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An intelligent fuzzy-based routing algorithm for video conferencing service provisioning in software defined networking

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TELECOMMUNICATION SYSTEMS 2024年第4期87卷 887-898页

作者： Wu, Changqian Zhang, Yulin Li, Na Rezaeipanah, Amin Minnan Sci & Technol Coll Key Lab Big Data & Artificial Intelligence Univ Fu Quanzhou 362000 Fujian Peoples R China Jose Rizal Univ Dept Business Adm Manila 1552 Philippines Tongji Univ Coll Elect & Informat Engn Shanghai 201800 Peoples R China Persian Gulf Univ Dept Comp Engn Bushehr Iran

The requirements for providing video conferencing services through Software-Defined Networking (SDN) are growing. The importance of this issue has been recognized by the research society, as video conferencing consumes significant network bandwidth. However, SDN can improve network performance and Quality of Service (QoS) by flexible mechanisms and adopting cheaper switches. The combination of SDN and fuzzy logic can provide a global perspective of traffic engineering to deal with these problems. In this study, we present an intelligent Fuzzy-based routing algorithm for Video Conferencing service provisioning under Latency and Bandwidth constraints in SDN (FRVCLB). FRVCLB considers the routing problem in SDN with guaranteed latency and bandwidth under QoS requirements, where the details of future requests are unknown. First, the network is weighted based on critical links to reduce routing interference on future requests. Second, FRVCLB uses a deferral module to temporarily postpone requests with high resource demands to manage connection priorities. Finally, an intelligent routing algorithm based on fuzzy logic is applied for routing on the weighted network. The results of the evaluations show that FRVCLB significantly improves the admission rate of video conferencing connections compared to its peers.

关键词： Software-defined networking Video conferencing services Fuzzy logic routing algorithm

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Multi-QoS routing algorithm based on reinforcement learning for LEO satellite networks

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Journal of Systems Engineering and Electronics 2025年第1期36卷 37-47页

作者： ZHANG Yifan DONG Tao LIU Zhihui JIN Shichao School of Integrated Circuit and Electronics Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Space-Ground Integrated Information Technology Space Star Technology Co.Ltd.Beijing 100095China

Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing *** satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite *** paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite *** auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing *** results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.

关键词： low Earth orbit(LEO)satellite network reinforcement learning multi-quality of service(QoS) routing algorithm

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Research on WSN Intelligent routing algorithm based on Bayesian Learning and Particle Swarm Optimization

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RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2024年第3期17卷 304-315页

作者： Jia, Songhao Yang, Cai Yang, Jizheng Zhang, Haiyu Chen, Xing Nanyang Normal Univ Coll Comp Sci & Technol Nanyang Peoples R China Henan Polytech Inst Fac Elect Informat Engn Nanyang Peoples R China

Background Wireless sensor networks have the characteristics of strong scalability, easy maintenance, and self-organization, but the energy of nodes is limited and it is difficult to replace the energy supply module. The survival time of the network has always been the key to restricting the development of wireless sensor *** Aiming at the problems of short network lifetime and low coverage, a multi-objective optimization routing algorithm has been proposed, focusing on how to balance the communication energy consumption of each node in the network and improve the coverage area of the remaining *** Firstly, the node region was divided into several fan ring subregions. Then, the particle swarm optimization algorithm was used to find the fan angles and radii of each fan ring subregion. Next, Bayesian learning was used to select the appropriate cluster *** The simulation results showed the convergence speed of the proposed algorithm to be improved, solving the problems of cluster head election and node routing planning, improving the utilization of node energy, and verifying the *** The particle swarm optimization algorithm and Bayesian learning have been introduced to cluster network nodes, and a multi-objective fitness function compatible with the energy consumption and coverage of network nodes has been designed. By optimizing the selection method of convergence nodes, the network communication cost of each node can be effectively balanced, and the speed of network coverage area reduction can be effectively reduced in the later period of node communication.

关键词： Wireless sensor network routing algorithm particle swarm optimization Bayesian learning method regional segmentation dynamic nodes multi-objective optimization

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Research on optimal intelligent routing algorithm for IoV with machine learning and smart contract

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Digital Communications and Networks 2023年第1期9卷 47-55页

作者： Baofeng Ji Mingkun Zhang Ling Xing Xiaoli Li Chunguo Li Congzheng Han Hong Wen Henan University of Science and Technology College of Information EngineeringLuoyang471000China The Institute of Atmospheric Physics Chinese Academy of Sciences(LAGEO)Beijing100029China Longmen Laboratory Luoyang471000China Chinese Academy of Agricultural Mechanization Sciences Beijing100000China University of Bristol BristolBS00UK University of Electronic Science and Technology of China Chengdu610000China

The huge increase in the communication network rate has made the application fields and scenarios for vehicular ad hoc networks more abundant and diversified and proposed more requirements for the efficiency and quality of data *** improve the limited communication distance and poor communication quality of the Internet of Vehicles(IoV),an optimal intelligent routing algorithm is proposed in this *** multiweight decision algorithm with the greedy perimeter stateless routing protocol,designed and evaluated standardized function for link *** additive weighting is used to optimize link stability and distance to improve the packet delivery rate of the *** blockchain system is used as the storage structure for relay data,and the smart contract incentive algorithm based on machine learning is used to encourage relay vehicles to provide more communication bandwidth for data packet *** proposed scheme is simulated and analyzed under different scenarios and different *** experimental results demonstrate that the proposed scheme can effectively reduce the packet loss rate and improve system performance.

关键词： IoV Machine learning Smart contract routing algorithm GPSR Relay transmission

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A reinforcement learning-based routing algorithm for large street networks

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INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 2024年第2期38卷 183-215页

作者： Li, Diya Zhang, Zhe Alizadeh, Bahareh Zhang, Ziyi Duffield, Nick Meyer, Michelle A. Thompson, Courtney M. Gao, Huilin Behzadan, Amir H. Texas A&M Univ Dept Geog College Stn TX 77843 USA Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA Texas A&M Univ Dept Construct Sci College Stn TX USA Texas A&M Inst Data Sci College Stn TX USA Texas A&M Univ Dept Landscape Architecture & Urban Planning College Stn TX USA Texas A&M Univ Dept Civil & Environm Engn College Stn TX USA

Evacuation planning and emergency routing systems are crucial in saving lives during disasters. Traditional emergency routing systems, despite their best efforts, often struggle to accurately capture the dynamic nature of flood conditions, road closures, and other real-time changes inherent in urban disaster logistics. This paper introduces the Reinforcerouting model, a novel approach to optimizing evacuation routes using reinforcement learning (RL). The model incorporates a unique RL environment that considers multiple criteria, such as traffic conditions, hazardous situations, and the availability of safe routes. The RL agent in this model learns optimal actions through interaction with the environment, receiving feedback in the form of rewards or penalties. The Reinforcerouting model excels in executing prompt and accurate route planning on large road networks, outperforming traditional RL algorithms and shortest-path-based algorithms. A higher safety score and episode reward of the model are demonstrated when compared to these classical methods. This innovative approach to disaster evacuation planning offers a promising avenue for enhancing the efficiency, safety, and reliability of emergency responses in dynamic urban environments.

关键词： Disaster evacuation reinforcement learning Geographic Information Science and Systems (GIS) artificial intelligence routing algorithm

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BeSnake: A routing algorithm for Scalable Spin-Qubit Architectures

IEEE TRANSACTIONS ON QUANTUM ENGINEERING

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IEEE TRANSACTIONS ON QUANTUM ENGINEERING 2024年第1期5卷 1页

作者： Paraskevopoulos, Nikiforos Almudever, Carmen G. Feld, Sebastian Delft Univ Technol Dept Quantum & Comp Engn NL-2628 CD Delft Netherlands Delft Univ Technol QuTech NL-2628 CJ Delft Netherlands Univ Politecn Valencia Dept Comp Engn Valencia 46022 Spain

As quantum computing devices increase in size with respect to the number of qubits, two-qubit interactions become more challenging, necessitating innovative and scalable qubit routing solutions. In this work, we introduce beSnake, a novel algorithm specifically designed to address the intricate qubit routing challenges in scalable spin-qubit architectures. Unlike traditional methods in superconducting architectures that solely rely on swap operations, beSnake also incorporates the shuttle operation to optimize the execution time and fidelity of quantum circuits and achieves fast computation times of the routing task itself. Employing a simple breadth-first search approach, beSnake effectively manages the restrictions created by diverse topologies and qubit positions acting as obstacles for up to 72% qubit density. It also has the option to adjust the level of optimization and to dynamically tackle parallelized routing tasks, all the while maintaining noise awareness. Our simulations demonstrate beSnake's advantage over an existing routing solution on random circuits and real quantum algorithms with up to 1000 qubits, showing an average improvement of up to 80% in gate overhead, 54% in depth overhead, and up to 8.33 times faster routing times.

关键词： Qubit routing Logic gates Computer architecture Topology Quantum circuit Task analysis Quantum compilation qubit mapping qubit routing routing algorithm spin qubits

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Vehicular delay tolerant network routing algorithm based on trajectory clustering and dynamic Bayesian network

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WIRELESS NETWORKS 2023年第4期29卷 1873-1889页

作者： Wu, Jiagao Cai, Shenlei Jin, Hongyu Liu, Linfeng Nanjing Univ Posts & Telecommun Sch Comp Nanjing 210023 Peoples R China Nanjing Univ Posts & Telecommun Jiangsu Key Lab Big Data Secur & Intelligent Proc Nanjing 210023 Peoples R China

Typically, delay tolerant network (DTN) suffers from frequent disruption, high latency, and lack of stable connections between nodes. As a special case of DTN, vehicular delay tolerant network (VDTN) has particular spatial-temporal characteristics. Different kinds of vehicles may have different movement ranges and movement patterns and the movements of vehicles exhibit significant dynamics from the temporal view. The movement patterns and dynamic characteristics of vehicles are difficult to be described accurately. To this end, a novel framework of VDTN routing algorithm based on trajectory clustering and dynamic Bayesian network (DBN) is proposed, which can capture the spatial-temporal characteristics and the movement patterns of vehicles in the real VDTN scenarios. Firstly, a K-means trajectory clustering (KTC) algorithm is adopted to cluster the trajectories of vehicles according to their spatial characteristics. Then, a KTC-based DBN structure learning algorithm is proposed to construct the prior network and transition network of DBN by an extended K2(+) algorithm to capture the temporal characteristics of VDTN, and multiple DBN models are established for different trajectory clusters to further improve the prediction accuracy. Finally, a VDTN routing algorithm is presented to forward message by the inference of DBN models. Simulation results show that the proposed VDTN routing algorithm has a higher delivery ratio as well as a lower overhead compared with other related routing algorithms, and the effectiveness of the trajectory clustering method and DBN models are verified.

关键词： Vehicular delay tolerant network routing algorithm K-means trajectory clustering Dynamic Bayesian network Performance

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Game-based congestion-aware routing algorithm in wireless network on chips

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INTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTING 2023年第4期42卷 258-268页

作者： Tahanian, Esmaeel Tajary, Alireza Rezvani, Mohsen Shahrood Univ Technol Fac Comp Engn Shahrood Iran

Wireless network on chip (WiNoC) has been introduced to alleviate some challenges with conventional NoC such as high latency and power consumption. routing the packet through the wireless links for arriving to far apart destination leads to a shorter path. Therefore, many of nodes prefer to send their packets to nearest wireless router on the WiNoC. When the demand for a wireless node increases, the likelihood of the congestion increases. To address this problem, we propose a game-based yet simple routing algorithm to balance the traffic in this paper. The WiNoC is modelled with a mixed-strategy Bayesian-game in which the nodes are the players with two valid actions namely, routing the packets with and without the wireless links. The simulation results show that using the proposed mixed-strategy for considerably improves the performance of the network, more precisely, the system performance is improved 10%-42% compared with the previous related works.

关键词： wireless network on chips WiNoCs routing algorithm game theory

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Analysis of multimedia network data security based on routing algorithm

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第1期18卷 23-32页

作者： Zheng, Li Zheng, Yuntian Wenzhou Power Co Wenzhou Zhejiang Peoples R China Chongqing Univ Coll Phys Chongqing Peoples R China

In today's society, the application of multimedia data is increasing, and the accompanying data security is also an important issue. This paper will analyze the data security of multimedia network based on routing algorithm. The advantages of wireless local area networks (WLAN) and ad hoc networks are combined in wireless mesh networks (WMNs), which have steadily grown to be a reliable method of wireless broadband access. The application of multi RF and multi-channel technology improves the performance of WMN. However, the limitation that includes the number of wireless network interface cards and channels in the network, results in the great challenges ofrouting and channel allocation in multi RF and multi-channel WMN. Based on AODV algorithm, this paper proposes a new cross layer routing algorithm which is JRCA-AODV algorithm. The simulation results demonstrate that the JRCA-AODV algorithm can successfully increase multiRF multi-channel WMN throughput while lowering packet loss rate and network delay. Take the packet rate of 8 Mbps as an example, the network throughput based on JRCA-AODV algorithm is 1.14 times that of MRMC-AODV algorithm, the packet loss rate based on JRCA-AODV algorithm is 14.06% lower than that of MRMC-AODV algorithm, and the network time delay based on JRCA-AODV algorithm is 14.27% lower than that of MRMC-AODV algorithm. At the same time, JRCA-AODV algorithm can effectively reduce the probability of data loss caused by the competitive and shared access mechanism of the channel, improve the success rate of data transmission, thus reduce the probability of data eavesdropping and tampering in the process of repeated transmission, and improve the security of multimedia network data. This will provide a new direction for promoting the idea of multimedia data security.

关键词： Multimedia network data security routing algorithm

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A Load Balance routing algorithm for Medical IoT Based on Link Quality

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WIRELESS PERSONAL COMMUNICATIONS 2023年第2期133卷 1265-1279页

作者： Shen, Hongming Cheng, Xingsi Xu, Boyang Shao, Wei Xu, Chen Shen, Xiaoyan Nantong Univ Sch Informat Sci & Technol Nantong Peoples R China Nantong Res Inst Adv Commun Technol Nantong Peoples R China Baokong Nantong IoT Technol Co Ltd Nantong Peoples R China

In order to address the pressing needs for energy efficiency, system stability, and reliable data transmission in medical Internet of Things (IoT) applications, a novel routing algorithm built upon Bluetooth Low Energy (BLE) mesh network architecture is proposed. This proposed algorithm quantifies the channel quality for each communication link within the network. By doing so, it retains only the two most viable links between the source and destination nodes to guarantee stability in message transmission. Moreover, the algorithm minimizes the number of solitary nodes functioning as intermediaries. This mitigates the risk of node over-utilization, which is a common cause of rapid battery depletion, thus prolonging the overall lifespan of the network. Comparative experimental data indicate that this proposed algorithm outperforms conventional mesh networking approaches in both channel quality and energy sustainability.

关键词： Medical IoT BLE mesh network routing algorithm B-AOMDV

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