Volume 16, Number 5

ENIAO: Energy Aware Faulty Node Re-Placement Integrated With Duty Cycling and Improved Harmony Search Based Clustering through Adaptive Fish School Search Routing for WSN Optimization

  Authors

RM.Alamelu¹, J.Naveen Ananda Kumar², C.Jayapratha³ and Govindaprabhu GB⁴, ¹Sri sarada Niketan College for Women, India, ²Tekinvaderz LLC, USA, ³Karpaga Vinayaga College of Engineering & Technology, India, ⁴Madurai Kamaraj University (MKU), India

  Abstract

In wireless sensor networks (WSNs), sensor nodes are constrained by resource constraints. The limited energy supply and susceptibility to failure greatly affect WSN lifespan, hindering long-term deployment. ENIAO is an Integrated cross-layer Optimized Routing Approach for WSNs that is fault-tolerant and energy-efficient. A bio-inspired clustering architecture and adaptive duty cycling are incorporated into ENIAO's routing optimization. In a clustering protocol, the network is partitioned, and paths are dynamically optimized within and between clusters. By optimizing active/sleep schedules, duty cycling optimizes energy efficiency. A variety of network conditions have been simulated to assess ENIAO's performance. Regarding fault tolerance and energy consumption, ENIAO significantly prolongs the network lifetime. As compared to benchmark protocols, it achieves higher throughput. As a result of the cross-layer design, ENIAO is automatically adapted to optimize energy usage and routing reliability. In the long run, large-scale IoT deployments are possible with ENIAO due to the integrated approach.

  Keywords

ENIAO, WSN, Fish School Search Routing, Duty Cycling, Improved Harmony Search based Clustering, Energy efficient, WSN Optimization.