Modern Approach to Enhance Routing Recitation in MANET Vishal Kumar Sagtani 1, Sandeep Kumar 2 1 M.Tech Scholar, 2 Asst. Professor & Head, Dept. of Computer Science & Engineering, Jagan Nath University, Jaipur Abstract Mobile Ad hoc network is a collection of self configuring nodes, linked wirelessly for a very short span of time to communicate with each other without any fixed infrastructure, and are free to move arbitrarily. In recent years, with the advent of wireless technology this network has found greatest attraction of researchers, to design an economical and reliable communication service between the mobile nodes but the extremely vibrant nature of such network poses several of challenges into design of an efficient routing protocol. Among several of proposed algorithms, the one traditional protocol has significant popularity in the researchers; use to design an algorithm for such network. However this protocol has suitable for such network but has some exclusive shortcoming that makes it ineffective for the network, such as high overhead. In this context this paper presents a modern approach to improve the recital of in the environment of MANET. The simulation work has been carried out using NS2 and the results clearly demonstrate the significance of proposed approach. Keywords, MANET,, PDR, RREQ I. INTRODUCTION A Mobile Ad Hoc Network (MANET) is a collection of wireless mobile nodes where nodes form an infrastructure less self configuring network for a very short span of time and are free to move arbitrarily [1]. In a MANET all nodes behave like both routers and hosts. In such a highly dynamic environment routing is a very critical task. Routing protocols basically perform three functionalities: route discovery, route maintenance and choosing of an optimal and most efficient path between source and destination. The performance of the routing protocols in a MANET environment is heavily affected by limited network bandwidth, high node mobility and battery power of the mobile nodes. The presence of high mobility implies frequent link failures and each routing protocol reacts differently during link failures. There are various studies and researches in this field in attempt to propose more efficient routing protocols. Most of the researchers concentrate on traditional topology based routing protocols while other concentrate on location based ad hoc routing strategies as described in later sections. During last few years this field has been a great area of interest for the researchers. However, there is no single routing protocol that can perform efficiently in every situation. The existing routing protocols are effective only when the node population is small. This paper presents a fresh approach by optimizing one of the famous routing algorithms to improve the routing performance in the environment of MANET. To present the significance of proposed approach, namely Advance, the simulation results has been compared with traditional algorithm, on the basis of performance metrics throughput, packet delivery ratio, end to end delay and normalized routing load of the network. The rest of the paper is organized as: section 2 gives brief overview of routing protocols for MANET. Related work is described in section 3. Section 4 describes the proposed approach to enhance protocol. Section 5 has the brief description about simulation scenario and performance metrics used for analysis of the selected protocols. Simulation results are shown in section 6 and finally the paper is concluded section 7. II. OVERVIEW OF ROUTING PROTOCOLS FOR MANET Numerous routing protocols have been proposed for the MANET like environment. These approaches can be broadly classified into five categories as depicted in the figure 1 on the basis of application area where they are most suitable: Figure 1 Categorization of Routing Protocols There are several papers [1, 2, 3] which describe various MANET routing protocols. Most of the researchers focus on the Topology Based Routing Protocols which again can be classified into following categories [3]: 265
Figure 2 Classification of Topology Based Routing Protocols Proactive protocols are mostly based on shortest path algorithms and also known as table driven routing protocol because they store the information of all connected nodes in form of tables. Reactive routing protocols were developed to overcome the overhead of proactive routing protocol. The Reactive routing protocols are also called on-demand routing protocol because these protocols establish the route only when it is needed and only for those nodes that are currently being used to send data packets from source to destination. The hybrid routing protocol combines characteristics of both reactive and proactive routing protocols and proposed to reduce the control overhead of proactive routing protocols with decreasing the initial route discovery delay in reactive routing protocols. The DSDV (Destination-Sequenced Distance Vector) routing protocol is developed on the basis of Bellman- Ford algorithm with some modifications. Each node in DSDV maintains a next-hop table, which it exchanges with its neighbours. Each table entry is tagged with a sequence number, which is originated by the destination node. Dynamic Source Routing (DSR) is an Ad Hoc routing protocol which is source-initiated rather than hop-by-hop. In this protocol every node in the networks maintains a route cache in which it stores the complete route to the destination node. This cache is updated periodically as new routes are discovered or the cache is expired due to being idle for long time. The data packet carries the source path in the packet header. The packets are forwarded using the routing information in the packet header instead of using routing tables of intermediate nodes. So the routing overhead is directly affected by the path length between the source and destination node. The broken links in this protocol are not repaired locally by the route maintenance process which is a limitation of this protocol. It has two important phases, route discovery and route maintenance [4, 5]. This paper mainly focuses on the study of protocol and approach to enhance it. A. Ad-Hoc On-Demand Distance Vector () Protocol is an on-demand routing algorithm that establishes a route only when a node wants to send a packet to a destination. It is a variation of Destination- Sequenced Distance-Vector (DSDV) routing protocol which is collectively based on DSDV and DSR and combines the features of both. For each destination node, creates a routing table like DSDV and for route discovery and maintenance uses the mechanism of DSR with significant differences. Unlike carrying entire route information in the data packets in DSR, data packets contain destination address only. It causes more routing overhead in DSR than. For determining a path from source to destination node the source node sends a route request packet to all its neighbours and this process is repeated until the node path is not discovered. protocol uses three types of control messages for routing operation as follows [3]: RREQ: When a route is not available for the desired destination, a route request packet is sent by the source node to all of its neighbouring nodes. RREP: If the node receiving RREQ packet is either the destination node, or has a valid route to the destination, it unicast a route reply message back to the source node. RERR: When a path breaks, the nodes on both sides of the link issue a route error to inform their end nodes of the link break. The sequence number of packet is checked at every intermediate node to produce a loop free path. protocol works in following two phases [1]: Route Discovery: initiates a route discovery process using Route Request (RREQ). The source node creates a RREQ packet which is composed of its IP address, its current sequence number, the destination s IP address, the destination s last sequence number and broadcast ID. The broadcast ID is incremented each time the source node initiates RREQ. This RREQ packet is broadcasted by the source node broadcasts to all of its neighbours. After that the source node sets a timer and waits for a reply. To process the RREQ, the node sets up a reverse route entry for the source node in its routing table. When RREP is routed back along the reverse path and received by an intermediate node, it sets up a forward path entry to the destination in its routing table. When the RREP reaches the source node, it means a route from source to the destination has been established and the source node can begin the data transmission. 266
Route Maintenance: A route is maintained as long as it is needed by the source node. Besides that when there is a link break, the upstream node of the link sends RERR (route error) message to its neighbouring upstream nodes which in turns send the RERR message to their upstream nodes. The process is repeated until the RERR message reached to the source node. When the source node receives the RERR messages it can stop sending data packets and reinitiate the route request mechanism using RREQ messages. The has the advantage of establishing ondemand route in between source and destination node with the lower delay in connection setup and does not require much memory for communication. has the ability of unicast & multicast routing. But there are several disadvantages of this protocol such as if there has multiple route reply packets for a single route request packet, it suffers from Heavy control overhead. It consumes extra bandwidth because of periodic beaconing. As the size of network grows, various performance metrics begin decreasing. is vulnerable to various kinds of attacks as it based on the assumption that all nodes must cooperate and without their cooperation no route can be established. III. RELATED WORK Many of the researchers have carried out simulation based study to evaluate the performance of routing protocol like, DSDV and DSR in MANET environment using different evaluation methods with varying node mobility on the basis of different performance metrics using different simulators. By using CBR traffic three routing protocol, DSR and DSDV analysed on the basis of performance metrics of throughput, average packet latency [6]. The protocol performs better in comparison of DSDV and TORA routing protocol shows in the simulation work results [7]. The performance of, DSDV, DSR, and TORA evaluated at the basis of E2E delay and PDR performance metric. For this work they used Maryland Routing Simulator [8]. The different simulators are also used to perform the analysis of routing protocols [9]. The NCTU ns 4.0 simulator was used to compare the performance of, DSDV and DSR routing protocol and in the same fashion of work MOVE and NS-2 simulator used to analysed performance of, OLSR and DSR routing protocol on basis of PDR and end to end delay [10]. In [11] another technique named as Expanding Ring Search (ERS) this is used to reduce the number of RREQ packets has been proposed. An improved ERS scheme is proposed in [12] named as Energy Efficient Expanding Ring Search Technique (EE). This approach is applied to the route discovery phase and saves energy of the nodes by avoiding the redundant rebroadcasting of the RREQ packets. IV. PROPOSED APPROACH TO ENHANCE The uses the flooding mechanism to find out the path between sources to destination node. This is efficient with small network but as size of network increases it increases the number of control packets, cause network congestion, use of high bandwidth, energy and the huge overhead problem. In this context to improve the performance of traditional routing protocol, an optimize approach has been proposed in this paper that control the flooding process of the protocol. Apart from this the focal point of the proposed algorithm is to reduce the communication path to maintain smooth routing. Figure 3 has depicted the approach overview. Yes Update the information about the path of destination and forward the packet Send RREQ to all neighbor Check valid reply from destination node NO Find link breakage or availability of new optimum path Yes Perform Local route reparing process or select the new optimum path NO Figure 3 Flowchart of the Proposed Approach If repaired Therefore this new approach of reducing active path (Advanced ) will reduce routing overhead as it will use the path with lesser number of hops from the source to destination. There will be several benefits of this approach. It will increase the PDR (packet delivery ratio) and hence the throughput will also be increased. Beside this with lesser end to end delay the nodes are required to become active for lesser amount of time which will result in lesser battery power consumption. Yes 267
V. SIMULATION SCENARIO AND PERFORMANCE METRICS A. Tool and Parameters Used for Simulation There is a wide range of network simulation tools is available in the market some of which are open source and some are proprietary. The most frequently used simulation tools are OPNET, Qualnet, and NS2. OPNET and Qualnet both also best network simulators, but these are not opens source tools and having the more cost of purchasing for such type of educational research work. Hence the NS2 simulator which is completely free and open source tool is a better choice to carry out simulations and researches for all types of networks. There are many versions of NS2 available ranging from NS-2.26 to NS-2.35. In this simulation work to analyse the performance of and Advanced routing protocols the open network simulator NS-2 version 2.32 has been used. Nodes follow a random waypoint mobility model, travelling at a variety of speeds over a 600 x 600 meters area. This simulation is run for 100 seconds of simulated time for varying number of nodes. Same simulation scenario has been used to analyse both the protocols because of unique behaviour of each protocol to compare them. The simulation parameters are briefed in Table 1: TABLE 1 SIMULATION PARAMETERS Throughput: The throughput of the protocols can be defined as percentage of the packets received by the destination among the packets sent by the source. It is the amount of data per time unit that is delivered from one node to another via a communication link. The throughput is measured in bits per second. This metric show the total number of packets that have been successfully delivered to the destination nodes and throughput improves with increasing nodes density. Packet Delivery Ratio (PDR): It is calculated by dividing the number of packets received at the destination node by the total packets sends by the source node. It specifies the packet loss rate, which limits the maximum throughput of the network and the delivery ratio performance. The high packet delivery ratio shows better performance of a protocol. End to End delay: The total time for transmitting a packet from source to the destination node is known as end to end delay. The delay performance metric include the delays due to route discovery, packet propagation and sending time and the time of packet in queue [14]. Normalized Routing Load (): Normalized routing load is the number of routing packets transmitted per data packet sent to the destination. Also each forwarded packet is counted as one transmission. This metric is also highly correlated with the number of route changes occurred in the simulation. Parameter Name Network Simulator Value NS-2, 2.32 version Number of Nodes 10, 20, 30, 50, 75 Network Size 600 x 600 Mobility Model Channel Type Antenna Type Pause Time 1.0s Max Speed Simulation Time Routing Protocol Traffic Type Packet Size B. Performance Metrics Random Way point (RWP) Wireless Channel Omni directional 20 m/s 100 s and CBR 512 bytes/packet There are several performance metrics on the basis of which routing protocols can be evaluated for network simulation [13]. The performance metrics used for simulation purpose are: Throughput, Packet delivery ratio, End to End delay and Normalized Routing Load. VI. SIMULATION RESULTS ANALYSIS AND DISCUSSION The performance of selected routing protocols and Advanced has been analysed for CBR traffic under five different scenarios of 10, 20, 30, 50 and 75 nodes. The result has been measured for performance metrics of packet delivery ratio (PDR), throughput, average end to end delay (E2E Delay) and normalized routing load. The simulation results are shown in the following graphs. 0.800 0.825 0.75535 0.39081 18.050 17.880 Figure 4 10 Nodes Scenario 95.545 92.779 268
Figure 4 shows the comparative analysis of and Advanced for all the performance metrics for 10 nodes scenario. It is clear from the figure that for 10 nodes scenario Advanced protocol produces routing load than. In this scenario gives better results for end to end delay. 5.488 6.671 0.06696 0.03600 94.666 93.421 4.035 4.297 8.870 8.830 0.01630 0.01663 4.690 4.620 Figure 5 20 Nodes Scenario 88.976 88.800 Figure 5 shows the comparative analysis of and Advanced for all the performance metrics for 20 nodes scenario. It is clear from the figure that for 20 nodes scenario Advanced protocol produces better throughput and PDR with lowest end to end delay and normalized routing load than. Figure 7 50 Nodes Scenario Figure 7 shows the comparative analysis of and Advanced for all the performance metrics for 50 nodes scenario. It is clear from the figure that for 50 nodes scenario Advanced protocol produces routing load than. produces higher end to end delay because of it always tries to find a path from source to destination with minimum number of hop counts even if there is a path established already between source and destination and it is being used for sending packets. This process sometimes may add additional delay for the operation of Advanced. In this scenario gives better results for end to end delay. 5.646 6.550 0.02532 0.02672 8.450 8.230 Figure 6 30 Nodes Scenario 90.000 89.252 Figure 6 shows the comparative analysis of and Advanced for all the performance metrics for 30 nodes scenario. It is clear from the figure that for 30 nodes scenario Advanced protocol produces routing load than. 7.963 10.122 0.08061 0.02160 10.890 9.950 Figure 8 75 Nodes Scenario 95.833 90.740 Figure 8 shows the comparative analysis of and Advanced for all the performance metrics for 75 nodes scenario. It is clear from the figure that for 75 nodes scenario Advanced protocol produces routing load than. In this scenario gives better results for end to end delay than Advanced. 269
VII. CONCLUSION The performance evaluation is necessary for analysing the shortcomings of existing approaches and proposing newer ones. In this paper performance of and the proposed approach Advanced has been compared on the basis of various performance metrics with increasing number of nodes in the mobility scenarios with CBR traffic. Finding indicates that from these any single protocol is not suitable for efficient routing in different environment. The simulation results indicate that in all the scenarios Advanced performs better than. Advanced produces better results for throughput, PDR and normalized routing load. Sometime it performed better for end to end delay and sometime not better than. Overall the suggested approach tried to enhance the performance of protocol and produced significant results. As stated above no single protocol can perform better in all the scenarios of MANET, hence there is always a chance of improvement in routing algorithms for MANET. Although Advanced produced better results for throughput, PDR and normalized routing load, yet still there are possibilities to minimize end to end delay. This work can be very useful for the research scholars who are interested to work in this direction. REFERENCES [1] Sunil Taneja, Ashwani Kush, A Survey of Routing Protocols in Mobile Ad Hoc Networks, International Journal of Innovation, Management and Technology, Vol. 1, No. 3, August 2010. [2] Gurpinder Singh, Jaswinder Singh, MANET: Issues and Behavior Analysis of Routing Protocols, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 4, April 2012. [3] Prabhakar Ranjan, Kamal Kant Ahirwar, Comparative Study of VANET and MANET Routing Protocols, Proc. of the International Conference on Advanced Computing and Communication Technologies (ACCT 2011). [4] D. Johnson, B.D.A. Maltz, and Y.C.Hu, The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (DSR), draft-ietfmanet-dsr-10.txt, 2004. [5] C.E.Perkins and E. M. Royer. Ad-Hoc On Demand Distance Vector Routing, Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications (WMCSA), pp. 90-100, 1999. [6] Rajendra V. Boppana, Satyadeva P Konduru, An Adaptive Distance Vector Routing Algorithm for Mobile, Ad Hoc Networks, IEEE INFOCOM,, 2001, pp. 1753-1762. [7] Vetrivelan, N and Reddy, A.V Performance Analysis of Three Routing Protocols for Varying MANET Size Proceedings of the International Multi Conference of Engineers and Computer Scientists 2008, Vol II IMECS 2008, 19-21 March, 2008, Hong Kong. [8] S.R. Das, R. Castaneda, J. Yan, and R. Sengupta, Comparative performance evaluation of routing protocols for mobile ad hoc networks, 7th Int. Conf. on Computer Communications and Networks (IC3N ), October 1998 pp., 153 161. [9] Khaleel Ur Rahman Khan, Rafi U Zaman, A.Venugopal Reddy, Performance Comparison of On-Demand and Table Driven Ad Hoc Routing Protocols using NCTUns, Tenth International Conference on Computer Modeling and Simulation. [10] Pranav Kumar Singh, Kapang Lego, Dr. Themrichon Tuithung, Simulation based Analysis of Ahoy Routing Protocol in Urban and Highway Scenario of VANET, International Journal of Computer Applications, January 2011, (0975 8887) Volume 12 No.10. [11] Ngoc Duy Pham and Hyunseung Choo, (2008) Energy Efficient Ring Search for Route Discovery in MANETS IEEE Communications Society subject matter experts for publication in the ICC proceedings. [12] S.Preethi, B. Ramachandran, (2011) Energy Efficient Routing Protocols for Mobile AdHoc Networks IEEE. [13] Ajay Kumar, Ashwani Kumar Singla Performance evaluation of Manet routing protocols on the basis of tcp traffic pattern International Journal of Information Technology Convergence and Services (IJITCS) Vol.1, No.5, October 2011. [14] S H Manjula, C N Abhilash, Shaila K, K R Venugopal, L M Patnaik, "Performance of Routing Protocol using group and entity Mobility Models in Wireless Sensor Networks," Proceedings of the International Multi Conference of Engineers and Computer Scientists (IMECS 2008), vol. 2, 19-21 March 2008, Hong Kong, pp. 1212-1217. 270