An Efficient Model of Content‐Aware Routing and Caching in WSN Using Heuristic Approach–Aided Multiobjective Derivation With Optimized Path

ABSTRACT

A particularly critical and contentious issue in WSNs is energy conservation, as sensors expend its energy across various functions including communication, mobility, clustering, computation, localization, and administration. The primary sources of energy consumption at the sensor node level are categorized into the following three main activities: sensing by the sensor module, processing by the CPU, and transmitting data via the radio link. Intensive sensing activities, demanding computational processes and frequent data transmissions not only deplete the network's lifespan but also compromise the availability of resources for additional tasks. This paper addresses the pivotal challenge of maximizing the lifetime and energy efficiency of WSNs through the deployment of intelligent, content‐aware routing and caching algorithms. The proposed solution emphasizes a cluster‐based framework for data transmission and processing, aiming to optimize energy utilization across the network. To achieve this, the novel Hybrid Position of Sailfish and Whale Optimization (HPSWO) is engaged to generate the shortest paths. In order to further analyze the effectiveness of routing and caching, constraints like link utilization, traffic demand, hop counts, average cache size, and accumulated link quality are considered for deriving the multiobjective function. At last, the overall routing process of the developed framework is evaluated using various performance metrics to demonstrate its better efficiency.