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An enhanced routing algorithm based on a re-position particle swarm optimization (RA-RPSO) for wireless sensor network

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第10期34卷 10304-10318页

作者： Elshrkawey, Mohamed Al-Mahdi, Hassan Atwa, Walid Suez Canal Univ Fac Comp & Informat Dept Informat Syst Ismailia 41522 Egypt Suez Canal Univ Fac Comp & Informat Dept Comp Sci Ismailia 41522 Egypt Menoufia Univ Fac Comp & Informat Dept Comp Sci Menoufia Egypt

Energy saving is a major requirement in the design of routing algorithms to maximize the throughput and lifetime of wireless sensor networks. To address this requirement, this work proposes a routing algorithm based on a novel Reposition Particle Swarm Optimization (RPSO) algorithm and a new fitness function. The role of the RPSO algorithm is to salvage particles that may have fallen into local minima, if any. The algorithm is evaluated using three types of benchmark functions, namely unimodal, multimodal, and rotated multimodal. The evaluation results demonstrate that RPSO outperforms native Particle Swarm Optimization and Particle Swarm Optimization with Levy Flight in terms of convergence speed and global optimum identification. The proposed RPSO is then employed to develop an efficient routing algorithm. The routing algorithm is tested in terms network lifetime, number of dead sensor nodes, energy consumption, and number of packets delivered to base station, against four competitive MetaHeuristic algorithms. The test results clearly indicate that the routing algorithm outperforms all the competitive algorithms for all the performance metrics. In particular, it achieves 14% to 29% higher network lifetime, 52% to 58% less dead sensor nodes, 61% to 70% less energy consumption, and 13% to 36% more throughput.

关键词： PSO Mult-objective function Wireless sensor network Clustering routing algorithm Power consumption

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On the correctness of inside-out routing algorithm

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IEEE TRANSACTIONS ON COMPUTERS 1997年第7期46卷 820-823页

作者： Kim, MK Yoon, H Maeng, SR KOREA ADV INST SCI & TECHNOL DEPT COMP SCIYUSUNG GUTAEJON 305701SOUTH KOREA

Recently, a new routing algorithm called inside-out routing algorithm was proposed for routing an arbitrary permutation in the omega-based 2log(2) N stage networks. This paper discusses the problems of the inside-out routing algorithm and shows that the suggested condition for proper routing in the omega-omega network is insufficient. An extended necessary and sufficient condition for proper routing in the omega-omega network is also suggested. However, it is unknown if any permutation can be successfully routed by a heuristic algorithm which follows the condition. Thus, the rearrangeability of the omega-omega network still remains an open problem.

关键词： multistage interconnection networks (MINs) asymmetric MINs omega-omega network rearrangeable networks routing algorithm

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A Near-Optimal Distributed QoS Constrained routing algorithm for Multichannel Wireless Sensor Networks

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SENSORS 2013年第12期13卷 16424-16450页

作者： Lin, Frank Yeong-Sung Hsiao, Chiu-Han Yen, Hong-Hsu Hsieh, Yu-Jen Natl Taiwan Univ Dept Informat Management Taipei 106 Taiwan Shih Hsin Univ Dept Informat Management Taipei 116 Taiwan

One of the important applications in Wireless Sensor Networks (WSNs) is video surveillance that includes the tasks of video data processing and transmission. Processing and transmission of image and video data in WSNs has attracted a lot of attention in recent years. This is known as Wireless Visual Sensor Networks (WVSNs). WVSNs are distributed intelligent systems for collecting image or video data with unique performance, complexity, and quality of service challenges. WVSNs consist of a large number of battery-powered and resource constrained camera nodes. End-to-end delay is a very important Quality of Service (QoS) metric for video surveillance application in WVSNs. How to meet the stringent delay QoS in resource constrained WVSNs is a challenging issue that requires novel distributed and collaborative routing strategies. This paper proposes a Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm to achieve an end-to-end route with lower delay and higher throughput. A Lagrangian Relaxation (LR)-based routing metric that considers the “system perspective” and “user perspective” is proposed to determine the near-optimal routing paths that satisfy end-to-end delay constraints with high system throughput. The empirical results show that the NODQC routing algorithm outperforms others in terms of higher system throughput with lower average end-to-end delay and delay jitter. In this paper, for the first time, the algorithm shows how to meet the delay QoS and at the same time how to achieve higher system throughput in stringently resource constrained WVSNs.

关键词： Wireless Sensor Networks Wireless Visual Sensor Networks system perspective user perspective QoS Near-Optimal Distributed QoS Constrained (NODQC) routing algorithm Lagrangian Relaxation

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Multi-user routing algorithm for indoor spaces-Adapted for social distancing

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第9期34卷 7045-7058页

作者： Alamri, Abdullah Alturki, Rayan Ali Alamri, Sultan Univ Jeddah Coll Comp Sci & Engn Jeddah Saudi Arabia Saudi Elect Univ Coll Comp & Informat Riyadh Saudi Arabia

The development of techniques and systems for indicating routes in outdoor and indoor spaces has received a great deal of attention. While outdoor route planning is based on criteria such as the shortest, fastest route, and the least number of turns, indoor route planning is primarily focused on accessibility and safety. routing systems for indoor spaces have become the focus of many researchers due to significant differences that make indoor routing is more complex than outdoor routing. An indoor environment is complex, which makes it difficult to find a route due to closed corridors, multiple floors, and other indoor features. Because of the present global scenario following the advent of the COVID-19 pandemic, indoor routing has become increasingly crucial. Wi-Fi, Bluetooth, and RFID are among the technologies used for indoor routing. For these technologies to help and guide users to the optimal route to their chosen destinations, they require accurate information, appropriate processing and modeling, and route density monitoring to ensure social distancing. In this paper, a new multi-user routing algorithm for indoor spaces is proposed. It has been adapted to the need for social distancing, and is based on multiple users, allowing more than one user to take the route or separate routes at one time without causing congestion on the same route. Despite the complexity of the system, the evaluation indicated that the proposed algorithm successfully controlled the flow of moving objects while ensuring social distancing and maintaining low costs. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： routing algorithm Indoor space Spatial databases Social distancing COVID-19 Indoor technology

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Wireless sensor networks routing algorithm based on particle swarm optimisation

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INTERNATIONAL JOURNAL OF INTERNET PROTOCOL TECHNOLOGY 2018年第3期11卷 159-164页

作者： Yang, Junhan Xian Univ Sci & Technol Sch Comp Xian 710054 Shaanxi Peoples R China

routing policy is a key problem in wireless sensor network (WSN), and it aims to find an optimal path to transmit the data of source nodes to the destination nodes. Wireless sensor networks can represented as a graph model, where graph nodes refers the wireless sensors, and graph edges are used to connects various sensors. Furthermore, in this work, we suppose that wireless sensor networks contain three types of nodes, including base station, gateway, and sensor. In the proposed algorithm, each particle is exploited to provide a suitable route from each cluster head to the base station, and the dimension of each particle is equal to the number of gateways in WSN. In the end, experimental results demonstrate that the proposed algorithm is able to effectively prolong network lifetime and increase the number of packets received by base station. Furthermore, the conclusion can be drawn that the proposed method can effectively solve the WSN's routing problem, because particle swarm optimisation is able to effectively optimise WSN routing scheme.

关键词： wireless sensor networks WSN routing algorithm particle swarm optimisation PSO linear programming

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A fuzzy-based fast routing algorithm with guaranteed latency-throughput over software defined networks

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JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES 2022年第10期34卷 8221-8233页

作者： Li, Hongsheng Osmani, Amjad Aziz, Amira Sayed A. Huanghuai Univ Sch Intelligent Manufacture Zhumadian 463000 Henan Peoples R China Islamic Azad Univ Dept Comp Engn Qazvin Branch Qazvin Iran Future Univ Egypt Fac Comp & Informat Technol Digital Media Dept New Cairo 11835 Egypt

With the development of online communications over the Internet, the network is required to guarantee the Quality of Service (QoS) requirements for different traffic flows. High quality and fast communication can be provided by Software-Defined Networks (SDN). SDN is a promising architecture for efficient man-agement of network resources by separating control logic from data planes. In order to ensure the QoS requirements of traffic flows in SDN, this paper proposes a Fuzzy-based fast and efficient routing algo-rithm with guaranteed Latency-Throughput (FRLR). The FRLR develops the dynamic routing problem in SDN using a traffic flow classification mechanism based on a fuzzy system. The purpose of the fuzzy sys-tem is to efficiently distribute resource allocation to improve the handling of future requests. In addition, the FRLR classifies traffic flows based on latency to reduce computational complexity. Besides, FRLR can effectively direct traffic flows and reduce network energy consumption by identifying critical links and selecting appropriate paths. Simulations on standard topologies with different scenarios confirm the bet-ter performance of FRLR by guaranteeing QoS requirements. The FRLR classifies traffic flows efficiently and offers significant improvements in the scalability and throughput of the network. Also, FRLR has pro-vided superior results compared to some state-of-the-art algorithms such as MDA, MDWCRA, FARP, ECMP, and QI-RM. Experimental results show that FRLR works on average between 7% and 24% better than other algorithms.(c) 2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Software defined networks Latency Throughput Traffic flows Fuzzy systems routing algorithm

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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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A New Reactive routing algorithm to Improve Capacity and Average End-to-End Delay in MANETs

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2015年第2期40卷 487-499页

作者： Bojd, Elahe Ataee Moghim, Neda Nassiri-Mofakham, Faria Movahedinia, Naser Univ Isfahan Fac Comp Engn Esfahan *** Iran

Delay and capacity are two important parameters in mobile ad hoc networks (MANETs). Increasing the network capacity almost leads to delay increases, as well. Many recent works have been conducted to achieve both desirable capacity and delay, simultaneously. To achieve such aim, this study proposes a new reactive routing algorithm. This algorithm modifies multi-hop Dynamic Virtual Router algorithm to overcome the performance limits of MANETs. Mobility metrics are defined to estimate the mobility degree of the nodes' neighborhood. A new route setup process is defined;using the estimated information and a local repair mechanism is also introduced in the new proposed algorithm. In this local repair mechanism, a new route is sought between the repairing node and its next hop on the communication path. Simulation study shows that the proposed algorithm significantly improves the network performance, including throughput and delay;so that, the increasing overhead is not remarkable considering the great performance improvement of the algorithm.

关键词： Mobile ad hoc networks routing algorithm Capacity Delay Mobility

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An optimized routing algorithm for vehicle ad-hoc networks

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ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH 2019年第3期22卷 754-766页

作者： Bello-Salau, H. Aibinu, A. M. Wang, Z. Onumanyi, A. J. Onwuka, E. N. Dukiya, J. J. Ahmadu Bello Univ Dept Comp Engn Zaria Nigeria Fed Univ Technol Dept Mechatron Engn Minna Nigeria Univ South Africa Sch Engn Dept Elect & Min Engn Florida South Africa Fed Univ Technol Dept Telecommun Engn Minna Nigeria Fed Univ Technol Minna Dept Transport Management Minna Niger State Niger

Efficient routing algorithms are essential to guarantee reliable communication in Vehicular Adhoc Networks (VANETs). In this paper, we present a twofold approach entailing the design of a new route metric for VANET communication, which considers important parameters such as the received signal strength;transmit power, frequency and the path loss. We further present an improved genetic algorithm-based route optimization technique (IGAROT) that guarantees better routing in VANETs. We used IGAROT to determine optimal routes required to communicate road anomalies effectively between vehicles in VANETs. The performance of our proposed algorithm was compared with the well-known conventional Genetic algorithm (GA) route optimization technique under same simulation conditions. Based on the average route results obtained, our findings indicate that IGAROT provided 4.24%, 75.7% and 420% increment over the conventional GA in the low, medium and high car density scenarios, respectively. Our findings suggest that IGAROT improves road anomaly communication among vehicles thus enabling drivers to better navigate anomalous roads with the aim to reduce road-anomaly induced accidents. Further benefits of our system may include the prompt notification of road maintenance agencies concerning persisting road conditions via vehicle to infrastructure communication. (C) 2019 Karabuk University. Publishing services by Elsevier B.V.

关键词： Genetic algorithm routing algorithm Route optimization routing protocols Route metric VANET

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