International Conference on Computing, Communication and Automation (ICCCA2016) ISBN:978-1-5090-1666-2/16/$31.00 ©2016 IEEE 383 Hybrid Genetic Algorithm based Technique to Maximize the Network Lifetime in WSN Vinay Kumar Singh 1 , Vidushi Sharma 2 , Anil Kumar Sagar 3 1 Department of Computer Science & Engineering and Information Technology, Anand Engineering College, Agra, India vksingh100@rediffmail.com 2 School of Information & Communication Technology, Gautam Buddha University, Greater Noida, India vidushi@gbu.ac.in 3 Galgotias University, Greater Noida aksagar22@gmail.com Abstract --Wireless sensor networks have sensor nodes that communicate with each other for transmitting the data and thus consume its most of the energy during this transmission. They are battery exhaustive and the battery life is limited. There is need to minimize this energy consumption and as a result extend the overall network lifetime. A novel approach is proposed in this paper that makes use a hybrid combination of simulated annealing and genetic algorithms calculate the energy efficient optimal routing and as a result the network survives for longer period. In the objective function of the routing search, the technique calculates the minimum distance and also considering the remaining energy of the nodes between the source and sink. The simulation results show the improved network lifetime and better utilization of the residual energy. Keywords--wireless sensor network; network lifetime; energy efficient; genetic algorithm, simulated annealing, residual energy I. INTRODUCTION A Wireless Sensor Network (WSN) consists of a number of sensor nodes that are deployed randomly or manually. The main function of theses sensor nodes is to continuously monitor the target area. Whenever some activity takes place in the target area, the sensor nodes in the nearby surroundings capture the event data and try to send it to the sink via the most optimal energy efficient route. This energy efficient route can be minimum distance route between the source and sink, or it could be a route having minimum hops. In some cases the selection of next node in the routing may be based upon the shortest distance towards the sink. These sensor nodes are very small in size and inexpensive. They are autonomous in the sense that they make use of the battery power provided within it and no external power supply is used and once the battery power is exhausted they are disposed off as there is no provision for battery change or recharge. These sensor nodes are spread in random manner in a wide area which is to be monitored for the purpose of remote operations. The sensor nodes have limited power, constrained storage capacity, limited computing capability and bandwidth [1-4]. The routing protocols used in WSN mainly focus on reducing the power consumption so that the overall network lifetime is extended. The industry now-a- days is paying attention to manufacturing sensor nodes that consume less power, having low cost and that can perform multiple functions. The functions of the sensor nodes are to sense that data, collect / gather the data and data processing, and communicating with the other sensor nodes in the network using the radio frequency (RF) network. The sensor nodes have a wide variety of applications ranging from military, healthcare, civil to environmental [4]. II. LITERETURE REVIEW The researchers are now-a-days aiming at developing routing protocols for WSN that consume very little amount of energy. If the energy consumption is reduced significantly this will result in extended network lifetime and thus the overall cost of implementation of the network can be reduced. A number of researchers have done research in energy efficient routing for WSN, a summary of which if discussed with results in [5, 6]. The routing design for WSN should focus on reducing the energy consumption, it could be because of compressing the data before transmission so that less amount of data is sent and thus less energy is consumed. Data aggregation is another approach in which if multiple sensor nodes are sending the same data to an intermediate node then it should not forward all the packets but forward the same packet only once. An energy efficient protocol that uses data centric approach and also discusses the performance analysis of these routing protocols is done in [7]. There are many techniques suggested for routing in WSN geographical routing and topological routing. In geographical routing is the position based routing in which the next node is selected based on the shortest distance or maximum residual energy. In topological routing the path is calculated at the sink and then communicated to all the nodes. Research has shown considerable improvement in the search for the energy efficient optimal routing for WSN by using evolutionary algorithms [8]. In one of the approaches the average path length is minimized to reduce the power consumption [9] in which a wireless network of transceiver nodes is considered and the spatial distribution of the nodes is known beforehand and they use genetic algorithm optimization method. The sensor nodes in the network consists of a transceiver antenna ( a transmitter and a receiver). The task of the algorithm is to minimize the overall average length of the path towards the sink and also reduce the power consumption during transmission. Multipath routing is also used as an alternative in routing schemes for WSN whereby multiple paths are selected for routing alternatively so that the residual power of the nodes can be effectively utilized. Multipath routing also enhances the reliability of the routing and can be used for routing the data in unreliable environments. In this type of routing multiple