QoS and QoE Enhanced Resource Allocation for Wireless Video Sensor Networks Using Hybrid Optimization Algorithm

Resource allocation has posed a challenging of scarce resources to activities over time. Problems of optimal resource allocation are motivated by questions that arise in project scheduling, production planning, computer control, broadcasting, routing data, maintenance scheduling, and etc. Data transmission in environmental, security, and health monitoring requires both quality of service (QoS) and quality of equipment (QoE) aware network in order to ensure efficient usage of the resources and effective access. In this paper, we propose a resource allocation scheme for wireless video sensor network using hybrid optimization (RAS-HO) algorithm. Firstly, the cluster formation is performed by the modified animal migration optimization algorithm, which enhances the energy consumption. Secondly, an efficient resource allocation is performed by a glowworm swarm optimization based decision making algorithm. Simulation results show that the proposed scheme achieves required resources better than existing schemes in terms of QoS metrics are energy efficient, delay fairness, throughput, and QoE metrics are peak signal to noise ratio, structural similarity.