managed devices, and a gateway, which uses the SOAP protocol to communicate with a management application. This work allowed for the identification and analysis of the primary network management system initiatives for IoT networks, in which there are four fundamental device management requirements for any deployment of IoT devices: provisioning and authentication, configuration and control, monitoring and diagnostics, and software updates and maintenance.
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Kim, Sangdae, Cheonyong Kim, Hyunchong Cho, and Kwansoo Jung. "A Hierarchical Routing Graph for Supporting Mobile Devices in Industrial Wireless Sensor Networks." Sensors 21, no. 2 (January 11, 2021): 458. http://dx.doi.org/10.3390/s21020458.
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As many industrial applications require real-time and reliability communication, a variety of routing graph construction schemes were proposed to satisfy the requirements in Industrial Wireless Sensor Networks (IWSNs). Each device transmits packet through a route which is designated based on the graph. However, as existing studies consider a network consists of static devices only, they cannot cope with the network changes by movement of mobile devices considered important in the recent industrial environment. Thus, the communication requirements cannot be guaranteed because the existing path is broken by the varying network topology. The communication failure could cause critical problems such as malfunctioning equipment. The problem is caused repeatedly by continuous movement of mobile devices, even if a new graph is reconstructed for responding the changed topology. To support mobile devices exploited in various industrial environments, we propose a Hierarchical Routing Graph Construction (HRGC). The HRGC is consisted of two phases for hierarchical graph construction: In first phase, a robust graph called skeleton graph consisting only of static devices is constructed. The skeleton graph is not affected by network topology changes and does not suffer from packet loss. In second phase, the mobile devices are grafted into the skeleton graph for seamless communication. Through the grafting process, the routes are established in advance for mobile device to communicate with nearby static devices in anywhere. The simulation results show that the packet delivery ratio is improved when the graph is constructed through the HRGC.
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Kim , Sangdae, Cheonyong Kim , Hyunchong Cho , and Kwansoo Jung . "A Hierarchical Routing Graph for Supporting Mobile Devices in Industrial Wireless Sensor Networks." Sensors 21, no. 2 (January 11, 2021): 458. http://dx.doi.org/10.3390/s21020458.
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As many industrial applications require real-time and reliability communication, a variety of routing graph construction schemes were proposed to satisfy the requirements in Industrial Wireless Sensor Networks (IWSNs). Each device transmits packet through a route which is designated based on the graph. However, as existing studies consider a network consists of static devices only, they cannot cope with the network changes by movement of mobile devices considered important in the recent industrial environment. Thus, the communication requirements cannot be guaranteed because the existing path is broken by the varying network topology. The communication failure could cause critical problems such as malfunctioning equipment. The problem is caused repeatedly by continuous movement of mobile devices, even if a new graph is reconstructed for responding the changed topology. To support mobile devices exploited in various industrial environments, we propose a Hierarchical Routing Graph Construction (HRGC). The HRGC is consisted of two phases for hierarchical graph construction: In first phase, a robust graph called skeleton graph consisting only of static devices is constructed. The skeleton graph is not affected by network topology changes and does not suffer from packet loss. In second phase, the mobile devices are grafted into the skeleton graph for seamless communication. Through the grafting process, the routes are established in advance for mobile device to communicate with nearby static devices in anywhere. The simulation results show that the packet delivery ratio is improved when the graph is constructed through the HRGC.
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Zhu, Fangzhou, Liang Liu, Simin Hu, Ting Lv, and Renjun Ye. "WND-Identifier: Automated and Efficient Identification of Wireless Network Devices." Security and Communication Networks 2021 (November 20, 2021): 1–16. http://dx.doi.org/10.1155/2021/9069123.
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The widespread application of wireless communication technology brings great convenience to people, but security and privacy problems also arise. To assess and guarantee the security of wireless networks and user devices, discovering and identifying wireless devices become a foremost task. Currently, effective device identification is still a challenging issue, as device fingerprinting requires huge training datasets and is difficult to expand, and rule-based identification is not accurate and reliable enough. In this paper, we propose WND-Identifier, a universal and extensible framework for the identification of wireless devices, which can generate high-precision device labels (vendor, type, and product model) efficiently without user interaction. We first introduce the concept of device-info-related network protocols. WND-Identifier makes full use of the natural language features in such protocol messages and combines with the device description in the welcome page, thereby utilizing extraction rules to generate concrete device labels. Considering that the device information in the protocol messages may be incomplete or forged, we further take advantage of the application logic independence and stability of the device-info-related protocol, so as to build a multiprotocol text classification model, which maps the device to a known label. We conduct experiments in homes and public networks and present three application scenarios to verify the effectiveness of WND-Identifier.
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Maheswari, G. Uma. "Fuzzy QoS Based OLSR Network." International Journal of Interdisciplinary Telecommunications and Networking 3, no. 1 (January 2011): 50–55. http://dx.doi.org/10.4018/jitn.2011010104.
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Quality-of-Service (QoS) routing protocol is developed for mobile Ad Hoc Networks. MANET is a self configuring network of mobile devices connected by wireless links. Each device in the MANET is free to move independently in any direction; therefore, it changes links to other devices frequently. The proposed QoS-based routing in the Optimized Link State Routing (OLSR) protocol relates bandwidth and delay using a fuzzy logic algorithm. The path computations are examined and the reason behind the selection of bandwidth and delay metrics is discussed. The performance of the protocol is investigated by simulation. The results in FQOLSR indicate an improvement in mobile wireless networks compared with the existing QOLSR system.
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Jia, Liang, Ye Tian, and Junguo Zhang. "Identifying Animals in Camera Trap Images via Neural Architecture Search." Computational Intelligence and Neuroscience 2022 (February 7, 2022): 1–15. http://dx.doi.org/10.1155/2022/8615374.
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Wild animals are essential for ecosystem structuring and stability, and thus they are important for ecological research. Since most wild animals have high athletic or concealable abilities or both, it is used to be relatively difficult to acquire evidence of animal appearances before applications of camera traps in ecological researches. However, a single camera trap may produce thousands of animal images in a short period of time and inevitably ends up with millions of images requiring classification. Although there have been many methods developed for classifying camera trap images, almost all of them follow the pattern of a very deep convolutional neural network processing all camera trap images. Consequently, the corresponding surveillance area may need to be delicately controlled to match the network capability, and it may be difficult to expand the area in the future. In this study, we consider a scenario in which camera traps are grouped into independent clusters, and images produced by a cluster are processed by an edge device installed with a customized network. Accordingly, edge devices in this scenario may be highly heterogeneous due to cluster scales. Resultantly, networks popular in the classification of camera trap images may not be deployable for edge devices without modifications requiring the expertise which may be hard to obtain. This motivates us to automatize network design via neural architecture search for edge devices. However, the search may be costly due to the evaluations of candidate networks, and its results may be infeasible without considering the resource limits of edge devices. Accordingly, we propose a search method using regression trees to evaluate candidate networks to lower search costs, and candidate networks are built based on a meta-architecture automatically adjusted regarding to the resource limits. In experiments, the search consumes 6.5 hours to find a network applicable to the edge device Jetson X2. The found network is then trained on camera trap images through a workstation and tested on Jetson X2. The network achieves competitive accuracies compared with the automatically and the manually designed networks.
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Shafiq, Muhammad, Zhihong Tian, Ali Kashif Bashir, Korhan Cengiz, and Adnan Tahir. "SoftSystem: Smart Edge Computing Device Selection Method for IoT Based on Soft Set Technique." Wireless Communications and Mobile Computing 2020 (October 9, 2020): 1–10. http://dx.doi.org/10.1155/2020/8864301.
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The Internet of Things (IoT) is growing day by day, and new IoT devices are introduced and interconnected. Due to this rapid growth, IoT faces several issues related to communication in the edge computing network. The critical issue in these networks is the effective edge computing IoT device selection whenever there are several edge nodes to carry information. To overcome this problem, in this paper, we proposed a new framework model named SoftSystem based on the soft set technique that recommends useful IIoT devices. Then, we proposed an algorithm named Softsystemalgo. For the proposed system, three different parameters are selected: IoT Device Security (IDSC), IoT Device Storage (IDST), and IoT Device Communication Speed (IDCS). We also find out the most significant parameters from the given set of parameters. It is evident that our proposed system is effective for the selection of edge computing devices in the IoT network.
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Manin, A. V., and D. B. Vyner. "System of monitoring parameters of distribution grid with corrective control based on neural network." Vestnik IGEU, no. 4 (August 31, 2022): 35–45. http://dx.doi.org/10.17588/2072-2672.2022.4.035-045.
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Background. As a rule, the control of compensating devices is carried out in the automatic control system with sensors of network parameters and control system included in a specific node of the electrical network. However, the general state of the electrical network in terms of reactive power flows is not considered. At present, static VAR compensators are mostly spread. They are designed on the principle of an indirect compensation system, which has several disadvantages. In this regard, to optimize reactive power flows and maintain the specified voltage values in the network nodes with an abruptly variable nature of reactive power consumption, it is necessary to stabilize the required network parameters and minimize the loss of electrical energy due to the flow of reactive power. Materials and methods. To improve the energy efficiency of corrective devices, it is proposed to use static VAR compensators based on magnetic valve elements. To generate control actions, an artificial neural network (ANN) module is introduced into the monitoring to predict the capacities of consumers. Such a neural network is based on an electrical network model described by the combined matrix method. The main processor generates control signals for corrective devices. Results. The authors have proposed to generate control signals for corrective devices by processing information received from remote voltage sensors and current sensors of the distribution grid. The proposed system for monitoring the distribution grid makes it possible to stabilize the required parameters of the network for consumers, to minimize the loss of electrical energy due to the flow of reactive power. Conclusions. The block of neural networks minimizes the emergency situations and accidents. The use of the static VAR compensators based on magnetic valve elements will additionally improve the energy efficiency of the distribution network monitoring system. The use of matrix analysis of network parameters in the distribution network of monitoring system to generate control signals for corrective devices allows optimizing networks in such a way as to minimize reactive power losses to select and install reactive power compensation devices and control them. The use of SVC based on magnetic valve elements as a corrective device improves the efficiency of reactive power compensation in networks with an abruptly variable nature of electrical energy consumption.
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Jailton, José, Tassio Carvalho, Jasmine Araújo, and Renato Francês. "Relay Positioning Strategy for Traffic Data Collection of Multiple Unmanned Aerial Vehicles Using Hybrid Optimization Systems: A FANET-Based Case Study." Wireless Communications and Mobile Computing 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/2865482.
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In the new context of Next Generation Networks, Aerial Ad Hoc Networks, also known as FANET (Flying Ad Hoc Network), are being used to monitor areas of difficult access. Owing to the dynamism and autoconfiguration of this type of network, a strategy is needed to position its devices (drones) to ensure it can achieve good performance. In light of this, this paper proposes a flight path planning model, which involves a metaheuristic optimization-based approach. The proposal relied on the artificial neural networks to optimize the positioning of the relay device, so that the throughput between the other devices could be increased; the benefits of the proposal were demonstrated through simulations.
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Kodati, Sarangam, Kumbala Pradeep Reddy, Thotakura Veerananna, S. Govinda Rao, and G. Anil Kumar. "Security Framework Connection Assistance for IoT Device Secure Data communication." E3S Web of Conferences 309 (2021): 01061. http://dx.doi.org/10.1051/e3sconf/202130901061.
Full textAbstract:
Today, Internet of Things (IoT) services has been increasing extensively because of their optimum device sizes and their developed network infrastructure that includes devices based on internet embedded with various sensors, actuators, communication, and storage components providing connection and data exchange. Presently number of industries use vast number of IoT devices, there are some challenges like reducing the risks and threats that exposure, accommodating the huge number of IoT devices in network and providing secure vulnerabilities have risen. Supervised learning has recently been gaining popularity to provide device classification. But this supervised learning became unrealistic as producing millions of new IoT devices each year, and insufficient training data. In this paper, security framework connection assistance for IoT device secured data communication is proposed. A multi-level security support architecture which combines clustering technique with deep neural networks for designing the resource oriented IoT devices with high security and these are enabling both the seen and unseen device classification. The datasets dimensions are reduced by considering the technique as auto encoder. Therefore in between accuracy and overhead classification good balancing is established. The comparative results are describes that proposed security system is better than remaining existing systems.
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Qomarudin, Muhammad Faisal, and Agit Amrullah. "SISTEM MONITORING JARINGAN REALTIME BERBASIS INTERNET CONTROL MESSAGE PROTOCOL." JINTECH: Journal Of Information Technology 3, no. 2 (August 12, 2022): 67–80. http://dx.doi.org/10.22373/jintech.v3i2.1935.
Full textAbstract:
Network monitoring in the company is more extensive and complex, each device must be connected to the network so that there are no obstacles when there is receiving and sending data from various devices. Problems on computer networks cannot be predicted when they occur and continuous monitoring is needed to ensure the network is connected properly and it is difficult to troubleshoot network damage. Therefore, a network monitoring system is needed to check the network so that administrators can find out network conditions. By using the Internet Control Message Protocol to check the network continuously so that it can find out the condition of the device, taking into account the latency and data obtained by Packet Internet Gopher. Network checks and notifications use a backdoor working system or through a background process, control the process is also a network check log to find out which devices are often disconnected and to make network troubleshooting easier. In this paper, will be building a network monitoring system that displays network status and monitors the network continuously with telegram notifications, network logs to facilitate troubleshooting, Internet Protocol management and backdoor system settings by the name of SIMONIT.