An adaptive fuzzy rule based energy efficient clustering and immune-inspired routing protocol for WSN-assisted IoT system

被引：1
作者：
Preeth S.K.S.L. [1 ]
Dhanalakshmi R. [1 ]
Kumar R. [2 ]
Shakeel P.M. [3 ]
机构：
[1] Department of CSE, NIT Nagaland, Chumukedima, Dimapur
[2] Department of Electronics and Instrumentation Engineering, NIT Nagaland, Chumukedima, Dimapur
[3] Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka
来源：
Journal of Ambient Intelligence and Humanized Computing | 2024年 / 15卷 / Suppl 1期
关键词：
Cluster head selection; Clustering; Routing and internet of things; Wireless sensor networks;
D O I：
10.1007/s12652-018-1154-z
中图分类号：
学科分类号：
摘要：
Energy efficiency is a significant problem in wireless sensor networks. Sensor networks are battery powered, therefore become a dead after certain period of time. In clustering technique, the cluster head selection is an essential issue. To moderate all above problems, this paper introduced adaptive fuzzy rule based energy efficient clustering and immune-inspired routing (FEEC-IIR) protocol for WSN assisted IoT system. For an optimal cluster head selection, adaptive fuzzy multi-criteria decision making approach (AF-MCDM) is used which is a combination of fuzzy AHP and TOPSIS method is introduced an energy efficient clustering algorithm. The criteria of energy status, QoS impact and node location are taken as the main factors that can influence the selection of cluster heads while each criteria contains some sub-criteria. For routing, immune-inspired optimization algorithm is used to enhance the data delivery reliability. The cluster based routing is an efficient manner to reduce the energy consumption. The experimental results show that our introduced approach improves the QoS parameters such as packet delivery ratio, packet loss ratio, throughput, network lifetime, end to end delay, channel load, jitter, bit error rate (BER), buffer occupancy and energy consumption compared with existing clustering and routing approach. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
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页码：33 / 33
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