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Smart city article details
| Title | An Energy-Aware Iot Routing Approach Based On A Swarm Optimization Algorithm And A Clustering Technique |
|---|---|
| ID_Doc | 8008 |
| Authors | Sadrishojaei M.; Navimipour N.J.; Reshadi M.; Hosseinzadeh M. |
| Year | 2022 |
| Published | Wireless Personal Communications, 127, 4 |
| DOI | http://dx.doi.org/10.1007/s11277-022-09927-0 |
| Abstract | The Internet of Things (IoT) comprises many nodes dispersed around a particular target region, and it has lately been applied in a variety of sectors such as smart cities, farming, climatology, smart metering, waste treatment, and others. Even though the IoT has tremendous potential, some difficulties must be addressed. When building the clustering and routing protocol for huge-scale IoT networks, uniform energy usage and optimization are two significant concerns. Clustering and routing are well-known NP-hard optimization challenges applied to the IoT. The ease with which chicken can be implemented has garnered much interest compared to other population-based metaheuristic algorithms in solving optimization problems in the IoT. Aiming to reduce and improve node energy consumption in the IoT network by choosing the most suitable cluster head, the current effort seeks to extend the life of a network by selecting the most appropriate cluster head. A new cost function for homogenous dispersion of cluster heads was proposed in this research, and a good balance among exploration and exploitation search skills to create a node clustering protocol based on chicken search. This procedure is a big step forward from previous state-of-the-art protocols. The number of packets received, the total power consumption, the number of active nodes, and the latency of the suggested integrated clustered routing protocol are all used to evaluate the protocol's overall performance. The proposed strategy has been demonstrated to improve power consumption by at least 16 percent. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. |
| Author Keywords | Chicken swarm optimization; Cluster head; IoT; Power consumption; Swarm intelligence |
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