An Energy Efficient Cross Layer Design for Wireless Sensor Network Prathibha M J National Institute of Engineering, Mysore, India Kiran B N National Institute of Engineering, Mysore, India mjprathibha@gmail.com kiranbn@gmail.com Abstract- Wireless Sensor Network (WSN) is an inter connected collection of sensor nodes used for sensing. Energy optimization is a major issue in Wireless Sensor Network (WSN). WSN nodes operate on batteries due to this WSN has a limited lifetime. In this paper, a cross layer design using EEDSR and S-MAC is proposed which helps to achieve the efficiency in terms of increased network life time. It is compared with DSR and MAC, DSR and S-MAC and the results are analyzed. NS-2 is used for simulation. protocols Dynamic Source Routing protocol realized to be promising one. A significant design challenge is presented by Routing to meet the various design challenges to cater the real time application requirements in wireless sensor networks (WSNs) communication. In this paper, we design a modified Dynamic Source Routing protocol, termed as Energy Aware DSR EEDSR and cross link it with S-MAC which aims to consumes very less energy to provide enhanced quality of Service for delay applications in Wireless Sensor Networks. This method leads to significant power saving and long lasting routes. It maintains the existing performance of DSR and adds to it the power awareness to increase the network lifetime. The most significant benefit by adding energy awareness is that it avoids, for a long time, partitioning of network into non-communicating disjoint sets. The paper aims at discovering a power efficient cross layer scheme for ad hoc network with less or no mobility. Simulation result shows that the proposed cross layer scheme outperforms other schemes used for communication in terms of different energy related parameters. At the time of route selection, EEDSR takes consideration of battery status of the path while also giving importance to delay. With this main factor in consideration, EEDSR always selects less congested and more stable route for data delivery. In this paper, an attempt has been made to evaluate the performance of cross layer scheme using some simulation network models, to investigate how well this performs on WSNs using NS-2 simulator. Index terms: WSN, Cross layer, DSR, Energy aware routing. I. INTRODUCTION The specialized category of sensor networks is increasingly deployed to monitor the physical environments in variety of delay sensitive applications such as military applications, agriculture, medical transport, industry etc. The monitoring applications involves sensing of information during emergency state from the physical environment where the network of sensor is deployed. During critical conditions like explosions, fire and leaking of toxic gases, there is a need of system which should be fast enough and must respond within a fraction of seconds. These leads to a big challenge for researchers to develop a fast, reliable and fault tolerant channeled sensor networks during emergency and critical conditions to base station that receives the events [1].Wireless Sensor Network (WSN) [2] is a special category of Ad hoc Network that may be used for a specific targeted application. Wireless Sensor Networks mainly consists of thousands of low cost, small size and battery powered sensor nodes which has more potentials than other Ad hoc networks to be deployed in many emerging areas. It is necessary to modify the existing DSR and to cross link it with S-MAC to meet the criteria such as robust, energy efficient, minimum delay in routing the packets in WSN[3]. Out of so many routing II. LITERATURE REVIEW & RELATED WORK Many research efforts in the recent years have focused on developing efficient scheme for energy optimization. [5] uses S-MAC with routing protocols such as DSR,AODV,DSDV, and OLSR for comparison and shows that S-MAC when used with OLSR consumes less power, increased network life time and survivability. In [6] a dynamic S-MAC that adapts dynamically to the network-traffic state is proposed. The dynamic S-MAC protocol improves the energy consumption of S-MAC by changing the frame length according to the network-traffic state. Using the NS-2 Simulator the performance of dynamic S-MAC is compared with that of the SMAC protocol and showed an improvement in terms of energy efficiency. [7] discusses about DSR routing protocol which has provided the basic for any energy efficient routing protocols where by modifying its structure of control packet and considering some new energy matrices, power consumption can be reduced. 3. along the link Y-> X, they are still sent, to avoid destabilizing the network. If one of the neighbors Y receives a packet to be forwarded, containing in its path, the link Y-> X, Y will attempt to save (salvage) the packet, or will generate a Route Error to be sent in broadcast, so that it reaches the source of this packet, which will attempt to re-send the package using a different path, not containing the link Y-> X. If the source cannot find other paths in its Route Cache, and on sending of a Route Request, if it appears that the node X is still active, and it appears to be the only "bridge" node to a certain destination, it will be still used to forward packets.[8] III. FEATURES OF EADSR The DSR protocol is composed of two mechanisms that work together to allow the discovery and maintenance of source routes in the ad hoc network. A Modifications to route discovery phase When a node receives a Route Request (RREQ) which is not a final destination, before forwarding RREQ packets to neighboring nodes, it waits for a pseudo random amount of time interval. This time interval is inversely proportional to the level of residual energy of the node in that moment. RREQ wil be sent through the best route from the point of view of "overall" energy. The path is chosen by computing the sum of the energy levels through all the possible paths and selecting the one which has got maximum energy level from source to destination. B Modifications to route maintenance phase Following modifications are done to original DSR 1. When the energy of an intermediate node X, forwarding data within a multi-hop path reaches a level less than or equal to a certain threshold of the initial energy, the node X sends a special broadcast packet to its neighbors Y, containing a flag in the header "low energy" set to 1, with which it implies asks not to continue to forward packets to it, if there are other paths to the destination node. 2. Each neighbor Y which receives the broadcast packet of "low energy", it eliminates the paths containing the link Y-> X from its Route Cache , which is considered to be "virtually" dead (although in fact it is still working, not having X completely exhausted of its energy). If there are packets that have yet to be forwarded IV. FEATURES OF S-MAC A Periodic Listen and Sleep In many sensor network applications, nodes will be in idle state for a long period of time if no sensing event happens. The nodes need not to keep listening all the time even though if no transmission is there. S-MAC reduces the listen time by allowing nodes to go into periodic sleep mode. For example, if in each second a node sleeps for half second and listens for the other half, its duty cycle is reduced to 50%. So we can achieve close to 50% energy savings. B Collision Avoidance Multiple senders may want to send the data to a receiver at the same time, then they need to contend for the medium to avoid collisions. For this a RTS/CTS exchange mechanism is used to address the hidden terminal problem [4].Unicast packets follow the sequence of RTS/CTS/DATA/ACK between the sender and the receiver. There is a duration field in each transmitted packet which indicates the remaining transmission time. So if a node receives a packet destined to another node, it knows how long it has to wait befor the next attempt and hence defers from sending. C Overhearing Avoidance S-MAC tries to avoid overhearing by allowing interfering nodes go to sleep after they hear the RTS or CTS packet. Since the DATA packet is normally much longer than the control packets, the approach prevent the neighboring nodes from overhearing the long DATA packet and the following ACK. D Message Passing The message is fragmented into many independent small packets. Entire message uses only one RTS/CTS exchange. Every time a data fragment is transmitted, the sender waits for an ACK from the receiver. If it fails to receive the ACK, it will extend the reserved transmission time for one more fragment, and re-transmit the current fragment immediately. V. RESULTS AND DISCUSSIONS Fig 1.3 shows plot of residual energy versus time for DSR, DSR SMAC and EEDSR SMAC protocols Fig 1.1 Scenario showing the commincation pattern Fig 1.4 shows Residual energy levels at a node at the end of 200sec. Fig 1.2 Scenario showing thw communication pattern Fig 1.5 shows Residual energy levels at a node at the end of 350 sec The residual energy level of 15 nodes in network for three protocols DSR, DSR-SMAC and EEDSR SMAC protocols is plotted using various graphs. The values of residual energy for individual nodes are obtained from trace files generated by simulation. The histogram results and pie chart of the same are shown in figures. From the different histogram plots and pie chart plots it is found that EEDSR SMAC protocol proves to be comparatively energy efficient than DSRSMAC protocol and DSR protocol. VI CONCLUSION This paper proposes a scheme which improves the energy efficiency significantly. Comparision is done among DSR and MAC, DSR and S-MAC and EEDSR and S-MAC. The results shows that EEDSR and S=MAC provides higher energy efficiency and improved network life time.. REFERENCES [1] Á. Lédeczi, A. Nádas, P. Völgyesi, G. Balogh, B. Kusy, J. Sallai, G. Pap, S. Dóra, K. Molnár, M. Maróti and G Simon, “Countersniper System for Urban Warfare,” ACM Transactions on Sensor Networks, Vol. No. 2, 2005. [2] T. He, S. Krishnamurthy, J. A. Stankovic, T. Abdelzaher, L. Luo, R. Stoleru, T. Yan, L. Gu, G. Zhou, J. Hui and B. Krogh, “VigilNet: An Integrated Sensor Network System for Energy- Efficient Surveillance,” ACM Transactions on Sensor Networks, Vol. 2, No. 1, 2006. [3] Mourtaji, I., et al. 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