Content-Aware Routing Algorithms in WSN for Energy-Efficient Content Delivery Through Clustering With Hybridized Optimization Aided Shortest Path Selection

Wireless sensor networks (WSNs) are primarily used for transferring data and in multimedia applications in the last few years. Improving and refining the routing protocol is required to satisfy user demand in multimedia content delivery with better performance. WSN is composed of small sensing devices that are used for efficient communication. Due to the lack of resources, the handling of WSNs is regularly problematic. The most important objective of WSNs is to improve energy efficiency. The sensors consume more energy for a variety of tasks, including communication, routing, clustering, localization, on-board computations, maintenance, and so on. Nevertheless, there are three primary categories of energy consumption at the node level: radio link relationships, microprocessor evaluation, and sensing via sensing modules. The life span and resource availability of the WSN are greatly reduced by frequent communication and over-cost processing in the WSN. Hence, a content-aware routing algorithm in WSN is implemented in this work to make energy-efficient content delivery through clustering. The host-based communication challenges are solved by using an optimal path-selection-based clustering approach. Initially, clustering is employed to handle energy efficiency and lifetime in WSN. Further, the shortest path selection is done via the hybridized optimization approach, where the Hybridization of Kookaburra with Gold Rush Optimizer (HK-GRO) attains the optimal solution. The energy-efficient content-based routing is performed based on objective constraints like hop counts, link utilization, average cache size, traffic demand, accumulated link quality, energy consumption, and distance between sources to destination for improving routing performance. The efficiency of the proposed clustering-based content-aware energy-efficient routing is validated with the conventional models using some performance measures.