Journal articles: 'Mobile wireless computing networks'

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Liu, Zhou-zhou, and Shi-ning Li. "Sensor-cloud data acquisition based on fog computation and adaptive block compressed sensing." International Journal of Distributed Sensor Networks 14, no. 9 (September 2018): 155014771880225. http://dx.doi.org/10.1177/1550147718802259.

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The emergence of sensor-cloud system has completely changed the one-to-one service mode of traditional wireless sensor networks, and it greatly expands the application field of wireless sensor networks. As the high delay of large-scale data processing tasks in sensor-cloud, a sensor-cloud data acquisition scheme based on fog computing and adaptive block compressive sensing is proposed. First, the sensor-cloud framework based on fog computing is constructed, and the fog computing layer includes many wireless mobile nodes, which helps to realize the implementation of information transfer management between lower wireless sensor networks layer and upper cloud computing layer. Second, in order to further reduce network traffic and improve data processing efficiency, an adaptive block compressed sensing data acquisition strategy is proposed in the lower wireless sensor networks layer. By dynamically adjusting the size of the network block and building block measurement matrix, the implementation of sensor compressed sensing data acquisition is achieved; in order to further balance the lower wireless sensor networks’ node energy consumption, reduce the time delay of data processing task in fog computing layer, the mobile node data acquisition path planning strategy and multi-mobile nodes collaborative computing system are proposed. Through the introduction of the fitness value constraint transformation processing technique and parallel discrete elastic collision optimization algorithm, the efficient processing of the fog computing layer data is realized. Finally, the simulation results show that the sensor-cloud data acquisition scheme can effectively achieve large-scale sensor data efficient processing. Moreover, compared with cloud computing, the network traffic is reduced by 20% and network task delay is reduced by 12.8%–20.1%.

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Wang, Xingzhu. "A Collaborative Detection Method of Wireless Mobile Network Intrusion Based on Cloud Computing." Wireless Communications and Mobile Computing 2022 (October 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/1499736.

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In order to improve the communication security of wireless mobile network, a collaborative intrusion detection method based on cloud computing is studied. The mobile terminal and the cloud computing platform are connected by the wireless mobile network. The cloud computing platform authentication server adopts a dual server and multifactor authentication scheme for mobile cloud computing to provide authentication services for mobile terminal users. The web server of the cloud computing platform uses the intrusion node detection protocol of the neighbor classification mechanism to provide a communication security protocol for users; Using the HMM algorithm, the intrusion detection module of the computing platform realizes the intrusion detection of wireless mobile network. Finally, using authentication service, security protocol, and intrusion detection module completes the cooperative detection of mobile network intrusion. The experimental results show that this method can realize the cooperative detection of wireless mobile network intrusion, and the detection accuracy is as high as 98%, which ensures the communication security of wireless mobile network.

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Jeong, Young-Sik, Jae Dong Lee, Jeong-Bae Lee, Jai-Jin Jung, and Jong Hyuk Park. "An Efficient and Securem-IPS Scheme of Mobile Devices for Human-Centric Computing." Journal of Applied Mathematics 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/198580.

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Recent rapid developments in wireless and mobile IT technologies have led to their application in many real-life areas, such as disasters, home networks, mobile social networks, medical services, industry, schools, and the military. Business/work environments have become wire/wireless, integrated with wireless networks. Although the increase in the use of mobile devices that can use wireless networks increases work efficiency and provides greater convenience, wireless access to networks represents a security threat. Currently, wireless intrusion prevention systems (IPSs) are used to prevent wireless security threats. However, these are not an ideal security measure for businesses that utilize mobile devices because they do not take account of temporal-spatial and role information factors. Therefore, in this paper, an efficient and secure mobile-IPS (m-IPS) is proposed for businesses utilizing mobile devices in mobile environments for human-centric computing. Them-IPS system incorporates temporal-spatial awareness in human-centric computing with various mobile devices and checks users’ temporal spatial information, profiles, and role information to provide precise access control. And it also can extend application ofm-IPS to the Internet of things (IoT), which is one of the important advanced technologies for supporting human-centric computing environment completely, for real ubiquitous field with mobile devices.

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Patalbansi, Vikram, and Dr G. Prasanna Laxmi. "Mobile Cloud Computing Cryptographic Scheme." Journal of University of Shanghai for Science and Technology 23, no. 06 (June 19, 2021): 1148–57. http://dx.doi.org/10.51201/jusst/21/05394.

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The ubiquitous network like Mobile Cloud Computing (MCC) provides a high quality of wireless services depending upon the wireless communication system network security level. And so many researches are carried out by the researcher on security algorithms for wireless communication system constructed in different network reliability. In our proposed thesis paper, on a theoretical basis, we developed the theory of MCC Security Layer Protocol security system in which we used the cryptographic hash function SHA-256 to generate a private key for entities, RC5 encryption, and decryption algorithm, Temporal Key Integrity Protocol (TKIP) generating a dynamic sequential key and CRC-32 checksum to detecting the error in our packets. The MSLP uses the stored symmetric secret key calculated on the basis of the Diffie-Hellman Key sharing scheme to generate keystream for cryptography functions. The secret key stored in the device’s filesystem our database prior to the deployment on Mobile Cloud Computing and remains the same throughout the session of communication. These systems use the dynamic initialization vector to avoid reply attacks and message integrity code calculated on source and destination devices addresses and actual frame contents. In the proposed thesis paper we analyze the security measures at the MSLP level and before transmitting information over the mobile networks, the information is encrypted in the form of frames and at the physical layer, this frame converted into its equivalent radio signals.

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Paliwal, Rakesh, and Irfan Khan. "Design and Analysis of Soft Computing Based Improved Routing Protocol in WSN for Energy Efficiency and Lifetime Enhancement." International Journal on Recent and Innovation Trends in Computing and Communication 10, no. 3 (April 13, 2022): 12–24. http://dx.doi.org/10.17762/ijritcc.v10i3.5521.

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Mobile wireless sensor networks have been developed as a result of recent advancements in wireless technologies. Sensors in the network are low-cost and have a short battery life, in addition to their mobility. They are more applicable in terms of the essential properties of these networks. These networks have a variety of uses, including search and rescue operations, health and environmental monitoring, and intelligent traffic management systems, among others. According to the application requirements, mobile wireless sensor nodes are energy limited equipment, so energy conservation is one of the most significant considerations in the design of these networks. Aside from the issues posed by sensor node mobility, we should also consider routing and dynamic clustering. According to studies, cluster models with configurable parameters have a substantial impact on reducing energy usage and extending the network's lifetime. As a result, the primary goal of this study is to describe and select a smart method for clustering in mobile wireless sensor networks utilizing evolutionary algorithms in order to extend the network's lifetime and ensure packet delivery accuracy. For grouping sensor nodes in this work, the Genetic Algorithm is applied initially, followed by Bacterial Conjugation. The simulation's results show a significant increase in clustering speed acceleration. The speed of the nodes is taken into account in the suggested approach for calibrating mobile wireless sensor nodes.

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Oksiiuk, Oleksandr, and Vadym Krotov. "ANALYSIS AND CHOICE OF ROUTING PROTOCOLS IN WIRELESS AD HOC NETWORKS BASED ON THE USE THE NEURAL NETWORK." Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska 9, no. 1 (March 3, 2019): 53–55. http://dx.doi.org/10.5604/01.3001.0013.0921.

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In the past few years, we have seen a rapid expansion in the field of mobile computing due to the proliferation of inexpensive, widely available wireless devices. However, current devices, applications and protocols are solely focused on cellular or wireless local area networks (WLANs), not taking into account the great potential offered by ad hoc networking. Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized network management. In such networks, the wireless mobile nodes may dynamically enter the network as well as leave the network. Mobility and dynamic topology are the main characteristics of ad hoc networks. In the last years, the hundreds of new routing protocols were designed, that are used for the various scenarios of this design space. The routing features in wireless ad hoc networks are described. The corresponding routing protocols are reviewed. The paper proposes a method for selecting the preferred protocol wireless networks using the mathematical tools of neural networks.

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Alnezari, Amani S., and Nasser-Eddine Rikli. "Achieving Mobile Cloud Computing through Heterogeneous Wireless Networks." International Journal of Communications, Network and System Sciences 10, no. 06 (2017): 107–28. http://dx.doi.org/10.4236/ijcns.2017.106006.

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Zhou, Liang, Honggang Wang, and Yi Qian. "Research advance in wireless networks and mobile computing." Telecommunication Systems 60, no. 1 (November 21, 2014): 1–2. http://dx.doi.org/10.1007/s11235-014-9916-1.

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BERENBRINK, PETRA, THOMAS FRIEDETZKY, JÁN MAŇUCH, and LADISLAV STACHO. "(QUASI) SPANNERS FOR MOBILE AD HOC NETWORKS." Journal of Interconnection Networks 06, no. 02 (June 2005): 63–84. http://dx.doi.org/10.1142/s0219265905001320.

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We introduce a notion of t-quasi-spanner as an alternative to classical t-spanners. Our motivation for quasi-spanner comes from a problem of computing a sparse backbone for ad hoc wireless networks with fixed transmission ranges. We study computational complexity of the problem of computing sparsest quasi-spanner. Then we concentrate on the case t = 2 and give a distributed algorithm for computing a 2-quasi-spanner with linear number of edges. Finally, we give a modification of our algorithm which performs well on a class of random ad hoc networks.

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Brooks, Tyson. "Authenticating Devices in Fog-mobile Edge Computing Environments through a Wireless Grid Resource Sharing Protocol." International Journal of UbiComp 13, no. 2 (April 30, 2022): 1–17. http://dx.doi.org/10.5121/iju.2022.13201.

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The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing and wireless grids has resulted in the widespread deployment of relatively immature technology. These technologies, which will primarily use 5G wireless communication networks, are becoming popular because they can be deployed quickly with little infrastructure and lends themselves to environments utilizing numerous internet connected devices (ICD). There are, however, many significant challenges faced by security designers, engineers and implementers of these networks in ensuring that the level of security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected by a robust security architecture due to these technologies being plagued with security problems. The authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new information system platforms. This article identifies an authentication process required for these ICDs, which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud network through a wireless grid authentication process. The purpose of this article is to begin to hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and mobile edge computing clouds to create this new IoT architecture. An authentication process developed from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors depending on their capability to handle five primary functions: management of identification [ID] and presence, permissions management, data transferability, application-programming interface [API] and security.

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Ceballos, Henry Zárate, and Jorge Eduardo Ortiz Triviño. "S.O.V.O.R.A.: A Distributed Wireless Operating System." Information 11, no. 12 (December 14, 2020): 581. http://dx.doi.org/10.3390/info11120581.

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Due to the growth of users and linked devices in networks, there is an emerging need for dynamic solutions to control and manage computing and network resources. This document proposes a Distributed Wireless Operative System on a Mobile Ad-hoc Network (MANET) to manage and control computing resources in relation to several virtual resources linked in a wireless network. This prototype has two elements: a local agent that works on each physical node to manage the computing resources (e.g., virtual resources and distributed applications) and an orchestrator agent that monitors, manages, and deploys policies on each physical node. These elements arrange the local and global computing resources to provide a quality service to the users of the Ad-hoc cluster. The proposed S.O.V.O.R.A. model (Operating Virtualized System oriented to Ad-hoc networks) defines primitives, commands, virtual structures, and modules to operate as a distributed wireless operating system.

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Durachman, Yusuf. "Analysis of Learning Techniques for Performance Prediction in Mobile Adhoc Networks." International Innovative Research Journal of Engineering and Technology 6, no. 2 (December 30, 2020): IS—46—IS—53. http://dx.doi.org/10.32595/iirjet.org/v6i2.2020.141.

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Current advancements in cellular technologies and computing have provided the basis for the unparalleled exponential development of mobile networking and software availability and quality combined with multiple systems or network software. Using wireless technologies and mobile ad-hoc networks, such systems and technology interact and collect information. To achieve the Quality of Service (QoS) criteria, the growing concern in wireless network performance and the availability of mobile users would support a significant rise in wireless applications. Predicting the mobility of wireless users and systems performs an important role in the effective strategic decision making of wireless network bandwidth service providers. Furthermore, related to the defect-proneness, self-organization, and mobility aspect of such networks, new architecture problems occur. This paper proposes to predict and simulate the mobility of specific nodes on a mobile ad-hoc network, gradient boosting devices defined for the system will help. The proposed model not just to outperform previous mobility prediction models using simulated and real-world mobility instances, but provides better predictive accuracy by an enormous margin. The accuracy obtained helps the suggested mobility indicator in Mobile Adhoc Networks to increase the average level of performance.

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Hsu, Ching-Hsien, and Emmanuel Udoh. "Mobile and Wireless Computing towards Sustainable and Ubiquitous Clouds Services." International Journal of Grid and High Performance Computing 5, no. 3 (July 2013): 1–5. http://dx.doi.org/10.4018/jghpc.2013070101.

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The ever-growing cloud computing and services provide dynamic intelligence and play an increasingly critical role in all aspects of our lives. By taking advantage of virtualized resources, cloud computing services presents an attractive means to address the challenges while realizing the potential of Mobile and Wireless Computing (MWC). The MWC paradigm can be generalized to include mobile devices, which not only incorporate sophisticated methods for users to interact with the online world through numerous applications in their devices, but are endowed with multiple sensors that enable them to contribute data as nodes in the IoT. In this context, mobile cloud services that enable widespread data collection through mobile devices and collaborative use of mobile devices to enhance existing and realize new applications are very much of interest. As such, the MWC has come to the picture seeking solutions for computing and IT infrastructures to be energy efficient and environmentally friendly. This special issue is in response to the increasing convergence between MWC and cloud services, while different approaches exist, challenges and opportunities are numerous in this context. The research papers selected for this special issue represent recent progresses in the field, including works on services computing and modeling, mobile cloud, U-Care cloud, vehicle networks, energy-aware architectures, and wireless sensor network technologies and applications. This special issue includes four extended version of the selected paper originally presented at the 17th Mobile Computing Workshop (MC 2012) and the 8th Workshop on Wireless, Ad Hoc and Sensor Networks (WASN 2012), held at Taipei, Taiwan; one extended version of the selected paper originally presented at the 4th IEEE International Conference on Cloud Computing Technology and Science (IEEE CloudCom 2012), held at Taipei, Taiwan; and one regular submission with 20% average acceptance rate for 2012 submissions in IJGHPC. The papers selected for this issue not only contribute valuable insights and results but also have particular relevance to the mobile, wireless and cloud computing community. All of them present high quality results for tackling problems arising from the ever-growing mobile and cloud services. We believe that this special issue provides novel ideas and state-of-the-art techniques in the field, and stimulates future research in the mobile and wireless services in clouds.

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Tomic, Slavisa, and Marko Beko. "Special Issue: Localization in Wireless Sensor Networks." Journal of Sensor and Actuator Networks 9, no. 1 (February 27, 2020): 14. http://dx.doi.org/10.3390/jsan9010014.

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Lei Lei, Zhangdui Zhong, Kan Zheng, Jiadi Chen, and Hanlin Meng. "Challenges on wireless heterogeneous networks for mobile cloud computing." IEEE Wireless Communications 20, no. 3 (June 2013): 34–44. http://dx.doi.org/10.1109/mwc.2013.6549281.

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Sheng, Zhengguo, Chinmaya Mahapatra, Victor C. M. Leung, Min Chen, and Pratap Kumar Sahu. "Energy Efficient Cooperative Computing in Mobile Wireless Sensor Networks." IEEE Transactions on Cloud Computing 6, no. 1 (January 1, 2018): 114–26. http://dx.doi.org/10.1109/tcc.2015.2458272.

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Hart, Jim, and Mike Hannan. "The future of mobile technology and mobile wireless computing." Campus-Wide Information Systems 21, no. 5 (December 2004): 201–4. http://dx.doi.org/10.1108/10650740410567554.

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Wu, Xintao, Jie Gan, Shiyong Chen, Xu Zhao, and Yucheng Wu. "Optimization Strategy of Task Offloading with Wireless and Computing Resource Management in Mobile Edge Computing." Wireless Communications and Mobile Computing 2021 (November 11, 2021): 1–11. http://dx.doi.org/10.1155/2021/8288836.

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Mobile edge computing (MEC) provides user equipment (UE) with computing capability through wireless networks to improve the quality of experience (QoE). The scenario with multiple base stations and multiple mobile users is modeled and analyzed. The optimization strategy of task offloading with wireless and computing resource management (TOWCRM) in mobile edge computing is considered. A resource allocation algorithm based on an improved graph coloring method is used to allocate wireless resource blocks (RBs). The optimal solution of computing resource is obtained by using KKT conditions. To improve the system utility, a semi-distributed TOWCRM strategy is proposed to obtain the task offloading decision. Theoretical simulations under different system parameters are executed, and the proposed semi-distributed TOWCRM strategy can be completed with finite iterations. Simulation results have verified the effectiveness of the proposed algorithm.

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Anandakrishnan, N., and Neena Roshini. "A STUDY ON GEOGRAPHICAL ROUTING WITH ADAPTIVE POSITION UPDATE." International Journal of Engineering Technologies and Management Research 5, no. 3 (February 13, 2020): 108–15. http://dx.doi.org/10.29121/ijetmr.v5.i3.2018.181.

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Geographical Routing is a routing methodology mainly used for wireless mobile networks (Mobile Adhoc Networks, MANETs). MANETs are comprised of mobile nodes or mobile computing devices which are free to move randomly and thus the network's wireless topology may also change randomly. In Geographical Routing, nodes need to maintain the current positions of their neighbors for making forwarding decisions and hence the Adaptive Position Update (APU) method is proposed. Based on the flexibility of the nodes and the forwarding decisions made in the network, APU dynamically keeps in track of the rate of position updates. It is based on nodes with movements which are complex to predict their updated positions frequently and also the nodes which are closer to forwarding paths and update their positions more frequently. The APU is validated by network simulations showing that APU can potentially reduce the traffic load and acknowledge the mobility of nodes. It also improves the routing performance in terms of packet delivery ratio and packet delays.

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Lai, Shiwei, Rui Zhao, Shunpu Tang, Junjuan Xia, Fasheng Zhou, and Liseng Fan. "Intelligent secure mobile edge computing for beyond 5G wireless networks." Physical Communication 45 (April 2021): 101283. http://dx.doi.org/10.1016/j.phycom.2021.101283.

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Gu, Yixiao, Yao Yao, Cheng Li, Bin Xia, Dingjie Xu, and Chaoxian Zhang. "Modeling and Analysis of Stochastic Mobile-Edge Computing Wireless Networks." IEEE Internet of Things Journal 8, no. 18 (September 15, 2021): 14051–65. http://dx.doi.org/10.1109/jiot.2021.3068382.

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Zhou, Fuhui, and Rose Qingyang Hu. "Computation Efficiency Maximization in Wireless-Powered Mobile Edge Computing Networks." IEEE Transactions on Wireless Communications 19, no. 5 (May 2020): 3170–84. http://dx.doi.org/10.1109/twc.2020.2970920.

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Rimal, Bhaskar Prasad, Dung Pham Van, and Martin Maier. "Cloudlet Enhanced Fiber-Wireless Access Networks for Mobile-Edge Computing." IEEE Transactions on Wireless Communications 16, no. 6 (June 2017): 3601–18. http://dx.doi.org/10.1109/twc.2017.2685578.

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Chen, Ying, Shuang Chen, and Xin Chen. "Efficient caching strategy in wireless networks with mobile edge computing." Peer-to-Peer Networking and Applications 13, no. 5 (February 29, 2020): 1756–66. http://dx.doi.org/10.1007/s12083-020-00874-w.

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Li, Xiaomin, and Jiafu Wan. "Proactive caching for edge computing-enabled industrial mobile wireless networks." Future Generation Computer Systems 89 (December 2018): 89–97. http://dx.doi.org/10.1016/j.future.2018.06.017.

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BUI, MARC, SAJAL K. DAS, AJOY K. DATTA, and DAI THO NGUYEN. "RANDOMIZED MOBILE AGENT BASED ROUTING IN WIRELESS NETWORKS." International Journal of Foundations of Computer Science 12, no. 03 (June 2001): 365–84. http://dx.doi.org/10.1142/s0129054101000539.

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We propose a novel approach for shortest path routing in wireless mobile networks. The approach makes use of n mobile agents initially launched from n mobile nodes forming the network. The agents move randomly from node to node and update routing information as they go. The approach is presented in this paper with two protocols. Both of them exhibit good performance in terms of the network and computing resource consumptions. The first protocol relies on independent mobile agents and imposes a minimum bandwidth requirement on individual mobile agents. Each agent carries the link state of its creator and this information remains unchanged except when the mobile agent returns to the home node. The second protocol is a refinement of the first protocol, with some form of interaction between the mobile agents. Each agent maintains the routing table of its creator instead of link state. The randomly walking agents spread the update information and compute the shortest paths via exchanging network state information between the routing tables they carry and the routing tables at the nodes they traverse. The correctness of the protocols is proven. Our analysis shows that the agent cooperation improves the system performance when dealing with topology and link cost changes.

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Intisar Mohsin Saadoon. "OLSR Protocol based on Fog Computing and SDN in VANet." Global Journal of Engineering and Technology Advances 10, no. 2 (February 28, 2022): 060–70. http://dx.doi.org/10.30574/gjeta.2022.10.2.0037.

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Wireless technology has been the subject of a lot of study in recent years. VANET is the fastest-growing area in wireless communications. The Vehicle Ad-Hoc Network (VANet) is a subtype of the Mobile Ad-Hoc Network (MANet) that is used to enhance road safety and passenger experience, giving a unique perspective on intelligent transportation systems. This wireless invention is supposed to improve road safety and efficiency as part of the Intelligent Transportation System. Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) techniques that enable IEEE 802.11p wireless access technologies deliver applications (secure/unsecure) while exchanging information to avert an accident and provide travelers with trustworthy information make up the VANET. As an end result of investments in independent cars, new network technology including SDN, side computing, and VANET studies are being introduced, causing VANET simulators to review their assist for those new capabilities. In this paper, we offer an SDN-compliant solution for managing wireless fog networks by combining open Flow and IP transfer protocols in a way that provides a flexible and configurable wireless data plane for fog networks in addition intelligent traffic engineering for network offloading. The proposal includes an efficiency rating for connections with decreased latency, flexible load balancing to select the quickest way, and lower network cost.

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Kim, Dong Ha, Cheolhoon Kim, Yumi Oh, Sungwon Lee, and Seung Gwan Lee. "Very High Data Rate Support for Mobile Cloud Services Using SDN-Based Heterogeneous Carrier Aggregation." International Journal of Software Engineering and Knowledge Engineering 24, no. 07 (September 2014): 983–1011. http://dx.doi.org/10.1142/s021819401440004x.

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Mobile traffic is currently the most important traffic on the Internet, both domestically and internationally. This is predominantly attributable to widespread cloud computing-based services on mobile networks. Fifth generation (5G) mobile networks are expected to comfortably accommodate this type of traffic by supporting 1,000 times faster speeds than conventional 4G. However, commercial implementation of 5G mobile is targeted for the year 2020. Therefore, interim accommodation approaches are needed. In essence, 5G mobile networks are an evolution of 4G in which a licensed spectrum that generates revenue from user data transfer is being considered. Consequently, more cost-effective methods that utilize the unlicensed spectrum are also desired. Meanwhile, concomitant with pursuit of miniaturization and reduction in weight, the number and types of network interfaces in recent mobile devices are increasing. We propose a method for carrier aggregation of multiple heterogeneous wireless links based on software-defined networking (SDN) that controls traffic and manages the wireless interfaces of mobile devices effectively when multiple radio access technologies are available. Evaluations conducted of the proposed method on an experimental testbed developed using the OpenStack cloud computing platform with aggregated multiple radio access technology environments indicate that it is feasible and provides higher data rate.

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Zhang, Jianshan, Ming Li, Xianghan Zheng, and Ching-Hsien Hsu. "A Time-Driven Cloudlet Placement Strategy for Workflow Applications in Wireless Metropolitan Area Networks." Sensors 22, no. 9 (April 29, 2022): 3422. http://dx.doi.org/10.3390/s22093422.

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With the rapid development of mobile technology, mobile applications have increasing requirements for computational resources, and mobile devices can no longer meet these requirements. Mobile edge computing (MEC) has emerged in this context and has brought innovation into the working mode of traditional cloud computing. By provisioning edge server placement, the computing power of the cloud center is distributed to the edge of the network. The abundant computational resources of edge servers compensate for the lack of mobile devices and shorten the communication delay between servers and users. Constituting a specific form of edge servers, cloudlets have been widely studied within academia and industry in recent years. However, existing studies have mainly focused on computation offloading for general computing tasks under fixed cloudlet placement positions. They ignored the impact on computation offloading results from cloudlet placement positions and data dependencies among mobile application components. In this paper, we study the cloudlet placement problem based on workflow applications (WAs) in wireless metropolitan area networks (WMANs). We devise a cloudlet placement strategy based on a particle swarm optimization algorithm using genetic algorithm operators with the encoding library updating mode (PGEL), which enables the cloudlet to be placed in appropriate positions. The simulation results show that the proposed strategy can obtain a near-optimal cloudlet placement scheme. Compared with other classic algorithms, this algorithm can reduce the execution time of WAs by 15.04–44.99%.

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Piramu Preethika, SK, and R. Gobinath. "A survey of mobile cloud computing offloading concepts based on measurements and algorithms." International Journal of Engineering & Technology 7, no. 2.26 (May 7, 2018): 13. http://dx.doi.org/10.14419/ijet.v7i2.26.12525.

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Handheld computing devices at the moment everywhere in the arms of generation dependent human beings of every age. Clients are looking for new innovative thoughts to first and best utilization of Smart Mobile Devices. The rapid enlargement of the number of clever telephone users has given rise of various research subjects. While the technological advancements are happening from hardware and package levels, novel ideas are being introduced. One amongst those ideas is Mobile Cloud computing which is the mix of cloud computing, mobile compu-ting and wireless networks to bring wealthy process resources to mobile users, network operators, yet as cloud computing suppliers. MCC offloading is a technique to overcome the barriers like battery life, memory usage, computation difficulties faced in Mobile computing with the help of cloud. This survey not only focuses on the concepts of offloading, it also concentrates on the measurements and basic ideas of Mobile Cloud computing related algorithms.

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Chirivella-Perez, Enrique, Juan Gutiérrez-Aguado, Jose M. Alcaraz-Calero, and Qi Wang. "NFVMon: Enabling Multioperator Flow Monitoring in 5G Mobile Edge Computing." Wireless Communications and Mobile Computing 2018 (August 14, 2018): 1–16. http://dx.doi.org/10.1155/2018/2860452.

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With the advances of new-generation wireless and mobile communication systems such as the fifth-generation (5G) mobile networks and Internet of Things (IoT) networks, demanding applications such as Ultra-High-Definition video applications is becoming ever popular. These applications require real-time monitoring and processing to meet the mission-critical quality of service requirements and are expected to be supported by the emerging fog or edge computing paradigms. This paper presents NFVMon, a novel monitoring architecture to enable flow monitoring capabilities of network traffic in a 5G multioperator mobile edge computing environment. The proposed NFVMon is integrated with the management plane of the Cloud Computing. NFVMon has been prototyped and a reference implementation is presented. It provides novel capabilities to provide disaggregated metrics related to the different 5G mobile operators sharing infrastructures and also about the different 5G subscribers of each of such mobile operators. Extensive experiments for evaluating the performance of the system have been conducted on a mid-sized infrastructure testbed.

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Al-Razgan, Muna, and Taha Alfakih. "Wireless Sensor Network Architecture Based on Mobile Edge Computing." Security and Communication Networks 2022 (April 1, 2022): 1–16. http://dx.doi.org/10.1155/2022/9073220.

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Wireless sensor networks (WSN) are infrastructure-less and fully distributed systems of self-configurable and self-organized nodes that wish to share the IoT devices’ data over the air. WSN consists of heterogeneous/homogeneous sensors dispersed in a particular area to monitor phenomena, such as volcanoes, pressure, sound, temperature, and pollution, then transfer their data to a central location for analysis and decision-making. The deployment of WSNs is often used in difficult places, such as disaster areas, battlefields, conflict zones, and volcanic zones, which require efficient data collection. However, WSNs face many challenges, such as latency, multitasks, and data quality. This paper proposes an efficient solution for multiple data collection tasks exploiting mobile edge computing (MEC) technique-enabled WSN in war field and disaster areas. Firstly, we integrate WSN and MEC to produce a novel data collection framework (WSN). Secondly, we modelled the data collection process, including multiple sensors and tasks. Thirdly, determine the best way to deploy sensors in the targeted area (e.g., military areas, isolated areas, and areas infested with terrorists) to cover the whole destination area, based on set values for data quality. Finally, find an appropriate technique for routing by choosing the routing protocol to improve their capabilities performance and decrease the energy consumption to increase the life of the WSN. Furthermore, the security of WSN is one of the key parameters, especially in the routing protocol, since it is critical to ensure the security of transmitted data and how it is transmitted securely to mitigate the attacks. The framework which works as a simulation tool shows a good result and has been proven the efficient interaction between the MEC and WSN. We compare the results with traditional methods, which proved to outperform them.

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Dahane, Amine, Nasr-Eddine Berrached, and Abdelhamid Loukil. "Safety of Mobile Wireless Sensor Networks Based on Clustering Algorithm." International Journal of Wireless Networks and Broadband Technologies 5, no. 1 (January 2016): 73–102. http://dx.doi.org/10.4018/ijwnbt.2016010105.

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Clustering approaches for mobile wireless sensor networks (WSNs) tend to extend the battery life of the individual sensors and the network lifetime. Taking into account the mobility of the network, a powerful mechanism to safely elect a cluster head is a challenging task in many research works. As a proposed technique to deal with such problem, the approach based on the computing of the weight of each node in the network is chosen. This paper is intended to propose a new algorithm called “S-WCA” for safety of mobile sensor networks based on clustering algorithm using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, a summary of the highlight of the authors' work is provided in a comprehensive strategy for monitoring the network, so as to detect and remove the malicious nodes. Simulation study is used to demonstrate the performance of the proposed algorithm.

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Wang, Tao, and William N. N. Hung. "Reliable Node Clustering for Mobile Ad Hoc Networks." Journal of Applied Mathematics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/285967.

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Mobile ad hoc networks (MANETs) are gaining popularity in recent years due to their flexibility, the proliferation of smart computing devices, and developments in wireless communications. Due to the mobile nature of the network, creating reliable clusters that can sustain for long period of time is a challenging problem. In this paper, we use probabilistic analysis to guide our clustering algorithm towards more reliable clusters. We also use scatter search to perform clustering while considering various performance metrics. Experiment results show that our clustering approach produces more reliable clusters than prior approaches.

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Kaleem, Faisal, Abolfazl Mehbodniya, Kang K. Yen, and Fumiyuki Adachi. "A Fuzzy Preprocessing Module for Optimizing the Access Network Selection in Wireless Networks." Advances in Fuzzy Systems 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/232198.

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A heterogeneous wireless network is characterized by the presence of different wireless access technologies that coexist in an overlay fashion. These wireless access technologies usually differ in terms of their operating parameters. On the other hand, Mobile Stations (MSs) in a heterogeneous wireless network are equipped with multiple interfaces to access different types of services from these wireless access technologies. The ultimate goal of these heterogeneous wireless networks is to provide global connectivity with efficient ubiquitous computing to these MSs based on the Always Best Connected (ABC) principle. This is where the need for intelligent and efficient Vertical Handoffs (VHOs) between wireless technologies in a heterogeneous environment becomes apparent. This paper presents the design and implementation of a fuzzy multicriteria based Vertical Handoff Necessity Estimation (VHONE) scheme that determines the proper time for VHO, while considering the continuity and quality of the currently utilized service, and the end-users' satisfaction.

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Dong, Xiaogang, Zheng Wan, Changshou Deng, Wenying Wen, and Yuxuan Luo. "Intelligent Time Allocation for Wireless Power Transfer in Wireless-Powered Mobile Edge Computing." Wireless Communications and Mobile Computing 2022 (August 24, 2022): 1–13. http://dx.doi.org/10.1155/2022/6722848.

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Wireless-powered mobile edge computing is a new network computing paradigm that combines with the advantages of wireless power transfer and mobile edge computing. When the harvest-then-offload protocol is adopted in this network, the time of wireless power transfer has a significant impact on system performance. If the time is too short, the user cannot harvest enough energy. If it is too long, the user will not have enough time to complete the task offloading. Both result in many of user tasks being discarded. To address this problem, DEWPT, a differential evolution-based optimization scheme for wireless power transfer time, is proposed in this paper. DEWPT is designed with a hybrid mutation operator and a perturbation-based binomial crossover operator. The hybrid mutation operator combines the benefits of two mutation operators with distinct characteristics, so that DEWPT not only has a strong exploration ability but also can quickly converge. Meanwhile, the perturbation-based binomial crossover operator improves DEWPT’s ability to exploit local space. These two improvements effectively enhance DEWPT’s optimization performance, which is beneficial to find the optimal time for wireless power transfer. Furthermore, to improve the optimization efficiency, micro-population is introduced into DEWPT. Finally, the computation completion ratio maximization model is used to validate the performance of DEWPT in the wireless-powered mobile edge computing network with multiple edge servers. Numerical results show that the computation offloading scheme integrating with DEWPT can achieve a higher computation completion rate than three benchmark schemes, and is competitive in complexity. This demonstrates that DEWPT is an effective time allocation scheme for wireless power transfer.

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Kumar, Sunil, Kashyap Kambhatla, Fei Hu, Mark Lifson, and Yang Xiao. "Ubiquitous Computing for Remote Cardiac Patient Monitoring: A Survey." International Journal of Telemedicine and Applications 2008 (2008): 1–19. http://dx.doi.org/10.1155/2008/459185.

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New wireless technologies, such as wireless LAN and sensor networks, for telecardiology purposes give new possibilities for monitoring vital parameters with wearable biomedical sensors, and give patients the freedom to be mobile and still be under continuous monitoring and thereby better quality of patient care. This paper will detail the architecture and quality-of-service (QoS) characteristics in integrated wireless telecardiology platforms. It will also discuss the current promising hardware/software platforms for wireless cardiac monitoring. The design methodology and challenges are provided for realistic implementation.

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Wu, Huaming, Zhu Han, Katinka Wolter, Yubin Zhao, and Haneul Ko. "Deep Learning Driven Wireless Communications and Mobile Computing." Wireless Communications and Mobile Computing 2019 (April 28, 2019): 1–2. http://dx.doi.org/10.1155/2019/4578685.

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Al-Turkistany, Mohammad, Abdelsalam (Sumi) Helal, and Mark Schmalz. "Adaptive wireless thin-client model for mobile computing." Wireless Communications and Mobile Computing 9, no. 1 (January 2009): 47–59. http://dx.doi.org/10.1002/wcm.603.

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Bagchi, Susmit, Hafizur Rahaman, and Purnendu Das. "MDVM System Concept, Paging Latency and Round-2 Randomized Leader Election Algorithm in SG." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 5 (September 20, 2006): 752–60. http://dx.doi.org/10.20965/jaciii.2006.p0752.

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The future trend in the computing paradigm is marked by mobile computing based on mobile-client/server architecture connected by wireless communication network. However, the mobile computing systems have limitations because of the resource-thin mobile clients operating on battery power. The MDVM system allows the mobile clients to utilize memory and CPU resources of Server-Groups (SG) to overcome the resource limitations of clients in order to support the high-end mobile applications such as, m-commerce and virtual organization (VO). In this paper the concept of MDVM system and the architecture of cellular network containing the SG are discussed. A round-2 randomized distributed algorithm is proposed to elect a unique leader and co-leader of the SG. The algorithm is free from any assumption about network topology, buffer space limitations and is based on dynamically elected coordinators eliminating single point of failure. The algorithm is implemented in distributed system setup and the network-paging latency values of wired and wireless networks are measured experimentally. The experimental results demonstrate that in most cases the algorithm successfully terminates in first round and the possibility of second round execution decreases significantly with the increase in the size of SG (|<I>Na</I>|). The overall message complexity of the algorithm is O(|<I>Na</I>|). The comparative study of network-paging latencies indicates that 3G/4G mobile communication systems would support the realization of MDVM system.

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Cai, Yegui, F. Yu, and Shengrong Bu. "Cloud computing meets mobile wireless communications in next generation cellular networks." IEEE Network 28, no. 6 (November 2014): 54–59. http://dx.doi.org/10.1109/mnet.2014.6963805.

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Ko, Seung-Woo, Kaifeng Han, and Kaibin Huang. "Wireless Networks for Mobile Edge Computing: Spatial Modeling and Latency Analysis." IEEE Transactions on Wireless Communications 17, no. 8 (August 2018): 5225–40. http://dx.doi.org/10.1109/twc.2018.2840120.

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Yu, Guanding, Jun Zhang, Victor C. M. Leung, Marios Kountouris, and Chonggang Wang. "IEEE Access Special Section Editorial: Mobile Edge Computing for Wireless Networks." IEEE Access 6 (2018): 11439–42. http://dx.doi.org/10.1109/access.2018.2806239.

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Spyrou, Constantinos, George Samaras, Evaggelia Pitoura, and Paraskevas Evripidou. "Mobile Agents for Wireless Computing: The Convergence of Wireless Computational Models with Mobile-Agent Technologies." Mobile Networks and Applications 9, no. 5 (October 2004): 517–28. http://dx.doi.org/10.1023/b:mone.0000034705.10830.b7.

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Zhao, Nan, Fan Ren, Wei Du, and Zhiyang Ye. "Deep Reinforcement Learning for Task Offloading and Power Allocation in UAV-Assisted MEC System." International Journal of Mobile Computing and Multimedia Communications 12, no. 4 (October 2021): 1–20. http://dx.doi.org/10.4018/ijmcmc.289163.

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Mobile edge computing (MEC) can provide computing services for mobile users (MUs) by offloading computing tasks to edge clouds through wireless access networks. Unmanned aerial vehicles (UAVs) are deployed as supplementary edge clouds to provide effective MEC services for MUs with poor wireless communication condition. In this paper, a joint task offloading and power allocation (TOPA) optimization problem is investigated in UAV-assisted MEC system. Since the joint TOPA problem has a strong non-convex characteristic, a method based on deep reinforcement learning is proposed. Specifically, the joint TOPA problem is modeled as Markov decision process. Then, considering the large state space and continuous action space, a twin delayed deep deterministic policy gradient algorithm is proposed. Simulation results show that the proposed scheme has lower smoothing training cost than other optimization methods.

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Khasawneh, Ahmad M. Al. "Mobile computing in Jordan: a roadmap to wireless." International Journal of Information Technology and Management 9, no. 3 (2010): 260. http://dx.doi.org/10.1504/ijitm.2010.030943.

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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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Lin, Qiang. "Dynamic Resource Allocation Strategy in Mobile Edge Cloud Computing Environment." Mobile Information Systems 2021 (August 7, 2021): 1–10. http://dx.doi.org/10.1155/2021/8381998.

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With the development of the mobile Internet, smart mobile terminals have become an indispensable tool for people's lives and mobile applications are becoming more and more powerful. This research mainly discusses the dynamic resource allocation strategy of the mobile edge cloud computing environment. The physical resource layer in the network model is responsible for providing specific resources that are actually available, such as hardware resources, computing resources, storage resources, mainly including base stations, mobile edge computing servers, spectrum, power, and other communications of different infrastructure vendor basic components of the system. The functions of the virtual machine monitor include resource virtualization and resource management. As an important component of wireless network virtualization, virtual machine monitors are usually deployed in physical base stations to provide physical resources and to consider the connection between the virtual machine stations. The business of the business cache model is an application that is requested by users running on the mobile edge computing server or cloud at the base station. The computing task scheduling in the mobile edge environment can be classified as a wireless interaction model. This model captures the user throughput in cellular network interaction. The physical layer channel access strategy (CDMA) allows all mobile users to efficiently share the same spectrum resources at the same time. When the preference coefficient for task energy consumption varies between 0.35–0.55 and 0.65–1, the superior range of maximum system efficiency achieved by RAOM accounts for 55% of the entire range. This research contributes to the reasonable allocation of resources, and the mobile edge computing model improves the fairness of users with a lower transmission cost.

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El-Sofany, Hosam, and Samir Abou El-Seoud. "A Novel Model for Securing Mobile-based Systems against DDoS Attacks in Cloud Computing Environment." International Journal of Interactive Mobile Technologies (iJIM) 13, no. 01 (January 29, 2019): 85. http://dx.doi.org/10.3991/ijim.v13i01.9900.

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the increasing growth of mobile devices technology and Mobile-based systems with the emerging of cloud computing technology, created a Mobile Cloud Computing field to be the recent future technology for different wireless services. The development of Mobile-based system under cloud computing environment solve some performance and environment related issues include: bandwidth, storage capacity, availability, scalability and heterogeneity. The Mobile-based cloud computing apps are different comparing to mobile computing apps, since in the first model the devices run cloud based web applications not as mobile computing native apps. Services of Mobile-based systems via cloud are accessing and sharing through internet connection thus they are open for attacker to attack on its security. Distributed Denial of Service (DDoS) attacks can cause a big problem in mobile cloud computing security. The main objective of DDoS attacks is to infect wireless devises resources (e.g., software applications, wireless network, etc.) and make them unavailable to the authorized user. In DDoS, the attacker tries to overload the Mobile-based service with traffic. The main objective of this research paper is to introduce novel model for securing Mobile-based systems against DDoS attacks. Efficiency and performance analysis evaluations of the proposed model are presented. The feedbacks of the experimental results were highly promising, for protecting mobile-based cloud computing systems against DDoS attacks.

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Boukerche, Azzedine. "Wireless and mobile ad hoc networking and computing." Journal of Parallel and Distributed Computing 63, no. 1 (January 2003): 1–2. http://dx.doi.org/10.1016/s0743-7315(02)00027-8.

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Journal articles on the topic 'Mobile wireless computing networks'

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