Intelligent Triangulation based Sink Relocation and Energy-Equivalent Cluster based Routing for WSN assisted IoT
Keywords:
Wireless sensor networks (WSNs), Angle Separated Hexagon (ASep-Hex), Rule-based Balancing Degree (RBD), Energy Equivalent Cluster Formation and Validation (E2CFV), Quality Aware Assessment Model (QA2M), Multi-Objective Spider Monkey Optimization (MOsMO)Abstract
Internet of Things (IoT) applications are made possible by wireless sensor networks (WSNs), which offer a seamless infrastructure for data collecting. The unequal energy usage and associated communication bottlenecks in large-scale IoT deployments, however, make efficient data routing and sink relocation difficult tasks. Our goalistoenhance network lifetime by minimizing energy efficiency. Many static sensor nodes form our network, along with a single mobile sink node. The proposed work includes 4 consecutive processes such as balanced clustered formation, Intra- cluster routing, inter-cluster routing, and Intelligent sink relocation. Firstly, we construct a network as Angle Separated Hexagon (ASep-Hex)divided by 6 parts by angle. A new Energy Equivalent Cluster Formation and Validation (E2CFV) method forms clusters in each sector and CH is selected by Fused Parameter (FuP). We introduce a novel approach namely Rule-based Balancing Degree (RBD) for validating formed clusters. Secondly, for intra-cluster routing, each cluster is a Hop-to-Hop Directed Acyclic Graph (H2H-DAG). Each node chooses the optimal parent for the CH based on Composite Criteria (Com-Criteria) after completion.Thirdly, the available best routes are learned from Tri-state Markov Chain Model (Tri-MCM). Then the generated routes are assessed by Quality Aware Assessment Model (QA2M). Fourthly, to identify candidate positions, a novel Intelligent Triangulation Method (ITM) is proposed. From the candidate positions, the optimal position is selected by Multi-Objective Spider Monkey Optimization (MOsMO) algorithm. The simulation, which uses the Network Simulator (NS-3.26), shows that the suggested work performs more than previous cutting-edge works.
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