Global Engineers & Technologists Review

1.0 INTRODUCTION Advancement in technologies such as sensing, electronics and computing have attracted tremendous research interest in the field of wireless sensors network (WSNs). Apart from their enormous potential for both the commercial and military applications wireless sensors network is generally consist of large number of low cost, low power multifunctional energy constrained sensors nodes with limited computational and communication capabilities. WSNs are the collection of autonomous sensing devices that can be deployed in to physical environment like hospitals, forest, highways, etc to cooperatively monitor the region. Any wireless sensors robot network (WSRN) consist of an ensemble of sensors and robot nodes that communicate via wireless links to perform distributed and actuation task. While sensors are highly constrained devices (i.e, they posses limited computing power, battery, memory, transmission range etc). Robots are resource-rich usually mobile and meant to assist, maintain and optimize sensors network, for example, they may perform intelligent movement for the data collection or sensors placement. In this paper we are dealing with an optimization problem by using the meta heuristic approach in which the demand of delivery customer can be met by a relatively large number of pickup customers. In this situation it is not necessary to visit all the delivery spots, only demanded locations will be included in the tour so as to minimize its cost. This problem is similar to the prize distribution and pickup and delivery problem. As an application we are taking the coverage repair problem in wireless sensors robot network already deployed in some area of interest. Since the therefore in order to save the energy and prolonging the network life time and due to the sensors have limited battery lifetime therefore not all of the sensors are actually needed to provide reliable area coverage. Thus sensors may follow a scheduling algorithm in which some will go to sleep mode (passive sensors) and some will be responsible for monitoring the region (active sensors). In addition due to the failure of any active node the total network coverage can be collapse, thus a single mobile robot with a limited cargo capacity is required locate to the damage sensors for their replacement. This task is to be repeated so often, and the network coverage has to be repair by replacing all the damage sensors with a spare ones. By optimal tour we mean the shortest trajectory or the minimum distance among the nodes of wireless sensors network. To solve the problem, the meta heuristic genetic algorithm GA are introduced. Genetic algorithm is the branch of the evolutionary algorithm that is the change over a long period of time. This approach is very useful in solving most of the networking problem. As far as the significance of GA is concern it is most helpful tool for solving different kinds of optimizing problem regarding to wireless sensors network. For example GA is helpful to achieve the optimum in band width in wireless networking by investigating the channel allocation for radio transmission over wireless network (Pradeep et al., 2012). GA based multi-objective methodology can be implemented for self-organizing wireless sensor network for transmission signal strength (Amol et al., 2009). ABSTRACT