Optimum Path Connectivity and Coverage in WSN to Increase Network Lifetime: A Review

Abstract

As we all know, this age has become the age full of many different technologies which are helping each and every personality in their daily routine directly or indirectly. One of these technologies wireless sensor network has emerged in many areas and has gained a large popularity because of its great capabilities and functionalities. Wireless sensor network shortly named as WSN, is a network made by grouping some or many sensor nodes, technically known as motes, which are able to make communication with each other within the network range for performing many different tasks when needed and colleting the necessary information for achieving the purposed goal of that network and then forward that complete information to the base station of that network, technically called sink. In recent years WSN has made its presence in most of the areas for example military applications, medical applications and industrial areas. As WSN is being widely used but there is still many problems are present in WSN. Some problems of WSN are maximum target coverage problem, most energy efficient network and fault tolerant network. For effective communication it is necessary to cover most of the targets and also use optimum path to connect nodes so that network lifetime could be increased. Main concern of target coverage problem is the random deployment of the sensor network for supervising the specific targets for rising the life span of the network it also dictates that how much efficiently the monitoring and sensor tracking of any sensor network works.. To increase the lifetime of the network an optimal node deployment scheme is required that would minimize the cost of the network, reduce the energy consumption and resilient to node. In this paper we have proposed a system that can be used to solve all these issues after reviewing some previous researches in this field. In this work we will use a hybrid approach of merging some important algorithms and approaches to design a system that can solve these issues. Our system will work in two phases: First, Genetic Algorithm (GA) is applied to achieve optimum result and second, Support Vector Machine (SVM) is used to achieve a fault tolerant energy efficient network. SVM is used to detect intrusions like black hole attack and selective forwarding attack. In our approach both the phases will work in parallel for generating most efficient optimum path.