An improved data aggregation for fog computing devices in internet of things

被引:0
|
作者
Jalasri M. [1 ]
Lakshmanan L. [2 ]
机构
[1] Department of AI&DS, Panimalar Engineering College
[2] Department of CSE, Sathyabama Institute of Science and Technology, Tamil Nadu, Chennai
关键词
cloud computing; clustering; EEHCA; energy efficient heterogeneous clustering algorithm; fog computing; internet of things; IoT; particle swarm optimisation; PSO; RFDs; river formation dynamics; routing; security; wireless sensor network; WSN;
D O I
10.1504/IJNVO.2024.137550
中图分类号
学科分类号
摘要
Diverse data that have private information are stored in the cloud by institutions and users. Fog computing has progressed with regard to service latency and has also been comprehensively studied. A proposal has been made in this work to secure IoT data, a clustering algorithm that utilises backup cluster head (CH) for network performance enhancement, and also utilises a multi-route protocol for data transmission towards the fog system. Comparisons are made between the proposed algorithm and the energy efficient heterogeneous clustering algorithm (EEHCA). A novel particle swarm optimisation (PSO) and river formation dynamics (RFDs) algorithm was proposed in this work for effective CH election in wireless sensor network (WSN) to efficiently transmit data towards the base station (BS) with minimised energy. This technique bypasses local optima during the solution search, leading to significantly improved results. RFD-EEHCA outperforms EEHCA by 8.53% and PSO by 8.09% in terms. © 2024 Inderscience Enterprises Ltd.
引用
收藏
页码:114 / 133
页数:19
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