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1
Akinwande, Olumide. "Interest Forwarding in Named Data Networking Using Reinforcement Learning." Sensors 18, no. 10 (October 8, 2018): 3354. http://dx.doi.org/10.3390/s18103354.
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In-network caching is one of the key features of information-centric networks (ICN), where forwarding entities in a network are equipped with memory with which they can temporarily store contents and satisfy en route requests. Exploiting in-network caching, therefore, presents the challenge of efficiently coordinating the forwarding of requests with the volatile cache states at the routers. In this paper, we address information-centric networks and consider in-network caching specifically for Named Data Networking (NDN) architectures. Our proposal departs from the forwarding algorithms which primarily use links that have been selected by the routing protocol for probing and forwarding. We propose a novel adaptive forwarding strategy using reinforcement learning with the random neural network (NDNFS-RLRNN), which leverages the routing information and actively seeks new delivery paths in a controlled way. Our simulations show that NDNFS-RLRNN achieves better delivery performance than a strategy that uses fixed paths from the routing layer and a more efficient performance than a strategy that retrieves contents from the nearest caches by flooding requests.
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Bazmi, Parisa, and Manijeh Keshtgary. "A NEURAL NETWORK BASED TRAFFIC-AWARE FORWARDING STRATEGY IN NAMED DATA NETWORKING." IIUM Engineering Journal 17, no. 2 (November 30, 2016): 59–69. http://dx.doi.org/10.31436/iiumej.v17i2.617.
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Named Data Networking (NDN) is a new Internet architecture which has been proposed to eliminate TCP/IP Internet architecture restrictions. This architecture is abstracting away the notion of host and working based on naming datagrams. However, one of the major challenges of NDN is supporting QoS-aware forwarding strategy so as to forward Interest packets intelligently over multiple paths based on the current network condition. In this paper, Neural Network (NN) Based Traffic-aware Forwarding strategy (NNTF) is introduced in order to determine an optimal path for Interest forwarding. NN is embedded in NDN routers to select next hop dynamically based on the path overload probability achieved from the NN. This solution is characterized by load balancing and QoS-awareness via monitoring the available path and forwarding data on the traffic-aware shortest path. The performance of NNTF is evaluated using ndnSIM which shows the efficiency of this scheme in terms of network QoS improvementof17.5% and 72% reduction in network delay and packet drop respectively.
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Pu, Cong. "Pro NDN : MCDM-Based Interest Forwarding and Cooperative Data Caching for Named Data Networking." Journal of Computer Networks and Communications 2021 (March 18, 2021): 1–16. http://dx.doi.org/10.1155/2021/6640511.
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Named data networking (NDN), as a specific architecture design of information-centric networking (ICN), has quickly became a promising candidate for future Internet architecture, where communications are driven by data names instead of IP addresses. To realize the NDN communication paradigm in the future Internet, two important features, stateful forwarding and in-network caching, have been proposed to cope with drawbacks of host-based communication protocols. The stateful forwarding is designed to maintain the state of pending Interest packets to guide Data packets back to requesting consumers, while the in-network caching is used to reduce both network traffic and data access delay to improve the overall performance of data access. However, the conventional stateful forwarding approach is not adaptive and responsive to diverse network conditions because it fails to consider multiple network metrics to make Interest forwarding decision. In addition, the default in-network caching strategy relies on storing each received Data packet regardless of various caching constraints and criteria, which causes the routers in the vicinity of data producers to suffer from excessive caching overhead. In this paper, we propose the Pro NDN , a novel stateful forwarding and in-network caching strategy for NDN networks. The Pro NDN consists of multicriteria decision-making (MCDM) based interest forwarding and cooperative data caching. The basic idea of the MCDM-based interest forwarding is to employ Technique for Order Performance by Similarity to Idea Solution (TOPSIS) to dynamically evaluate outgoing interface alternatives based on multiple network metrics and objectively select an optimal outgoing interface to forward the Interest packet. In addition, the cooperative data caching consists of two schemes: CacheData, which caches the data, and CacheFace, which caches the outgoing interface. We conduct extensive simulation experiments for performance evaluation and comparison with prior schemes. The simulation results show that the Pro NDN can improve Interest satisfaction ratio and Interest satisfaction latency as well as reduce hop count and Content Store utilization ratio.
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Akther, Nazma, Kingshuk Dhar, Shahid Md Asif Iqbal, Mohammed Nurul Huda, and Asaduzzaman. "Interest forwarding strategy in Named Data Networks (NDN) using Thompson Sampling." Journal of Network and Computer Applications 205 (September 2022): 103458. http://dx.doi.org/10.1016/j.jnca.2022.103458.
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din, Muhammad Salah ud, Muhammad Atif Ur Rehman, and Byung-Seo Kim. "CIDF-WSN: A Collaborative Interest and Data Forwarding Strategy for Named Data Wireless Sensor Networks." Sensors 21, no. 15 (July 30, 2021): 5174. http://dx.doi.org/10.3390/s21155174.
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Recent years have witnessed the huge popularity of Information-Centric Networking (ICN) and its realization as Named Data Networking (NDN) in the context of wireless sensor networks (WSNs). The participating nodes in WSNs are usually equipped with a single radio interface. The existing solutions lack in providing the efficient next forwarder selection in NDN-based single radio WSNs. In this work, we propose a collaborative Interest and Data Forwarding (CIDF-WSN) Strategy for Named Data Wireless Sensor Networks. CIDF-WSN develop a Neighbor Information Base (NFIB) which enables the node to select the optimal next-hop relay in Interest packet forwarding. An efficient Interest packet processing mechanism assisted by the Interest Cache Table (ICT) is provided to avoid Interest packets loss and frequent re-transmissions. In addition, CIDF-WSN also provides a robust Data packet transfer mechanism accompanied by the Temp Cache Table (TCT) to avoid Data packet losses and to ensure well-timed content delivery. Simulation results reveal that CIDF-WSN outperforms the recently published works in terms of Interest satisfaction rate, total energy consumption, Data retrieval delays, and communication overhead.
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de Sousa, Antonio M., Francisco R. C. Araujo, and Leobino N. Sampaio. "A Link-Stability-Based Interest-Forwarding Strategy For Vehicular Named Data Networks." IEEE Internet Computing 22, no. 3 (May 2018): 16–26. http://dx.doi.org/10.1109/mic.2018.032501512.
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Guo, Xian, Baobao Wang, Yongbo Jiang, Di Zhang, and Laicheng Cao. "Homomorphic encryption based privacy-aware intelligent forwarding mechanism for NDN-VANET." Computer Science and Information Systems, no. 00 (2022): 51. http://dx.doi.org/10.2298/csis220210051g.
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Machine learning has been widely used for intelligent forwarding strategy in Vehicular Ad-Hoc Networks (VANET). However, machine learning has serious security and privacy issues. BRFD is a smart Receiver Forwarding Decision solution based on Bayesian theory for Named Data Vehicular Ad-Hoc Networks (NDN-VANET). In BRFD, every vehicle that received an interest packet is required to make a forwarding decision according to the collected network status information. And then decides whether it will forward the received interest packet or not. Therefore, the privacy information of a vehicle can be revealed to other vehicles during information exchange of the network status. In this paper, a Privacy-Aware intelligent forwarding solution PABRFD is proposed by integrating Homomorphic Encryption (HE) into the improved BRFD. In PABRFD, a secure Bayesian classifier is used to resolve the security and privacy issues of information exchanged among vehicle nodes. We informally prove that this new scheme can satisfy security requirements and we implement our solution based on HE standard libraries CKKS and BFV. The experimental results show that PABRFD can satisfy our expected performance requirements.
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Bellaj, Mohammed, Najib Naja, and Abdellah Jamali. "Distributed Mobility Management Support for Low-Latency Data Delivery in Named Data Networking for UAVs." Future Internet 16, no. 2 (February 10, 2024): 57. http://dx.doi.org/10.3390/fi16020057.
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Named Data Networking (NDN) has emerged as a promising architecture to overcome the limitations of the conventional Internet Protocol (IP) architecture, particularly in terms of mobility, security, and data availability. However, despite the advantages it offers, producer mobility management remains a significant challenge for NDN, especially for moving vehicles and emerging technologies such as Unmanned Aerial Vehicles (UAVs), known for their high-speed and unpredictable movements, which makes it difficult for NDN to maintain seamless communication. To solve this mobility problem, we propose a Distributed Mobility Management Scheme (DMMS) to support UAV mobility and ensure low-latency content delivery in NDN architecture. DMMS utilizes decentralized Anchors to forward proactively the consumer’s Interest packets toward the producer’s predicted location when handoff occurs. Moreover, it introduces a new forwarding approach that combines the standard and location-based forwarding strategy to improve forwarding efficiency under producer mobility without changing the network structure. Using a realistic scenario, DMMS is evaluated and compared against two well-known solutions, namely MAP-ME and Kite, using the ndnSIM simulations. We demonstrate that DMMS achieves better results compared to Kite and MAP-ME solutions in terms of network cost and consumer quality-of-service metrics.
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Wang, Fei, YongJun Xu, Lin Wu, Longyijia Li, Dan Liu, and Liehuang Zhu. "A PEFKS- and CP-ABE-Based Distributed Security Scheme in Interest-Centric Opportunistic Networks." International Journal of Distributed Sensor Networks 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/469076.
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Security is a crucial issue in distributed applications of multihop wireless opportunistic network due to the features of exposed on the fly communication, relaxed end-to-end connectivity, and vague destinations literately. In this paper, we focus on problems of user privacy leakage and end-to-end confidentiality invasion in content-based or interest-centric wireless opportunistic network. And we propose a public-encryption-with-fuzzy-keyword-search- (PEFKS-) and ciphertext-policy-attribute-based-encryption- (CP-ABE-) based distributed security scheme by refining and compromising two-pairing-based encryption, searchable encryption, and attribute-based encryption. Our scheme enables opportunistic forwarding according to fuzzy interests preserving full privacy of users and ensures end-to-end confidentiality with a fine-grained access control strategy in an interest-centric scenario of large-scale wireless opportunistic networks. Finally, we analyze and evaluate the scheme in terms of security and performance.
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Buvanesvari, Ramachandira, and Kanagaraj Joseph. "An Efficient Secured PIT Management and Attack Detection Strategy Enhanced by CSOA-DCNN Algorithm in a Named Data Networking (NDN)." International Journal of Intelligent Engineering and Systems 14, no. 1 (February 28, 2021): 103–12. http://dx.doi.org/10.22266/ijies2021.0228.11.
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Named Data Networking (NDN) is a developing Internet design that utilizes a new network communication model dependent on the identity of Internet content. Its core component, the Pending Interest Table (PIT) serves an important role of recording Interest packet information. In managing PIT, the issue of flow PIT measuring has been very challenging because of the huge use of long Interest lifetime especially when there is no adaptable replacement strategy, subsequently affecting PIT performance. Named Data Networking (NDN) might experience some emerging threats such as Interest Flooding Attacks (IFA). In this paper, we focus on the IFA that can seriously devour the memory resource for the Pending Interest Table (PIT) of each included NDN router by flooding a huge amount of malicious Interests with spoofed names. To extricate the pressure of PIT attacked by IFA, we propose a methodology of efficient Secured PIT management and attack detection strategy by using a cuckoo search optimization algorithmDeep convolutional neural network (CSOA-DCNN) algorithm in Named Data Network. The CSO algorithm initially utilizes a learning technique and afterward considers improved search operators and deep convolutional neural network architecture (DCNN) for classification. The network simulation tool is utilized to design and calculate PIT management. The results of the study on a 20 Gbps gateway trace shows that the corresponding PIT contains 1.5 M entries, and the lookup, insert and delete frequencies are 1.4 M/s, 0.9 M/s and 0.9 M/s. The contribution of this study is significant for Interest packet management in NDN routing and forwarding systems.
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Ryu, Sanguk, Inwhee Joe, and WonTae Kim. "Intelligent Forwarding Strategy for Congestion Control Using Q-Learning and LSTM in Named Data Networking." Mobile Information Systems 2021 (March 31, 2021): 1–10. http://dx.doi.org/10.1155/2021/5595260.
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Named data networking (NDN) is a future network architecture that replaces IP-oriented communication with content-oriented communication and has new features such as cache, multiple paths, and multiple sources. Services such as video streaming, to which NDN can be applied in the future, can cause congestion if data is concentrated on one of the nodes during high demand. To solve this problem, sending rate control methods such as TCP congestion control have been proposed, but they do not adequately reflect the characteristics of NDN. Therefore, we use reinforcement learning and deep learning to propose a congestion control method that takes advantage of multipath features. The intelligent forwarding strategy for congestion control using Q-learning and long short-term memory in NDN proposed in this paper is divided into two phases. The first phase uses an LSTM model to train a pending interest table (PIT) entry rate that can be used as an indicator to detect congestion by knowing the amount of data returned. In the second phase, it is forwarded to an alternative path that is not congestive via Q-learning based on the PIT entry rate predicted by the trained LSTM model. The simulation results show that the proposed method increases the data reception rate by 6.5% and 19.5% and decreases the packet drop rate by 7.3% and 17.2% compared to an adaptive SRTT-based forwarding strategy (ASF) and BestRoute.
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Mansour, Dima, Haidar Osman, and Christian Tschudin. "Load Balancing in the Presence of Services in Named-Data Networking." Journal of Network and Systems Management 28, no. 2 (December 21, 2019): 298–339. http://dx.doi.org/10.1007/s10922-019-09507-x.
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AbstractLoad balancing is a mechanism to distribute client requests among several service instances. It enables resource utilization, lowers response time, and increases user satisfaction. In Named-Data Networking (NDN) and NDN-like architectures, load balancing becomes crucial when dynamic services are present, where relying solely on forwarding strategies can overload certain service instances while others are underutilized especially with the limited benefit of on-path caching when it comes to services. To understand the challenges and opportunities of load balancing in NDN, we analyze conventional load balancing in IP networks, and three closely related fields in NDN: congestion control, forwarding strategies, and data center management. We identify three possible scenarios for load balancing in NDN: facade load balancer, controller for Interest queues, and router-based load balancing. These different solutions use different metrics to identify the load on replicas, have different compliance levels with NDN, and place the load balancing functionality in different network components. From our findings, we propose and implement a new lightweight router-based load balancing approach called the communicating vessels and experimentally show how it reduces service response time and senses server capabilities without probing.
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Sahnoun, Abdelkabir, Ahmed Habbani, and Jamal El Abbadi. "An Energy-Efficient Proactive Routing Scheme for MANET: Game Theoretical Approach of Forwarding with Selfish Nodes." International Journal of Electronics and Telecommunications 63, no. 4 (November 27, 2017): 399–404. http://dx.doi.org/10.1515/eletel-2017-0055.
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Abstract In Mobile Ad-hoc Networks, nodes exchange packets with each other using intermediate nodes as relays. Since nodes in MANETs are battery powered, energy conservation is a crucial issue. Accepting relay all request may not be in the best interest of a node. But if many nodes prefer not to consume energy in relaying packets on behalf of others, the overall performance of routing in network will be influenced. In this paper we address the energy-efficient routing problem in MANETs with selfish nodes. We modeled this problem as a game-theoretic constraint optimization; we defined the utility of each node as a weighted difference between a performance metric and some transmission costs. A motivate mechanism is proposed in order to induce nodes to forwarding cooperation. Each node independently implements the optimal equilibrium strategy under the given constraints. Simulation results by NS3 simulator show that our proposed approach can improve system performance in network lifetime and packet delivery ratio.
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Ayaz, Muhammad, Jawaid Iqbal, Muhammad Adnan, Saddam S. Hussain, Amerah Alabrah, Noor Ul Amin, Suheer Al-Hadhrami, and Sk Md Mizanur Rahman. "A Content Dissemination Technique Based on Priority to Improve Quality of Service of Vehicular Ad Hoc Networks." Journal of Advanced Transportation 2022 (April 12, 2022): 1–16. http://dx.doi.org/10.1155/2022/6903450.
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Due to the ability of Vehicular Ad Hoc Networks (VANETs) to improve mobility and create innovative services, they have received increasing attention from both industry and academia fields. Named Data Networking (NDN) is a network service that has been developed for Internet’s host-based packet delivery model. In VANETs, NDN is used as an emerging architecture for improving the quality of service (QoS) of the networks connected cloud and mobile Internet of Things (IoT). We can achieve this improvement using an efficient content dissemination and forwarding technique that depends on name-based routing, in-network content caching, and interest-based content retrieval. The large amount of data processed by several IoT sensors or nodes of VANETs makes content prioritizing and forwarding mechanism is crucial, especially when many end-users need common content simultaneously. Therefore, in this paper, we propose a content dissemination technique based on priority for boosting the service requirements of NDN-based cloud and mobile IoT nodes in the VANETs. The approach prioritizes the data flow of traffic into four classes: urgent, emergency, least, and average using a novel constrained location and deadline method, called New method employing Deadline Distance and Size of Data (NDDS). The highest priority is assigned to the data traffic with the emergency class, then urgent, average, and least class. To evaluate this proposed technique, a numerical simulation experiment is conducted by using the CloudSim toolkit. The simulation results demonstrate that the emergency data flow has minimum processing time, compared to the average, urgent, and least data flow, which can significantly enhance the QoS of NDN protocol-based Ad Hoc networks.
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Sun, Ling, Yun Liu, Qing-An Zeng, and Fei Xiong. "A novel rumor diffusion model considering the effect of truth in online social media." International Journal of Modern Physics C 26, no. 07 (April 30, 2015): 1550080. http://dx.doi.org/10.1142/s0129183115500801.
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In this paper, we propose a model to investigate how truth affects rumor diffusion in online social media. Our model reveals a relation between rumor and truth — namely, when a rumor is diffusing, the truth about the rumor also diffuses with it. Two patterns of the agents used to identify rumor, self-identification and passive learning are taken into account. Combining theoretical proof and simulation analysis, we find that the threshold value of rumor diffusion is negatively correlated to the connectivity between nodes in the network and the probability β of agents knowing truth. Increasing β can reduce the maximum density of the rumor spreaders and slow down the generation speed of new rumor spreaders. On the other hand, we conclude that the best rumor diffusion strategy must balance the probability of forwarding rumor and the probability of agents losing interest in the rumor. High spread rate λ of rumor would lead to a surge in truth dissemination which will greatly limit the diffusion of rumor. Furthermore, in the case of unknown λ, increasing β can effectively reduce the maximum proportion of agents who do not know the truth, but cannot narrow the rumor diffusion range in a certain interval of β.
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Ayadi, Mohamed Issam, Abderrahim Maizate, Mohammed Ouzzif, and Charif Mahmoudi. "Deep Learning Forwarding in NDN With a Case Study of Ethernet LAN." International Journal of Web-Based Learning and Teaching Technologies 16, no. 1 (January 2021): 1–9. http://dx.doi.org/10.4018/ijwltt.2021010101.
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In this paper, the authors propose a novel forwarding strategy based on deep learning that can adaptively route interests/data packets through ethernet links without relying on the FIB table. The experiment was conducted as a proof of concept. They developed an approach and an algorithm that leverage existing intelligent forwarding approaches in order to build an NDN forwarder that can reduce forwarding cost in terms of prefix name lookup, and memory requirement in FIB simulation results showed that the approach is promising in terms of cross-validation score and prediction in ethernet LAN scenario.
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Chen, Zhuo. "AI-Based Secure Undergraduates’ Ideological and Political Public Opinion Strategy." Security and Communication Networks 2022 (March 16, 2022): 1–10. http://dx.doi.org/10.1155/2022/8052594.
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The popularity of the Internet makes everyone have the right to speak. People are no longer passive receivers of information but propagators of information, and for this reason, cyber opinion comes into existence. Some social events that can arouse people’s sympathy and are related to people’s vital interests will eventually form cyber opinions through netizens’ comments, discussions, and forwarding. As members of the society, undergraduates have different interests, political tendencies, and social cognition. When making judgments and comments on controversial hot issues, undergraduates will make their own correct judgments of authenticity according to their own knowledge and social experience, which will make the propagation content of public opinion more diversified. Especially for ideological and political public opinion, it is very important to ensure the safety of the public opinion propagation model intelligently. In this paper, first, cellular automata (CA) of artificial intelligence (AI) is used to establish the propagation model of undergraduates’ ideological and political safety public opinion and the stochastic immune mechanism model is introduced. Then, a CA-based stochastic immune mechanism model is adopted to simulate the real propagation process of undergraduates’ ideological and political public opinion. Finally, the experimental results demonstrate that the moving probability of public opinion subjects has a great impact on the propagation speed and homogenization rate of cyber public opinion and the proposed CA model can well describe the actual propagation process of cyber public opinion. Meanwhile, the proposed propagation model can ensure the propagation of undergraduates’ ideological and political public opinion on safety.
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Ramadhan, Ghama Fadhila, Rastri Kusumaningrum, and Flori Mardiani Lubis. "Strategi Customer Relation PT. Panah Perdana Logisindo Dalam Upaya Peningkatan Kualitas Pelayanan Jasa Freight Forwarding." Jurnal Pemasaran Kompetitif 6, no. 3 (June 1, 2023): 249. http://dx.doi.org/10.32493/jpkpk.v6i3.28687.
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Penelitian ini menggunakan metode deskriptif kualitatif, yang meneliti bagaimana proses PT Panah Perdana Logisindo berhubungan dengan pelanggan. Pengambilan data dilakukan dengan cara observasi langsung pada kantor PT Panah Perdana Logisindo serta mewawancara informan yang sesuai dengan karateristik yang ditentukan, karakteristik yang dimaksud adalah karyawan atau direksi yang terlibat dalam proses perancangan customer relation. Penelitian ini didasarkan oleh konsep CRM dari Anton dan Goldenberry yang menyebutkan 3 konsep utama dalam CRM yakni, Karyawan (People), Teknologi (Technology), dan Proses (Process).Hasil dari penelitian ini menunjukan, PT Panah Perdana Logisindo mencari sumber daya manusia yang sesuai dengan kualifikasi perusahaan, membangun interaksi sosial yang baik antar karyawan, dan meningkatkan kemampuan dasar yang telah dimiliki oleh karyawannya dalam pengoptimalannya di bidang karyawan (People). PT Panah Perdana Logisindo dalam pengoptimalannya pada bidang teknologi (Technology) juga melakukan penyimpanan database dari konsumen, selalu mendengarkan dan menyesuaikan kepentingan konsumen serta kemampuan perusahaan, dan tetap mengawasi proses penerapan CRM. Dan yang terakhir dalam proses-nya (Process) PT Panah Perdana Logisindo selalu memulai dengan pengenalan terhadap konsumen, lalu penentuan pesan yang akan disampaikan, serta menetapkan metode penyampaian pesan tersebut.This research uses a qualitative descriptive method, which examines how the process of PT Panah Perdana Logisindo relates to customers. Data collection was carried out by direct observation at the PT Panah Perdana Logisindo office and interviewing informants according to the specified characteristics, the characteristics in question were employees or directors who were involved in the customer relations design process. This research is based on the CRM concept from Anton and Goldenberry which mentions 3 main concepts in CRM namely, Employees (People), Technology (Technology), and Process (Process). The results of this study indicate, PT Panah Perdana Logisindo is looking for human resources who in accordance with the company's qualifications, building good social interaction between employees, and improving the basic capabilities that employees already have in optimizing them in the field of employees (People). PT Panah Perdana Logisindo in its optimization in the field of technology (Technology) also keeps databases from consumers, always listens to and adjusts to consumer interests and company capabilities, and keeps an eye on the CRM implementation process. And finally, in the process, PT Panah Perdana Logisindo always starts with an introduction to the consumer, then determines the message to be conveyed, and determines the method of delivering the message
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Jumaa, Noor, Abbas Allawy, and Mustafa Shubbar. "Modelling and optimising a new hybrid ad-hoc network cooperation strategy performance using genetic algorithm." Serbian Journal of Electrical Engineering 18, no. 2 (2021): 193–210. http://dx.doi.org/10.2298/sjee2102193j.
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The lifetime of an ad-hoc network depends on a mobile device?s limited battery capacity. In ad-hoc multi-hop communication, source nodes use intermediate nodes as a relay to communicate with remote destinations. As cooperation between nodes is restrained by their battery resources, it might not be in their best interests to always accept relay requests. Therefore, if all nodes decide how much energy to spend for relaying, selfish or non-cooperative nodes reduce cooperation by rejecting to forward packets to others, thereby leading to a dramatic drop in the network?s throughput. Three strategies have been founded to solve this problem: tit-for-tat, live-and-let-live, and selective drop. This research explored a new strategy in ad-hoc cooperation which resulted from the combination of the live-and-let-live and selective drop strategies. This new strategy is based on the suggestion to select fewer hops with a low drop percentage and sufficient power to stay alive after forwarding the data packets towards the destination or other relays at the route path. We used a genetic algorithm (GA) to optimise the cooperative problem. Moreover, the fitness equation of the GA population was designed according to the mixing of the two strategies, which resulted in a new optimized hybrid dynamic-static cooperation.
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Delvadia, Krishna, and Nitul Dutta. "Reinforcement learning inspired forwarding strategy for information centric networks using Q‐learning algorithm." International Journal of Communication Systems, January 24, 2024. http://dx.doi.org/10.1002/dac.5707.
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SummaryContent interest forwarding is a prominent research area in Information Centric Network (ICN). An efficient forwarding strategy can significantly improve data retrieval latency, origin server load, network congestion, and overhead. The state‐of‐the‐art work is either driven by flooding approach trying to minimize the adverse effect of Interest flooding or path‐driven approach trying to minimize the additional cost of maintaining routing information. These approaches are less efficient due to storm issues and excessive overhead. Proposed protocol aims to forward interest to the nearest cache without worrying about FIB construction and with significant improvement in latency and overhead. This paper presents the feasibility of integrating reinforcement learning based Q‐learning strategy for forwarding in ICN. By revising Q‐learning to address the inherent challenges, we introduce Q‐learning based interest packets and data packets forwarding mechanisms, namely, IPQ‐learning and DPQ‐learning. It aims to gain self‐learning through historical events and selects best next node to forward interest. Each node in the network acts as an agent with aim of forwarding packet to best next hop according to the Q value such that content can be fetched within fastest possible route and every action returns to be a learning process, which improves the accuracy of the Q value. The performance investigation of protocol in ndnSIM‐2.0 shows the improvement in a range of 10%–35% for metrics such as data retrieval delay, server hit rate, network overhead, network throughput, and network load. Outcomes are compared by integrating proposed protocol with state‐of‐the‐art caching protocols and also against recent forwarding mechanisms.
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Delvadia, Krishna, and Nitul Dutta. "CTJIF-ICN: A Coadjuvant Trust Joint Interest Forwarding Mechanism in Information Centric Networks." International Research Journal of Multidisciplinary Technovation, February 10, 2024, 12–33. http://dx.doi.org/10.54392/irjmt2422.
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The Information centric networks (ICN) transforms the focal point of current Internet paradigm to data centric approach from host centric approach by allowing content driven forwarding and in-network caching mechanisms. Though NDN (Named data networking) paradigm of ICN assures a secure content communication, it is vulnerable to different attacks by the malicious nodes. To minimize the hazards from compromised nodes and to improve the network security, the remaining nodes should transparently receive information about such nodes. This will restrict the forwarding strategy to exploit these malicious nodes for forwarding interest and content as well. Our protocol introduces a dynamic model for prediction of trust in order to evaluate the node trust. Proposed approach observes the historical behaviors of node and uses extended fuzzy logic rules for the prediction of future behaviors to evaluate the node’s trust value. This prediction model is incorporated within the trust based forwarding mechanism that aims to forward interest through secure and shortest path. The extensive simulation study has been carried out to analyze the protocol performance in ns-3 driven ndnSIM-2.0 simulator for performance metrics such as data discovery latency, packet delivery ratio, network overhead, detection ratio and cache hit ratio. When we integrate our trust joint forwarding strategy to state-of-the-art protocols, their performance is significantly improved up to approximately 10-35% against stated performance measures for realistic network topology.
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Akther, Nazma, Kingshuk Dhar, Shahid Md Asif Iqbal, Mohammad Nurul Huda, and _. Asaduzzaman. "Interest Forwarding Strategy in Named Data Networks (Ndn) Using Thompson Sampling." SSRN Electronic Journal, 2022. http://dx.doi.org/10.2139/ssrn.4046433.
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Dutta, Nitul. "A bargain game theory assisted interest packet forwarding strategy for information centric network." Journal of Network and Computer Applications, November 2022, 103546. http://dx.doi.org/10.1016/j.jnca.2022.103546.
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Araujo, Francisco Renato C., Andre Luiz R. Madureira, and Leobino N. Sampaio. "A Multicriteria-Based Forwarding Strategy for Interest Flooding Mitigation on Named Data Wireless Networking." IEEE Transactions on Mobile Computing, 2022, 1–15. http://dx.doi.org/10.1109/tmc.2022.3206167.
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"Performance Evaluation of Best Route and Broadcast Strategy for NDN Producer’s Mobility." International Journal of Engineering and Advanced Technology 9, no. 1 (October 30, 2019): 3671–77. http://dx.doi.org/10.35940/ijeat.a2712.109119.
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Named Data Networking is a novel concept mainly for the future Internet infrastructure that is centered on routable named data. The NDN infrastructure comprises of a new constituent known as the strategy layer. The layer give access for automatic selection of network routes by considering network pre-conditions such as delay in Interest messages forwarding via a producer. However, expressing appropriate pre-condition in selecting the best possible routes to forward Interest messages remains a challenging factor in NDN, because various parameters and conditions opposes one another when selecting best routes. Besides, it is possible for data in NDN to be retrieved from several sources. Yet, so far preceding research on forwarding strategy techniques that can calculate, from which route accurate NDN data contents content are realized does not regard a network attacker trying to transmit invalid data contents containing same name as accurate data. Therefore, this paper evaluate performance of forwarding strategy using analytical and simulation, and that can be compatible to related network applications such as voice. In analytical, we exploit the use of distribution function for consistency. These are the Probability Density Function (PDF) and Cumulative Distribution Function (CDF). In simulation, each application require its own form of forwarding policy using best route and broadcast. These were exploited to evaluate the total delay in a given interval from 10 through 50 seconds for five times. Similarly in our evaluation, a largescale ring topology was use in the simulation consisting of 30 nodes and 48 links. Link bandwidth is configured as 1Mbps. Numbers of content consumer/producer starts from 1 to 18 so as to achieve our simulations. Both consumers and producers were randomly selected in term of unique content request on the access network. ndnSIM 2.1 is used in simulating the scenarios for several time intervals. Performance results presents best route policy carries significant delay when compared with broadcast policy. Also, in our result, Delay metric is half the value obtained during analytical and simulation processes for NDN producer’s best route and broadcast using CDF, as compared to the value realized in our benchmark paper for NDN consumer.
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"Energy-efficient Delay-aware and Profit Maximization Caching enabled, Congestion Control in Stochastic Network." International Journal of Engineering and Advanced Technology 8, no. 6 (August 30, 2019): 4266–74. http://dx.doi.org/10.35940/ijeat.f9127.088619.
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We are presenting a new unified structure for dynamic distributed forwarding and congestion-controlled network caching enabled. Improved use of data transfer capacity and storage resources in Stochastic networks in aspects of energy-efficient and profit-maximization. In the investigation of stochastic networks, a framework has been developed for combined implementation of caching, forwarding and traffic command called the Markov Decision Process in Stochastic Learning (MDPSL) strategy. The MDPSL structure uses a virtual plane that manages customer request prices, as well as a real plane that processes actual interest packets and data packets. It can accomplish dynamically structured transmission and caching. It can fulfill dynamically distributed forwarding and caching. Focus on MDPSL communication and queuing systems, including wireless networks with time-varying channels, mobility, and arrival of random traffic. Using this framework, estimates of the time are optimized such as throughput, utility throughput, energy, and distortion. Explicit performance-delay tradeoffs are provided to show the expense of attaining optimality. A congestion control algorithm is intended to improve client services subject to network stability when optimally coupled with forwarding and caching algorithms
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Yang, Ching-Chiao, Po-Lin Lai, and Xiaonan Zhu. "Can corporate social responsibility enhance organizational image and commitment in the ocean freight forwarding industry?" Maritime Business Review ahead-of-print, ahead-of-print (May 17, 2021). http://dx.doi.org/10.1108/mabr-01-2021-0005.
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Purpose In the past few decades, the concept of corporate social responsibility (CSR) has received substantial interest in the competitive business environment. This study aims to empirically examine the impact of CSR on corporate image, organizational commitment and organizational performance in ocean freight forwarders. Design/methodology/approach Five critical CSR dimensions were identified based on factor analysis: consumer interests, employee interests, environmental management, disclosure and corporate commitment and sponsorship. Structural equation modelling was subsequently performed to examine the hypothesized relationships among CSR, corporate image, organizational commitment and organizational performance. Findings Results indicated that CSR had significantly positive effects on corporate image and organizational commitment, whereas corporate image was positively related to organizational commitment and organizational performance, respectively. Organizational commitment was also positively related to organizational performance. However, CSR did not have a significant direct effect on organizational performance. Research limitations/implications This study intended to conduct a survey on logistics service providers; however, due to the limited availability of research on ocean freight forwarding service providers, the present sample was limited to ocean freight forwarding enterprises. Originality/value From a theoretical perspective, this study contributes to the field by identifying the important dimensions of CSR and their effects on corporate image, organizational commitment and organizational performance. Particularly, it demonstrated the effect of CSR on ocean freight forwarding employees’ organizational commitment.
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Mohr, Iris, Leonora Fuxman, and Ali B. Mahmoud. "A triple-trickle theory for sustainable fashion adoption: the rise of a luxury trend." Journal of Fashion Marketing and Management: An International Journal ahead-of-print, ahead-of-print (August 19, 2021). http://dx.doi.org/10.1108/jfmm-03-2021-0060.
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PurposeThis article critically synthesizes the literature on sustainable fashion, the movement behind it and plausible fashion adoption theories. Then, to build on those studies, developing a new theory about adopting sustainable fashion – mainly among millennials and Generation Z who are behind forwarding and adopting this fashion trend – is sought after.Design/methodology/approachThis is a theory-synthesized conceptual article that presents a literature-informed new theoretical structure pronouncing sustainable fashion adoption and its rise as a new luxury trend. That included explicating and unraveling the conceptual foundations and construction elements that different viewpoints use to articulate the trend under investigation and the searches for a common basis to construct a new and improved conceptual framework.FindingsThis study introduces the triple-trickle theory that incorporates the role of media and technology to organize and understand the diffusion of sustainable fashion and identify paths for future trickle-effects on fashion research.Research limitations/implicationsEven though this has the benefit of offering a vast array of views and evidence that offers an adequate problem inspection, further studies providing empirical evidence are needed to establish the external validity of the theory derived from this research.Practical implicationsThis theory can be applied to develop targeted practices to understand the diffusion and adoption of sustainable fashion and further practitioners’ understanding of product positioning, target marketing, marketing strategy and luxury opportunities in general.Originality/valueThough interest in sustainable fashion has increased among consumers, no theory or model exists to explain its adoption. Therefore, the triple-trickle theory is proposed and aimed to be a more relevant framework to offer a theoretical premise for future empirical investigations of sustainable fashion adoption.
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B R, Sreenivasa, Husam Lahza, Nandini G, Tawfeeq Shawly, Ahmed A. Alsheikhy, Naveen Kumar K R, and Hassan Fareed Lahza M. "Social context‐aware macroscopic routing scheme for opportunistic network." Transactions on Emerging Telecommunications Technologies, August 10, 2023. http://dx.doi.org/10.1002/ett.4844.
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AbstractOpportunistic networks (OppNets) have attracted widespread attention as wireless technologies have advanced. OppNets are widely used in delay‐tolerant applications because they route messages using a store‐carry‐forward mechanism. Recently, socially aware routing has been increasingly modeled for message dissemination in OppNets, where the message is routed selectively through cooperative nodes based on user interests; however, routing becomes extremely difficult as node density and data size increase. However, the current method fails to reduce data redundancy, message overhead, delay, and improve performance efficiency. To address the issues, this article proposes social context‐aware microscopic routing (SCAMR) for OppNets. SCAMR uses cluster‐based communication, novel social‐context association mapping, and an improved lost packet retrieval mechanism with minimal messaging overhead. In this work, the experiment was performed by considering three scenarios: varying node size, varying buffer size, and varying time‐to‐live size. The experimental results show that the SCAMR scheme improves delivery ratio by 71.25%, 67.87%, 69.18%, reduces delay by 33.93%, 26.68%, 35.36%, reduces the number of hop nodes (i.e., messaging overhead) by 77.84%, 71.53%, 76.04% over existing approaches namely, SCARF (SoCial‐Aware Reliable Forwarding Technique for Vehicular Communications), SRS (secure routing strategy), and EDT (effective data transmission) considering different scenarios, respectively.