ENERGY OPTIMIZATION AND THROUGHPUT MAXIMIZATION USING MAC- LAYER DESIGN IN MANET

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1 Journal of Computer Networking, Wireless and Mobile Communications (JCNWMC) ISSN Applied Vol. 3 Issue 2, Jun 2013, TJPRC Pvt. Ltd. ENERGY OPTIMIZATION AND THROUGHPUT MAXIMIZATION USING MAC- LAYER DESIGN IN MANET M. JANARDHANA RAJU 1 & P. SUBBAIAH 2 1 ECE, Sathyabama University, Chennai, Tamil Nadu, India 2 ECE, Bharath College, Andhra Pradesh, India ABSTRACT Adhoc wireless networks are power constrained since nodes operate with limited battery energy. Thus, energy Consumption is crucial in the design of new ad hoc routing protocols. Several techniques proposed to increase the overall throughput using on-demand routing protocol. Overall performance in data transmission reduces the rate of transmission in Mac layer, which affects the throughput in network, By our Mac protocol IEEE , We carry out a MAC analysis that is of particular focus on networks which is deployed to provide k-coverage for real-time applications, to improve the Uplink and downlink Ratio in rated transmission, It is shown that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain. We simulate in ns2 with different topology to define the Mac issues. KEYWORDS: Mobile Adhoc Networks, Link Repair Routing, Energy Optimisation, Throughput Maximization, Distributed Mac Protocols, Mac Issues INTRODUCTION MOBILE ad hoc networks (MANETs) is a special type of wireless network, every node have their individual property which can function individually in the network. Mobile nodes have application in search-and-use [2] the availability with the mobility handling operations. It is an centralized severing network, However, due to the error prone wireless channel and the dynamic network topology, fails to improve the data delivery rate. Even fast changing network topology is very difficult to maintain a stable routing. If such transmission is used as backup, the robustness of the routing protocol can be significantly enhanced. The main objectives of MANET routing protocols is to maximize network throughput, and to optimize maximize energy efficiency, better network lifetime, and to reduce delay [1]. The network throughput is calculated by packet received with time and the energy is by difference between the energy level of overall network, the most significant contribution to energy consumption is measured by routing overhead which is the number or size of routing control packets is small[1]. According to a passion process packets arrive randomly in space. Using full-distributed MAC protocol of either ALOHA or CSMA, the packets are transmitted to their proposed destinations. If the received SINR is above a threshold value within the duration of the packet the SINR based model is considered the packet/users transmission is successful. For the ALOHA or CSMA protocol of MAC the probability of outage bounds developed. This is a function that can be used for transmissions of density. To increase the approaches into the MAC protocol design for ad hoc network and to estimate the performance of the both MAC protocol (ALOHA or CSMA) the accurate bounds are used. The performance of CSMA is improved with receiver sensing of CSMA. A new frame work for MAC protocols is analyzing the performance in stipulations of probability in outage. It provide nearest representation of ad hoc network. These frameworks randomly place the nodes in space and the

2 12 M. Janardhana Raju & P. Subbaiah transmissions are continuous in time. Therefore this will lead to the get a nearby representation to an adhoc network. both with transmitter and with receiver sensing this SINR-based model have the probability of outage for unslotted ALOHA and CSMA. CSMA has a superior probability of back off; hence it is the most effective for higher densities. Compare with ALOHA and CSMA the CSMA performance not as good as ALOHA when the transmitter senses the channel. The CSMA performance is improved much if the receiver senses the channel and informs the transmitter over a control channel whether to transmit or not. The general simulations (the network simulator NS2 [2] is that reactive protocols(aodv protocol), those finding routes on fly by request with when they need in transmission, perform better than proactive routing protocols[2], which maintain the routes for all transmission [4]. If energy model approach is to be considered then, on-demand protocols, where transmission range in network will decide the control packets transfer is limited and the routing inform is frequently updated [4]. On demand protocols flooding the route request packets throughout the network does the route discovery. Our main aim is to make energy efficient routing protocol and to perform link recovery of the routing in the ad hoc network. Transmission range decides the routing way points or hops to reach destination, however it targets to reduce energy consumption between any two neighbouring nodes in the network[5].to reduce the transmission energy no of hops (intermediate node have to be reduced) in routing has to be reduced. The total transmission energy consumed in the network is depend on the reliability of data packet transmitting from one node to its neighbouring node called as the link cost[5]. PROBLEM IDENTIFICATION The main problem in routing is to achieve the maximum throughput is Link break and energy optimisation. Where link break can be repair using route threshold repair mechanism and energy usage will be minimized automatically. We address the other problem, which occurs in data transmission through MAC layer design. The ALOHA and CSMA are the MAC protocols which is used to increase the packet delivery rate In particular, we can analyze the transmission rate by having a fixed threshold on each transmitter (Tx) and receiver (Rx), and using MAC protocol of IEEE , we can improve the performance. IEEE (Low Rate) deals with low data rate but very long battery life (virtual energy) and very simple. Power is derived from external sources in network. Unicast routing is the process of forwarding unicasted traffic from a source to a destination on an internetwork. Unicasted traffic is destined for a unique address. Our related survey on Mac issues are as follows, CSMA/CD (Carrier Sense Multiple Access / Collision Detection) Every node senses the carrier before transmitting. If the carrier is not clear, the node defers transmission for a specified period. Otherwise, transmits [1]. While transmitting, the sender is listening to carrier and sender stops transmitting if collision has been detected. Packet Delay Packet delay results are presented as a function of a number of stations and packet size for basic access and RTS=CTS medium access mechanisms. Packet measurements need to span over a long period of time[1]. Queuing delay introduces a variable component to the point-to-point delays experienced by packets, as it depends on the traffic load along the path, which varies at different links and with time.

3 Energy Optimization and Throughput Maximization Using MAC- Layer Design in MANET 13 PROPOSED APPROACH The Ad-hoc On-demand Distance Vector (AODV) routing protocol [12] is one of the best reactive protocols in MANET and WMN routing protocols. It establishes routes on demand service needed. It discovers a route by broadcasting a Route Request message by the source node that is search for a route to a destination node through intermediate nodes, the destination node replies with a corresponding Route Reply message with in transmission range. During route discovery process, intermediate nodes create routing table updation for both source and destination nodes, thereby creating a bidirectional end-to-end route [12]. IEEE Mac Protocol: It is Fixed Broadband Wireless Access System. A reservation based medium access control (MAC) protocol has been adopted by the IEEE standard as the basic protocol for data communication within the upstream channel. Back-off algorithm with adjustable window size to resolve the collisions of request packets. Main demand is to enable rapid worldwide deployment of cost-effective broadband wireless access products, and to facilitate competition in broadband access by providing alternatives to wireless broadband access. Main advantage of our protocol is fast deployment, dynamic sharing of radio resources and low cost. Multipath is negligible and it acts as our only disadvantage. Uplink / Downlink - Random access area is primarily used for the initial access but also for the signalling when the terminal has no resources allocated within the uplink phase. A standard scheduling algorithm as to be used for analysis of packet distribution. In Mac layer bandwidth allocation will be dynamic or constantly specified above. The distance between two fixed nodes is set to 390 meters, which was selected to be able to setup connections for all single rate MAC protocols. Since the receiving power sensitivity gets higher as the capacity of the modulation increases, we pick a distance smaller and close to the shortest sensitivity range as the simulated distance, which is from 11 Mbps single rate protocol.as the receiving power changed, each RTS/CTS exchange will cause a channel capacity re-negotiation. the CBR throughput of BRAR with single rate MAC protocols, which are 1 Mbps, 2 Mbps, 5.5 Mbps and 11 Mbps. The throughput is the average CBR throughput in 1 second time period. As we expected, the rate-adaptive MAC protocol based on the Receiver-Based Auto-Rate get the highest throughput in a fading channel. However, the 11 Mbps MAC protocol performs poorly than we expected. It could be caused by the distance of 390 meters, which is close to the max sensitivity range of the 11 Mbps MAC protocol and fading may cause greater effects than in other cases. Carrier Sensing Zone When a node is within the carrier sensing zone. Note that, as per our definition here, the carrier sensing zone does not include trans- mission range. Nodes in the transmission range can indeed sense the transmission, but they can also decode it correctly. Therefore, these nodes will not be in the carrier sensing zone as per our definition. The carrier sensing zone is between 250 m and 550 m with the highest power level in our simulation. Figure 1: Nodes in Transmission Range in the Carrier Sensing Zone

4 14 M. Janardhana Raju & P. Subbaiah Power Law Without loss of generality, we assume a common channel model that follows the power law P recv = P tx / r n. Where Precv is the strength (or power) of the signal when it arrives at a receiver, Ptx is the transmission power, r is the transmission range, and n is the power loss exponent that takes a value between 2 and 4. Each node is assigned a default maximum transmission power, Pmax to send REQUEST message. This value is included in the header of the REQUEST message. In order to adjust the transmission power, each node needs to determine the transmission power that it needs to reach each of its neighbors. When a node receives a REQUEST message from a neighbor, it simply extracts the power level with which the packet is transmitted (Pmax) and compute the required transmission power, Preq, to reach this neighbor using the following equation: Preq = P max / P recv X Threshold Eq (1) Where Pthreshold is the minimum power for a packet to be received correctly. Random Broadcast Timer The random broadcast timer (RBT) of node as follows: RBT = [MaxRange distance MaxRange] + [MaxReach unreached MaxReach] rand () MaxDel In the equation above, MaxRange denotes the Maximum transmission range of a node, and MaxReach the maximum number of neighbors that a node can cover. It is expected [5] that the transmission range and number of immediate neighbors of all nodes should not exceed 250 meters and 20 respectively, MaxRange = 250 and MaxReach = 20. MaxRange = 250 is obtained by assuming n = 2 in (1) and Pthreshold = and Pmax = in (2). distance denotes the distance of node s from the message originating node while unreached represents the number of notyet-covered neighbors of node s (as seen by node s). rand () is a random number generator that generates a uniformly distributed number between [0,1] and MaxDel is the pre-determined maximum rebroadcast backoff time. Uniform random distribution of nodes is the assumption of wireless ad hoc networks. Because when using uniform random distribution of nodes it lead to reduce the data loss. The nodes are distributed according to a Poisson point process for achieved in a network throughput. To measure the other point of distributions the baseline performance is used. There is a strong impact on the local throughput where using non-uniform random distribution. The impact on throughput is associated with the network capacity and performance. Therefore it is necessary to take detailed analyses of node topology of ad hoc, sensor, and mesh networks. The spatial distribution of nodes in wireless ad hoc networks has some effects. Therefore as we saw in earlier that using the uniform random distribution decreasing the data loss and using the non-uniform random distribution increase the data loss in the throughput. Dependent optimization problems in different topology of clustered distribution can serve as an interesting class of models. The use of cognitive radios the location information are advocated its topological neighbourhood then it is possible to optimization its scope. EXPERIMENTAL RESULTS Network simulation (NS2) tools helps to simulate the demand on service of energy [2] maximisation by the mechanism of reducing the hops in the data transmission in network which dynamically change the topology. Our

5 Energy Optimization and Throughput Maximization Using MAC- Layer Design in MANET 15 performance is analysed with time taken to reach the destination with the estimated packets and the usage of the energy of individual nodes have been calculated. Figure 2: Comparison of Packet Delivery Ratio Figure 3: Comparison of Delay in Transmission CONCLUSIONS AND FUTURE WORK Routing and power consumption are intrinsically connected. In conventional routing algorithms, which are unaware of energy budget, connections between two nodes are established through the shortest routes. These algorithms may however result in a quick depletion of the battery energy of the nodes along the most heavily used routes in the network.mac protocol solves the in future work we can compare our work with enhanced power optimisation which is having the stable power for extreme transmission and overhead as their complicity. And which randomly increased the performance in the network. We develop an efficient model with dynamic link repair routing, which reduce the dropping ratio in the network. By selecting the shortest hop neighbour through on-demand protocol delay can be minimised to reduce the energy usage in the network, In future by Improving the Mac design in channel selection with scheduling data transmission we can show better quality. REFERENCES 1. Sunsook Jung, Nisar Hundewale, Alex Zelikovsky Energy Efficiency of Load Balancing in MANET Routing Protocols Department of Computer Science, Georgia State Univ., Atlanta, GA, USA in Conf. May C. Perkins, Ed., Ad Hoc Networking. Addison-Wesley, K. Fall and K. Varadhan, The vint project, uc berkeley, lbl, usc/isi, and xerox parc, [Online]. Available: Network Simulation tutorial is refered by

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