Intelligent Chimp Metaheuristics Optimization with Data Encryption Protocol for WSN

Abstract

Recent developments in low power electronic devices integrated into wireless communication technologies resulted in the domain of wireless sensor networks (WSN), which finds in applications in diverse data gathering and tracking applications. Since WSN is mostly deployed in harsh and inaccessible environments, it is necessary to design energy efficient and security solutions. The clustering technique is an effective way to lengthen the lifetime of WSN. But most of the clustering techniques elect cluster heads (CHs) irrespective of clusters. To resolve this issue, this paper presents a new intelligent metaheuristics based energy aware clustering with data encryption protocol (IMEAC-DEP) for WSN. The goal of the IMEAC-DEP technique is to elect an appropriate set of CHs and CHs to encrypt the data prior to intercluster communication. The proposed IMEAC-DEP model involves two major phases namely clustering and data encryption. At the first stage, a new chimp optimization algorithm based clustering (COA-C) technique is derived with four fitness parameters. Next, in the second stage, signcryption with artificial fish swarm optimization algorithm (SC-AFSA) based data encryption technique is derived. In order to validate the performance of the proposed IMEAC-DEP model, a series of experiments were performed and the results are investigated under different aspects. The resultant experimental values highlighted the superior performance of the IMEAC-DEP model over the recent stage of art methods interms of energy efficiency as well as security.

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