Smart City Gnosys

Smart city article details

Title Contextual Cluster-Based Glow-Worm Swarm Optimization (Gso) Coupled Wireless Sensor Networks For Smart Cities
ID_Doc 15953
Authors Ramesh P.S.; Srivani P.; Mahdal M.; Sivaranjani L.; Abidin S.; Kagi S.; Elangovan M.
Year 2023
Published Sensors, 23, 14
DOI http://dx.doi.org/10.3390/s23146639
Abstract The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH’s routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network’s lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique’s throughput and energy efficiency. © 2023 by the authors.
Author Keywords cluster head; glow-worm; multi-parameters; optimization and heterogeneous; retransmission ratio


Similar Articles


Id Similarity Authors Title Published
8370 View0.892Darabkh K.A.; Amareen A.B.; Al-Akhras M.; Kassab W.K.An Innovative Cluster-Based Power-Aware Protocol For Internet Of Things Sensors Utilizing Mobile Sink And Particle Swarm OptimizationNeural Computing and Applications, 35, 26 (2023)
30756 View0.89Kumar A.; Agrawal K.K.Improved Swarm Based Distributed Energy- Efficient Clustering Protocol For Iot Network Using Hybrid Optimization MethodJournal of Information Systems Engineering and Management, 10 (2025)
23415 View0.885Alomari M.F.; Alrubaye J.S.; Alaidi A.H.M.; Alrikabi H.T.H.S.Energy-Aware Collaborative Routing Protocol Using Bio-Inspired Algorithms For Heterogeneous Wireless Sensor NetworksJournal of Advances in Information Technology, 16, 5 (2025)
49667 View0.879Darabkh K.A.; Al-Akhras M.Smart Cities Optimization Using Computational Intelligence In Power-Constrained Iot Sensor NetworksSwarm and Evolutionary Computation, 94 (2025)
8298 View0.876Wang X.; Peng Y.; Huang L.An Improved Unequal Cluster-Based Routing Protocol For Energy Efficient Wireless Sensor NetworksProceedings - 2019 International Conference on Intelligent Transportation, Big Data and Smart City, ICITBS 2019 (2019)
23460 View0.876Devassy D.; Johnraja J.I.; Paulraj G.J.L.Energy-Efficient Chicken Swarm Optimization Algorithm Using Multiple Cluster Head Selection In Wireless Sensor NetworksICISTSD 2022 - 3rd International Conference on Innovations in Science and Technology for Sustainable Development (2022)
31134 View0.876Venkatesan V.K.; Izonin I.; Periyasamy J.; Indirajithu A.; Batyuk A.; Ramakrishna M.T.Incorporation Of Energy Efficient Computational Strategies For Clustering And Routing In Heterogeneous Networks Of Smart CityEnergies, 15, 20 (2022)
8008 View0.874Sadrishojaei M.; Navimipour N.J.; Reshadi M.; Hosseinzadeh M.An Energy-Aware Iot Routing Approach Based On A Swarm Optimization Algorithm And A Clustering TechniqueWireless Personal Communications, 127, 4 (2022)
61976 View0.872Gupta A.; Dubey T.K.Wireless Sensor Netwok Based Energy-Efficient Clustering Algorithm For Enabled Smart Cities Applications2024 15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024 (2024)
28645 View0.872Singh S.; Nikolovski S.; Chakrabarti P.Gwlbc: Gray Wolf Optimization Based Load Balanced Clustering For Sustainable Wsns In Smart City EnvironmentSensors, 22, 19 (2022)