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routing algorithm for Energy Efficiency Optimizing of Wireless Sensor Networks based on Genetic algorithms

WIRELESS PERSONAL COMMUNICATIONS 2023年第3期133卷 1373-1396页

作者： Albuquerque, Kaique Rhuan de Azevedo de Medeiros, Rafael Pereira Duarte, Rafael Moura Villanueva, Juan Moises Mauricio de Macedo, Euler Cassio Tavares Univ Fed Paraiba Joao Pessoa PB Brazil

With the popularization of wireless sensor networks (WSN) and the concept of IoT (Internet-of-things), several applications have emerged in the industrial, scientific and engineering sectors. However, energy consumption is a challenge, because the demands for improvement in transmission rates and latency limitations. In particular, increasing the lifetime of wireless sensor networks has been a common goal in recent research. A viable alternative to solve this problem consists in reducing the data traffic defined by the routing protocol, which optimizes the number of messages that travel through the network. These protocols can also be optimized using evolutive algorithms, such as genetic algorithms. In the present work, is proposed a routing algorithm for WSN based on genetic algorithms, with the purpose of minimizing the total distance from the sensor node to the sink, which would allow optimized use of energy by sensor nodes and extend the lifetime of the WSN. The proposed algorithm includes a form of chromosome coding that had not yet been used in the context of routing and a new multi-objective fitness function. Performance analyzes were carried out establishing exhaustive search (ES) and opportunistic routing (OR) algorithms as comparison references and considering two scenarios: an open field and the other in a closed residential area. Proposed algorithm revealed superior performance when compared to reference algorithms. In open space and in the residential scenario, the lifetime provided by the proposed algorithm was 7320 and transmissions greater than that provided by OR. It was also observed that, with the increase in the number of transmissions, the standard deviation of the nodes ' residual energy is smaller when GAEA-RP is applied, which means the predictability of the energy consumed by them. After 1.8x10(5) transmissions, it was 0.105 J for GAEA-RP versus 0.188 J for OR in the first scenario. In the second scenario, in addition to the smaller standard

关键词： Wirelles sensor network routing algorithm Genetic algorithm Energy balancing Optimize energy efficiency

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SQMCR: Stackelberg Q-Learning-Based Multi-Hop Cooperative routing algorithm for Underwater Wireless Sensor Networks

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IEEE ACCESS 2024年 12卷 56179-56195页

作者： Bin, Wang Ben, Kerong Hao, Yixue Zuo, Mingjiu Naval Univ Engn Coll Elect Engn Wuhan 430033 Peoples R China Huazhong Univ Sci & Technol Coll Comp Sci & Technol Wuhan 430074 Peoples R China

The underwater wireless sensor network (UWSNs) is an important communication facility supporting underwater monitoring applications. However, the transmission channel has the characteristics of high bit error rate, strong multipath effect, and many interference factors, and the network node has the characteristics of high energy consumption, difficult energy supply, and the node position vulnerable to change, which makes it extremely difficult for UWSNs to realize the reliable and efficient packet forwarding. To address the problem, we propose the Stackelberg Q-learning based multi-hop cooperative routing algorithm (SQMCR). The SQMCR builds the transmission routes based on the Q-learning algorithm, considering factors such as the delay, the remaining energy, and the network topology, which improves the rationality and adaptability of selecting the next-hop node. By balancing the packet forwarding benefits and the energy consumption costs based on the Stackelberg Q-learning algorithm, the SQMCR establishes the cooperative communication policy to ensure both the reliability and efficiency of underwater communications. It also adopts initializing Q-values and dynamic exploration probabilities optimization methods to further improve the performance of routing algorithms. Experimental results show that the SQMCR can help UWSNs increase the packet forwarding reliability and prolong the network lifetime by 17%. It has a better environment and application adaptability and is more suitable for underwater high-reliability applications.

关键词： Underwater wireless sensor networks (UWSNs) routing algorithm cooperative communication Stackelberg game

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Load balancing routing algorithm of industrial wireless network for digital twin

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COMPUTER NETWORKS 2025年 258卷

作者： Xiao, Linjie Li, Shining Wen, Qin Liang, Xiao Li, Yiming Wang, Wanbao Fu, Yuntao Northwestern Polytech Univ Xian 710129 Shaanxi Peoples R China

Digital twin is a transformative technology with the power to reshape the future of industries, which enables accurate simulation and optimization of the production process by creating virtual copies of physical entities. Industrial wireless network such as ISA100.11a, as an indispensable communication bridge in digital twin, provides a stable and reliable data transmission pathway for all-element connectivity. However, the access of a large number of nodes increases the risk of network congestion and poses a challenge to the real-time network transmission. Therefore, the intention of our research is to deal with network congestion by establishing a load balancing routing algorithm. First, considering the time-triggered characteristic of industrial scenarios, a directed acyclic graph model is established for multi-periodic communication streams. We analyze the causes of load imbalance in multi-source single-sink topology, and prove that choosing optimal path scheme is an NP- hard problem by generalizing to the multidimensional bin packing problem. Then, we theoretically derive the average load of the hierarchy, establish a loss function characterizing the degree of hierarchical load balancing, and propose a hierarchical load balancing strategy based on the black-winged kite algorithm by establishing a mapping relationship. Finally, a scheduling constraint model is introduced to evaluate the superiority of the proposed algorithm. Experimental validation shows that the proposed algorithm reduces 70.80%, 27.15%, 15.57%, 14.01% in terms of loss function value and 23.52%, 4.71%, 5.19%, 4.64% in terms of total delay as compared to Dijkstra algorithm, Greedy algorithm, Bat algorithm and Deep Q-Networks respectively.

关键词： Digital twin Industrial wireless network routing algorithm Load balancing Real-time transmission

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DFRDRL: a dynamic fuzzy routing algorithm based on deep reinforcement learning with guaranteed latency and bandwidth for software-defined networks

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JOURNAL OF BIG DATA 2024年第1期11卷 150页

作者： Wang, Yonghong Othman, Marini Choo, Wou Onn Liu, Ruiqing Wang, Xiaofeng Xinzhou Normal Univ Dept Comp Sci Xinzhou 034000 Shanxi Peoples R China INTI Int Univ Fac Data Sci & Informat Technol Nilai 71800 Negeri Sembilan Malaysia Xinzhou Normal Univ Dept Econ & Management Xinzhou 034000 Shanxi Peoples R China

Traditional routing algorithms have several limitations that become increasingly significant in the context of Software-Defined Networking (SDN). Firstly, these algorithms often have limited support for Quality of Service (QoS) requirements, making them less suitable for handling diverse traffic types efficiently. Moreover, current SDN controllers leverage a default shortest-path routing approach, which does not allow for more dynamic and flexible traffic management based on real-time network policies. To address these issues, this paper introduces a Dynamic Fuzzy routing algorithm based on Deep Reinforcement Learning (DRL) for SDN that provides guaranteed latency and bandwidth (DFRDRL). DFRDRL provides intelligent and efficient routing that adapts to dynamic traffic by considering path-state criteria and using DRL. Fuzzy logic mainly performs online routing between an ingress-egress pair. To adapt to dynamic traffic changes, DFRDRL can predict the traffic matrix in real time. Meanwhile, DFRDRL reduces the routing reliance on network topology by weighting the network based on critical nodes. Additionally, when the network experiences congestion based on the traffic matrix, a deferral mechanism is applied to prioritize requests with lower resource demands. This mechanism helps ensure efficient resource allocation by temporarily postponing or queuing higher-demand requests, thereby optimizing overall network performance during periods of congestion. The simulation results show that the performance of DFRDRL is better than the equivalent algorithms in terms of latency and throughput. Also, DFRDRL is about 2.5% more efficient than the best existing algorithm in terms of admission rate of routing requests.

关键词： Software-defined networking routing algorithm Dynamic routing Deep reinforcement learning

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An energy-efficient routing algorithm for dual-energy harvesting-assisted wireless sensor networks based on whale optimization strategy

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JOURNAL OF SUPERCOMPUTING 2025年第1期81卷 1-29页

作者： Sheng, Hao Jun, Chen Cui, Jianqun Fan, Xiying Zhen, Li Cent China Normal Univ Sch Comp Sci Wuhan 430079 Peoples R China Wuhan Inst Technol Hubei Key Lab Intelligent Robot Wuhan 430079 Peoples R China Xian Univ Posts & Telecommun Shaanxi Key Lab Informat Commun Network & Secur Xian 710121 Shaanxi Peoples R China Univ Sci & Technol Beijing Beijing Peoples R China

Energy harvesting (EH) wireless sensor networks (WSNs) have wide applications in various fields due to their ability to sense and transmit environmental information, while current routing algorithms on EH-WSN generally rely on a single EH method, such as solar or wind. Due to the uncertainty of EH efficiency, a single-type EH technique may not be able to meet the energy demand of WSNs. In light of this, we propose an energy-efficient dual EH routing algorithm based on whale optimization (WO) strategy (DEHRA-WO). In the modeling process, we firstly propose a dual EH (including solar EH and radio frequency charging (RFC) techniques) switching mechanism. Namely, if the collected solar energy is not enough to maintain the operation of WSNs, RFC is employed to harvest additional energy, in which the collected solar energy is predicted using Kalman filter theory. With this, a residual energy model is constructed to measure the energy status of nodes. Secondly, we provide a communication range model to confirm the transmission area of nodes, where the wireless fading environment is considered. After that, a data link layer model is established to reflect the node blocking state. Based on the above models, we define the evaluation function to indicate the possibility of a node to be selected as the next hop and then propose the overall path selection scheme using WO strategy. Moreover, we also prove the convergence of DEHRA-WO and analyze its complexity. Through extensive simulation experiments, we demonstrate the superior performance of DEHRA-WO in terms of packet loss rate and energy utilization.

关键词： Wireless sensor networks Dual-energy harvesting Kalman filter theory routing algorithm Whale optimization strategy

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CTWR: A congestion, temperature and wear-aware routing algorithm for partially-connected 3D network-on-chip

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COMPUTERS & ELECTRICAL ENGINEERING 2025年 124卷

作者： Asadboland, Mojtaba Mehranzadeh, Amin Mosleh, Mohammad Islamic Azad Univ Dept Comp Engn Dezful Branch Dezful Iran

Three-dimensional Network-on-Chip (3D-NoC) is an efficient solution to overcome communication limitations in complex System-on-Chip (SoC) architectures. However, challenges such as increased temperature, traffic congestion, and link wear-out significantly impact network performance and lifespan. In this study, we propose an adaptive routing algorithm named CTWR (Congestion, Temperature and Wear-aware routing), which simultaneously considers temperature, congestion, and wear-out while utilizing both intra-layer and inter-layer routing approaches to enhance network performance. The algorithm employs a dynamic approach to assess the realtime status of vertical links to control and reduce wear-out, selecting paths that mitigate thermal hotspots, balance traffic distribution, and extend the lifespan of interconnects. Extensive assessments and simulations performed under diverse traffic scenarios and multiple vertical link or elevator layout configurations indicate that the CTWR algorithm outperforms ETW, EF, HE, and Nezarat routing methods in reducing average packet delay by 92.71 %, 67.84 %, 56.33 %, and 26.91 %, respectively. Furthermore, our proposed approach enhances average network throughput by 9.88 %, 4.38 %, 2.64 %, and 1.66 % compared to these methods. Thermal analysis of the chip surface also reveals a lower overall temperature and a more balanced heat distribution than competing techniques.

关键词： 3D Network on Chip Partially connected routing algorithm Temperature-aware Congestion-aware Wear-aware

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An Efficient routing algorithm for Self-Organizing Networks in 5G-Based Intelligent Transportation Systems

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2024年第1期70卷 1757-1765页

作者： Quy, Vu Khanh Chehri, Abdellah Quy, Nguyen Minh Nguyen, Van-Hau Ban, Nguyen Tien Hung Yen Univ Technol & Educ Dept Informat Technol Hung Yen 160000 Vietnam Royal Mil Coll Canada Dept Math & Comp Sci Kingston ON K7K 7B4 Canada Posts & Telecommun Inst Technol Fac Telecommun Hanoi 100000 Vietnam

The rapid growth of the consumer Internet of Things (CIoT) has resulted in substantial enhancements in networking and data analytics. The emergence of customer-centric communication technologies like mobile ad hoc networks (MANETs) and vehicular ad hoc networks (VANETs), also known as self-organizing networks (SONs), along with the integration of 5G Internet of Things and artificial intelligence, has paved the way for intelligent transportation systems (ITS). In SONs, each vehicle serves as a network node. Hence, it is essential for these network nodes to interact, communicate, and exchange data in a flexible, efficient, and convenient manner. SONs offer revolutionary communication capabilities by enabling self-configuration, self-setting, and autonomous data transmission. However, one significant drawback of SONs is their poor network performance. In this study, we have developed an efficient routing scheme that aims to enhance the performance and reduce energy consumption of SONs for ITS in smart cities with low mobility speeds. The simulation results clearly show that the proposed algorithm performs better than conventional routing protocols in low-speed mobility scenarios. It outperforms in terms of network lifetime, packet delivery ratio, and latency.

关键词： routing routing protocols Measurement Ad hoc networks Mobile computing Internet of Things Clustering algorithms Consumer Internet of Things (CIoT) edge/fog computing routing algorithm low-speed transportation scenarios energy-saving effectiveness

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An Unequal Clustering Energy Consumption Balancing routing algorithm of UAV Swarm Based on Ultraviolet Secret Communication

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WIRELESS PERSONAL COMMUNICATIONS 2024年第1期137卷 221-235页

作者： Zhao, Taifei Cheng, Minhua Lyu, Xinzhe Zhang, Haijun Wang, Lu Xian Univ Technol Sch Automat & Informat Engn Xian 710048 Shaanxi Peoples R China

Focusing on the tasks collaboration requirements of Unmanned Aerial Vehicle (UAV) swarm in complex battlefield environment, it is especially important to ensure the reliability of routing communication within the formation. Wireless ultraviolet (UV) secret communication can meet the reliable and secret communication needs of UAV swarm in the complex atmospheric environment. Moreover, considering the limited energy carried by UAVs, in order to maximize the flight time of UAVs, this paper proposes an unequal clustering energy consumption balancing routing algorithm (UCEBRA) of UAV swarm based on UV secret communication. Combined the advantages of wireless UV scattering communication, this algorithm improves the selection threshold of candidate cluster heads (CHs) and the clustering conditions of nodes according to the performance of UAV nodes. Furthermore, a function, which can comprehensively reflect both distance and remaining energy of UAVs, is built in the process of inter-cluster routing, to balance the energy consumption of the CHs. The simulation results show that compared with low-energy adaptive clustering hierarchy (LEACH) and energy-efficient unequal clustering (EEUC), the energy efficiency of the UAV network is increased by 21.7% and 4.6% respectively, and the lifetime of the network prolongs by 26.2% and 7.8% under UCEBRA algorithm. Therefore, the algorithm proposed in this paper can efficiently balance the energy consumption of nodes and thus prolong the lifetime of UAV swarm.

关键词： UAV swarm Wireless UV communication routing algorithm Energy consumption balancing

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TB-TBP: a task-based adaptive routing algorithm for network-on-chip in heterogenous CPU-GPU architectures

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JOURNAL OF SUPERCOMPUTING 2024年第5期80卷 6311-6335页

作者： Fang, Juan Wei, Zhichao Liu, Yaqi Hou, Yumin Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China

With the rapid development of heterogeneous network-on-chip (NoC), a vast amount of shared resources are integrated into NoC. Intense resource competition exists between CPUs and GPUs, leading to congestion and a decrease in overall network performance. Reasonable node placement can minimize network conflicts at the topology level. This paper first discusses the placement of shared last-level cache and memory controller, then selects a more rational placement method and optimizes the path. To solve the hot spots problem in center placement method, a task-based routing algorithm is designed to plan the path. Simulation results demonstrate that, compared to the traditional routing algorithm, the overall network latency is reduced by 9%, and the CPU performance is improved by 13.6%. Furthermore, a dynamic task-based routing algorithm is proposed. Compared to the static task routing algorithm, the overall network latency is reduced by 2.08%, and the CPU performance is improved by 4.09%.

关键词： Heterogeneous architectures Network-on-chip (NoC) routing algorithm Task-based

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Social relationships and location information based routing algorithm in opportunistic networks

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INTERNET OF THINGS 2025年 29卷

作者： Wei, Guanghui Zhang, Feng Xu, Gang Seah, Winston K. G. Yuan, Zixuan Shi, Yongqiang Shanxi Univ Sch Comp & Informat Technol Taiyuan 030006 Shanxi Peoples R China Inner Mongolia Univ Coll Comp Sci Hohhot 010021 Inner Mongolia Peoples R China Victoria Univ Wellington Sch Engn & Comp Sci Wellington 6140 New Zealand

In opportunistic networks, the lack of a stable route between nodes necessitates the use of relay nodes for message transmission. In social attribute-based routing, the selection of relay nodes is mainly done according to historical encounter information among nodes. This historical information is used to compute utility values between nodes, which are then used to select relay nodes. However, when there is insufficient historical encounter information between source and destination nodes, the utility value between nodes may not be accurately calculated by traditional social routing strategies. This results in difficulties in selecting appropriate relay nodes and hence a low delivery ratio. To address this shortcoming, a routing algorithm based on social relationships and location information (SRLI) is proposed. Initially, historical encounter information among nodes is used to identify social relationships among nodes. Messages are forwarded to the relay nodes possessing higher social relationships with the destination nodes. To enhance the coverage of messages, the geographic cosine similarity between nodes is calculated. Messages are preferentially transmitted to adjacent nodes with lower similarity to the current node. In addition, a dynamic buffer management strategy is utilized to facilitate the appropriate discarding of messages. Lower priority messages are prioritized for deletion when a node buffer is full. Experimental results demonstrate that the proposed routing algorithm significantly outperforms the Epidemic, Prophet, and CHOP-NET algorithms in terms of message delivery ratio, average message forwarding latency and routing overhead. Our proposed SRLI is superior to CHOP-NET, Prophet and Epidemic by at least 16.9% in terms of average message forwarding latency and 7.7% in terms of message delivery ratio, while still being able to achieve 1.5% lower routing overhead.

关键词： Opportunistic networks routing algorithm Social relationships Cosine similarity Buffer management

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