Maximizing Throughput in Wireless Multimedia Sensor Network using Soft Computing Techniques

Wireless Multimedia Sensor Networks (WMSN) provides valuable information for scalar data, images, audio, and video processing in monitoring surveillance applications. streaming, however, is highly challenging networks as energy restriction sensor nodes limit the potential data transmission bandwidth lead to reduced throughput. WMSN’s two key design challenges, which can be achieved by clustering process, are efficiency throughput maximization. The use of technique helps organise into clusters, between each cluster a head (CH) will chosen. This paper introduces new Artificial Fish Swarm Optimization Algorithm (AFSA) with Clustering Technique Throughput Maximization WMSN, called AFSA-HC, based on Hill Climbing (HC). proposed AFSA-HC algorithm includes four processes optimise network throughput, namely node initialization, aggregation deflate algorithm, hybrid data. To check adequate performance presented technique, thorough experimental review carried out. results simulation showed that approach optimum various steps, consumption, life, stability packet loss.