Secured energy efficient transmission for maximizing endurance in wirel ess visual sensor network using genetic fuzzy system and reinforcement learning

Abstract

Wireless Visual Sensor Networks (WVSNs) are the advanced generation of Wireless Sensor Networks (WSNs) that makes possible implementation of multimedia based applications, like safety surveillance, home security, military, production plant and remote monitoring where presence of cameras augment the requirements posed by the application environment. WVSNs bring in many research opportunities along with challenges with respect to certain issues such as Field of View (FoV) coverage, occlusion due to presence of any obstacles, larger data processing as multimedia data consumes more resources for transmission in comparison to scalar data. Data reconstruction at the receiver end depends upon collaboration among several connected nodes and Quality of Service (QoS) requirements like Packet Delivery Ratio (PDR), Packet Loss Rate (PLR), resolution, latency, and jitter for multimedia applications need to be even more effective to achieve the desired outcome. Taking into account the constraints, conventional WSN protocols cannot be utilized in WVSNs. Most of the researches in WVSNs are still in the early stage as there are several open issues like sensor coverage, multimedia capturing, processing as well as transmission. The goal is to develop a new WVSN protocol that can handle multimedia processing, facilitate wireless communication, enable distributed processing, and utilize Machine Learning (ML) techniques in the design process to conserve energy resources. The proposed system in this research work is innovative genetic machine learning based Fuzzy Logic (FL) system that would mimic human cognitive actions like observation, learning and comprehending data and gain useful insights from the training data that would help towards arriving at informed decisions in the future. The architectural design is based on Mamdani s FL system. Performance aspects that decide the likelihood of a particular node being selected as access point called as Sojourn Point (SP) are node s residual energy, its centrality, distance between Mobile