A modified gray wolf‐based chameleon swarm algorithm for minimizing energy consumption and enabling secure communication in wireless sensor network. (31st August 2022)

• Record Type: Journal Article
• Authors: Anitha, S.; Saravanan, S.; Chandrasekar, A.
• Is Part Of: Concurrency and computation. Volume 34:Number 26(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-08-31
• Subjects: chameleon swarm algorithm -- improved gray wolf optimizer -- lightweight encryption model and secure key management -- wireless sensor network; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.7295
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: The efficiency and security of WSNs are improved by designing multiple lightweight cryptographic techniques and a 6LoWPAN protocol, depending on resource utilization and a reasonable amount of energy. This is still caused by constraints such as power resource management, authentication, key management, and flexibility protocols. To address these challenges, a novel approach called the modified gray wolf‐based chameleon swarm (MGW‐CS) algorithm is presented to select the cluster heads from WSN nodes. The MGW‐CS algorithm is an amalgamation of both improved gray wolf optimizer and chameleon swarm algorithm. During cluster head selection, the QoS parameters such as network lifetime, energy efficiency, and throughput and packet delivery ratio are improved and optimized. By presenting a lightweight and flexible cryptographic model to manage encryption complexities, the encryption parameters are automatically selected based on the currently available resources of each sensor node for data encryption. Among various WSN nodes, data exchanging and secure communication are established with the development of novel authentication and a lightweight key management model. The proposed model is implemented using the NS‐2 software. The proposed methodology offers a packet delivery rate of 98.6% for a total of 500 nodes when compared to the different state‐of‐art techniques.