Energy Efficient Protocol for Heterogeneous Wireless Sensor Network using Ant Colony Optimization Saburi Parvatkar, Deipali Gore Department of Computer Engineering, PES’s MCOE, Pune University Pune, Maharashtra, India Abstract— Wireless Sensor Network (WSN) is a collection of spatially distributed sensor nodes which are used to monitor environmental conditions. These sensor nodes collects information in analytical form, converts it to digital information with the help of ADC converter and routes the converted information to the sink node either directly or with the help of network of nodes. Since sensor nodes are usually mounted in remote and hostile areas and have limited battery life, optimum energy utilization is vital. Therefore there is a need to limit energy use. The proposed algorithm saves energy consumed during the switching activities of sensor nodes. Conventional scheduling protocols plan the activities of devices in either active state or sleep state. The proposed protocol introduces a new state called Low Power State. If the data packet to be sent is very small, then the energy consumed in switching the nodes from active state to sleep state and vice versa is very high. Low power state keeps nodes in idle mode where in the nodes’ radio will be active but will neither send nor receive anything. The proposed protocol satisfies sensing coverage and network connectivity constraints. Ant Colony Optimization (ACO) is a well known metaheuristic. It helps to find out the maximum number of disjoint connected covers that will satisfy both sensing coverage and network connectivity. Pheromone and heuristic information is used to find the coverage set of active sensors. The search experiences and domain knowledge used in ACO helps to accelerate the search process. Keywords— Ant Colony Optimization (ACO), Energy Efficiency, Pheromone, Time Division Multiple Access (TDMA), Wireless Sensor Network (WSN). I. INTRODUCTION Sensors have become an important part of our life. They are used in every nook and corner. They are indispensable. A Sensor node is made up of microcontroller, battery source, ADC and the sensor. The sensor senses the region which lies within the sensing range of the sensor node. The analog data sensed by the sensor is converted to digital form by the Analog to Digital converter (ADC) and the information is routed to the sink node. The sensor node is powered by battery. These batteries are usually non rechargeable. And even if they are rechargeable, it becomes difficult to recharge them since the sensor nodes are usually deployed in remote and hostile area. The main sources of energy wastage are collision, overhearing, idle listening and over emitting. Collision results into resending of data package. In overhearing the nodes receives packets that are destined for other nodes. In idle listening the nodes listen to the channel to receive possible data traffic whereas over emitting is caused by the transmission of a message when the destination node is not ready. Efficient utilization of Energy is a key design objective in Wireless Sensor Networks. Wireless sensor networks can be either homogeneous or heterogeneous. In homogeneous WSN, nodes are identical in terms of battery energy and hardware complexity. A heterogeneous sensor network consists of two or more types of nodes with different battery power and functionality [1]. A number of methods have been proposed for finding the best way to utilize the energy of the sensor nodes. Some of the methods include scheduling algorithms, Genetic Algorithms, Particle swarm optimization algorithms and ant colony optimization algorithm [2][3]. The main aim of the proposed protocol is to maximize the network lifetime, which can be defined as the period that the network satisfies the application requirements. The outline of the paper is as follows. Section II, covers the literature survey. Section III discusses the proposed approach followed by conclusion. II. LITERATURE SURVEY A. Scheduling Protocols In wireless sensor network, nodes listen to the channel even if no data is placed on the channel, i.e. idle listening. This happens because the nodes do not know when data will be placed on the channel. This issue is solved by TDMA protocols. Scheduling protocols are TDMA protocols. They reduce energy consumption by planning the activities of the devices [6]. Optimization techniques that consider device control approach which includes sleep/wakeup activities are found to be more effective. TDMA protocols have a fixed time slot for transmitting and receiving data. And therefore, every node after receiving and transmitting data goes in sleep mode or active mode and thus saves battery power. TDMA protocols reduce data transmissions because collision does not occur in TDMA protocols. But most of the TDMA protocols either put the nodes to sleep state or active state. Fixed low power modes involve an inherent trade-off. Deep sleep modes have low current draw and high energy cost and latency for switching the nodes to active mode while light sleep modes have quick and inexpensive switching to active mode with a higher current draw [4][5]. Saburi Parvatkar et al, / (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (3) , 2014, 3454-3456 www.ijcsit.com 3454