Chaotic Pigeon Inspired Optimization Technique for Clustered Wireless Sensor Networks
Source abstract
Abstract
Wireless Sensor Networks (WSN) interlink numerous Sensor Nodes (SN) to support Internet of Things (loT) services. But the data gathered from SNs can be divulged, tempered, and forged. Conventional WSN data processes manage the data in a centralized format at terminal gadgets. These devices are prone to attacks and the security of systems can get compromised. Blockchain is a distributed and decentralized technique that has the ability to handle security issues in WSN. The security issues include transactions that may be copied and spread across numerous nodes in a peer-peer network system. This breaches the mutual trust and allows data immutability which in turn permits the network to go on. At some instances, few nodes die or get compromised due to heavy power utilization. The current article develops an Energy Aware Chaotic Pigeon Inspired Optimization based Clustering scheme for Blockchain assisted WSN technique abbreviated as EACPIO-CB technique. The primary objective of the proposed EACPIO-CB model is to proficiently group the sensor nodes into clusters and exploit Blockchain (BC) for inter-cluster communication in the network. To select Cluster Heads (CHs) and organize the clusters, the presented EACPIO-CB model designs a fitness function that involves distinct input parameters. Further, BC technology enables the communication between one CH and the other and with the Base Station (BS) in the network. The authors conducted comprehensive set of simulations and the outcomes were investigated under different aspects. The simulation results confirmed the better performance of EACPIO-CB method over recent methodologies.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: IoT and Edge/Fog Computing · Energy Efficient Wireless Sensor Networks · Security in Wireless Sensor Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (21)
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