Abstract
Wireless Sensor Network (WSN) plays an important role in digital era due to its applicability in a wide range of applications such as military, smart city, healthcare, etc. Since the nodes in WSN experience power constraints and function via wireless connections, network survivability becomes a major design issue. Energy efficiency and secure data transmission are the most important solutions to be accomplished to enhance WSN survivability. The recent phenomena like Artificial Intelligence (AI) and metaheuristics can be involved in designing effective routing protocols. With this motivation, the current research paper presents a novel Trust Aware Oppositional Sine Cosine-based Multihop Routing (TAOSC-MHR) protocol to improve the survivability of WSNs. The major goal of the proposed TAOSC-MHR protocol is to increase the network's survivability by assuring trust and energy efficiency. Primarily, a weighted clustering scheme is applied to partition the network into clusters after which the Cluster Heads (CHs) are selected. Besides, TAOSC-MHR protocol involves an optimal route selection technique i.e., Oppositional Based Learning (OBL) concept with Sine Cosine Optimization (SCO) algorithm. In order to derive the optimal routes in WSN, the proposed TAOSC-MHR protocol derives an objective function with the inclusion of three parameters namely, residual energy, distance, and trust level of nodes. The design of trust aware routing protocol using OBL with SCO algorithm demonstrates the novelty of the study. A wide range of simulation analyses was conducted under different network scenarios and the obtained results signify the promising performance of the proposed technique over other techniques.