Smart City Gnosys
Smart city article details
| Title | Energy Efficient Clustering Using Modified Promethee-Ii And Ahp Approach In Wireless Sensor Networks |
|---|---|
| ID_Doc | 23231 |
| Authors | Srivastava A.; Mishra P.K. |
| Year | 2023 |
| Published | Multimedia Tools and Applications, 82, 30 |
| DOI | http://dx.doi.org/10.1007/s11042-023-15378-x |
| Abstract | In wireless sensor networks (WSNs), sensor nodes were considered to be an integral part of IoT (Internet of Things) for sensing and monitoring the environment. The IoT-based applications need to be optimized regarding the changing requirements of users as everything is connected via the internet. In today’s era, where every day new technologies were rebuilt where sensor nodes plays an important role on it. In every field, whether it is healthcare, smart agriculture, smart home appliances, smart traffic, or smart city sensors were deployed for sensing their environment, collecting data from them, and forwarding it to the servers. These sensor nodes were made up of non-rechargeable power batteries, as a fact efficient energy consumption of these batteries becomes vital. In WSN, efficient energy consumption is still an issue, and its solutions were given by many researchers among them, clustering is considered to be more effective in this domain. For efficient energy consumption, multi-attributes of cluster head selection need to be considered and proper coordination among the conflicting nature of multi-attributes needs to be done. In this paper, we have proposed PROMETHEE II and modified AHP together for cluster heads selection by considering multi-attributes. Twenty-one attributes were considered including connectivity, distance to the base station, residual energy, member nodes, and many more. Being conflicting in nature, proper coordination among these attributes has been done and optimal cluster heads were selected modified for data transmissions. In this paper, modified AHP has been compared with our proposed modified PROMETHEE II and AHP for understanding the significance of this integration. Results is evaluated in terms of energy consumption, network lifetime, and load balancing and it also validate that our proposed approach outperforms with modified AHP and other existing algorithms. Our proposed algorithm enriches network lifetime by balancing the load among sensor nodes which leads to efficient energy consumption. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
| Author Keywords | Cluster head selection; Clustering; Efficient energy; IoT; MADM method; Network lifetime; WSN |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
35434  | 0.892 | Srivastava A.; Mishra P.K. | Load-Balanced Cluster Head Selection Enhancing Network Lifetime In Wsn Using Hybrid Approach For Iot Applications | Journal of Sensors, 2023 (2023) |
| 913 | 0.889 | Nedham W.B.; Al-Qurabat A.K.M. | A Comprehensive Review Of Clustering Approaches For Energy Efficiency In Wireless Sensor Networks | International Journal of Computer Applications in Technology, 72, 2 (2023) |
| 40804 | 0.886 | Sunil G.; Tuteja G.; Nasra P.; Abbas H.M. | Optimizing Energy-Efficient Clustering Algorithms For Prolonged Lifetime In Wsn-Iot Deployments | 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2025 (2025) |
| 6226 | 0.87 | Wang L.; Wang H. | Adaptive Crow Search Algorithm For Hierarchical Clustering In Internet Of Things-Enabled Wireless Sensor Networks | International Journal of Advanced Computer Science and Applications, 16, 4 (2025) |
| 3423 | 0.868 | Darabkh K.A.; Al-Akhras M. | A Novel Load-Driven Location-And Power-Aware Eo-Based Iot-Wsn Clustering And Routing Protocol For Sustainable Smart Cities | IEEE Internet of Things Journal (2025) |
| 8457 | 0.867 | Baskaran P.; Karuppasamy K. | An Integrated Model For Energy Conservation In Iot-Enabled Wsn Using Adaptive Regional Clustering And Monkey Inspired Optimization | Journal of Intelligent and Fuzzy Systems, 43, 4 (2022) |
| 8882 | 0.865 | Saleh S.S.; Alansari I.S.; Farouk M.; Hamiaz M.K.; Ead W.; Tarabishi R.A.; Khater H.A. | An Optimized Hierarchal Cluster Formation Approach For Management Of Smart Cities | Applied Sciences (Switzerland), 13, 24 (2023) |
| 34835 | 0.864 | Liu D.; Liang C.; Mo H.; Chen X.; Kong D.; Chen P. | Leach-D: A Low-Energy, Low-Delay Data Transmission Method For Industrial Internet Of Things Wireless Sensors | Internet of Things and Cyber-Physical Systems, 4 (2024) |
| 8370 | 0.863 | Darabkh 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 Optimization | Neural Computing and Applications, 35, 26 (2023) |
| 58247 | 0.86 | Darabkh K.A.; Al-Akhras M. | Towards Optimized Iot Sensor Networks For Smart Cities: Centrality-Aware Position-Based Occlusion-Driven And Role Dynamics Solutions For Clustering And Routing | IEEE Internet of Things Journal (2025) |