International Journal on Future Revolution in Computer Science & Communication Engineering ISSN: 2454-4248 Volume: 4 Issue: 3 343 – 347 _______________________________________________________________________________________________ 343 IJFRCSCE | March 2018, Available @ http://www.ijfrcsce.org _______________________________________________________________________________________ Energy Aware Ant Colony Optimization (ENAANT) to Enhance Throughput in Mobile Ad hoc Networks M. Syed Khaja Mohideen Information Technology Department Salalah College of Technology Salalah, Sultanate of Oman sd_khaja@yahoo.com P. Calduwel Newton Department of Computer Science Government Arts College Kulithalai, Tamilnadu, India calduwel@gmail.com Abstract— Mobile Ad hoc Network (MANET) is a network of mobile nodes having communication without a predefined infrastructure. The applications of MANETs are increasing from home appliances to defense communications. As the mobile nodes are operated by the batteries, all the processes which are taking place in the node should aware of the consumed energy. Maintaining the link stability is one of the challenges and it is one of the factors to ensure the high throughput in the networks. Due to the limited energy, the links of the networks often goes off which affects the throughput of MANETs. Energy aware ACO is proposed to optimize the utilization of energy that is available in the mobile nodes to increase throughput by ensuring link stability. Based on the remaining energy and the amount of packets to be sent, the nodes are selected for routing. The simulation is done through Network Simulator 2 and the results show that the proposed research work performs well in increasing the throughput. Keywords-energy, manet, throughput, ant colony __________________________________________________*****_________________________________________________ I. INTRODUCTION MANET has become a popular and most attracting concept for researchers and various industries because of the wide range of applications. Some applications of MANET technology could include industrial and commercial applications involving cooperative mobile data exchange [1]. MANETs have several salient characteristics like dynamic topology, Bandwidth- constrained, variable capacity links, energy-constrained operation and limited physical security. Mobile devices of MANET can move in any direction independently and the devices can change the location at any time which causes changes in the topology. Each device should have the capability of routing because there is neither a centralized administration nor a predefined infrastructure. The characteristic of dynamic topology makes the communication more difficult because providing quality of service (QoS) became a challenging one. One of the parameters of QoS is throughput which makes the communication more efficient. In any network, the throughput is defined as the rate of successful delivery of message. The motivation behind the Ant Colony Optimization (ACO) is the foraging behavior of real ant colonies. This is exploited in artificial ant colonies for the search of optimal solutions to discrete optimization problems, to continuous optimization problems, and to optimize the communications in telecommunications, such as routing and load balancing. At the core of this behavior is the indirect communication between the ants by means of chemical pheromone trails, which enables them to find short paths between their nest and food sources [2]. The amount of pheromone is the guidance for the other ants. This research work is also inspired by this ACO and the ants are the control packets to be used for finding the paths between the intended mobile nodes. Ants are small control packets, which have the task to find a path towards their destination and gather information about it. Like ants in nature, artificial ants follow and drop pheromone. This pheromone takes the form of routing tables maintained locally by all the nodes of the network. They indicate the relative quality of different routes from the current node towards possible destination nodes. Ants normally take probabilistic routing decisions based on these pheromone tables, giving a positive bias to routes of higher pheromone intensity, to balance exploration and exploitation of routing information. Since the mobile nodes are equipped with limited energy the routing protocols and algorithms should consider the energy of the mobile devices. The efficiency of the routing protocols is not only to provide a better path between the mobile nodes, but also to utilize the energy of the node in an optimized manner. The energy consumption of a node includes the overall energy, energy consumed per layer, energy consumed for different operation modes, energy consumed for MAC and routing overhead and energy consumed for each packet. Even when a node is in idle mode, the energy is consumed for listening to the channel. In MANET energy consumption is calculated based on a mobile device operations, which can be classified into four different modes: transmit, receive, idle and sleep mode [3][4][5]. The average power consumed by a network interface is calculated by adding power consumed in all four modes such as sleep, idle, receive, and transmit. The routing protocols proposed for MANETs are generally categorized as table-driven and on-demand driven, based on the timing of when the routes are updated. With table-driven routing protocols, each node attempts to maintain consistent, up-to-date routing information to every other node in the network. Thus, it is proactive in the sense that when a packet needs to be forwarded, the route is already known and can be immediately used. In on-demand driven routing, routes are discovered only when a source node desires them and there are two major procedures such as route discovery and route maintenance [11]. MANETs face challenges during communication because of the factors like dynamic topology and limited energy. Due to the dynamic topology and limited energy, link stability became another big challenge. Ensuring good throughput in MANET is also affected by this reason. This research paper concentrates on enhancing the throughput through ACO and energy aware