Simulation and Performance Analysis Evaluation for Variant MANET Routing Protocols

Transcription

1 Simulation and Performance Analysis Evaluation for Variant MANET Mrs. Assistant Lecturer, Technical College on Mosul, Mosul, Iraq, doi: /ijact.vol3. issue1.1 Abstract This paper first describes characteristics of Mobile Ad hoc Networks (MANETs), and ir Routing protocol, and second a mobile ad hoc network (MANET) which consists of set mobile wireless nodes (25, 50, 75, and 100) and one fixed wireless server are design using OPNET Modeler The performance of this network under different routing protocol is analyzed by three metrics: delay, network load and throughput. The comparison analysis will carry out about se protocols and in last conclusion shows which routing protocol is best one for mobile ad hoc networks. 1. Introduction Keywords: MANET,, OPNET, AODV, TORA, DSR MANET stands for Mobile Ad hoc Network is a dynamic distributed system of arbitrarily moving wireless devices with limited battery power [1][2]. It is a decentralized autonomous wireless system which consists of free nodes. It is also sometimes called a mobile mesh network, and is a self configurable wireless network. A MANET consists of mobile nodes, a router with multiple hosts and wireless communication devices. The wireless communication devices are transmitters, receivers and smart antennas. These antennas can vary in many types, while nodes can be eir fixed or mobile. Node types are: mobile phone, laptop, personal digital assistance, MP3 player and personal computer. These nodes can be located in cars, ships, airplanes as well as small personal electronic devices [3]. Nodes can connect to each or randomly as well as forming arbitrary topologies. Nodes mselves can act like a router. The topology may also change frequently. Each user of node has freedom to move while communicating. One node can take packet from or node and transmit it to its neighboring node[4]. The ability of self configuration of se nodes makes m more suitable for urgently required network connections. For example in disaster hit areas where re is no communication infrastructure, and it is necessary to quickly obtain a communication infrastructure. MANET is a fast solution in any disaster situation. MANET is a spontaneous network. It is useful when dealing with wireless devices in which some of devices are part of network only for duration of a communication session. The MANET working group (WG) within Internet Engineering Task Force (IETF) works specifically on developing IP routing protocols topologies. Interest in MANETs is due to promise of ubiquitous connectivity beyond that currently being provided by Internet. Firstly, MANETs are easily deployed allowing a plug-and-communicate method of networking. Secondly, MANETs need no infrastructure [5], eliminating need for an infrastructure and reducing cost of establishing network. Moreover, such networks can be useful in disaster recovery where re is not enough time or resources to install and configure an infrastructure. Thirdly, MANETs do not need central management. Hence, y are used in military operations where units are moving around battle field and a central unit cannot be used for synchronization [6]. Potential applications of MANETinclude mobile conferencing, emergency services, disaster recovery, and battlefield operations[7] MANET have a dynamic nature, and are ideal as y have a large number of applications. Quick deployment and minimal configuration of MANET makes m suitable to use in emergencies such as natural disasters. The growth of technology and increase in Wi-Fi capable laptops, mobile phones, MP3 players and or small portable devices has created a genuine reason for population of MANET [8]. Ad hoc networks have two forms; one is static ad hoc networks (SANET), and or is called mobile ad hoc network (MANET). Commercial implementation of ad hoc networks has become possible due to development of new technology such as [9]

2 A number of MANET routing protocols were proposed in last decade. These protocols can be classified according to routing strategy that y follow to find a path (route) to destination. These protocols perform variously depending on type of traffic, number of nodes, rate of mobility, etc [5].Simulations provide a valuable means to compare different protocols and study ir performance in terms of efficiency and robustness. Indeed, network simulation environments such as ns-2, GloMoSim, Qualnet, and Opnet are most commonly used tools for evaluating and comparing performance of mobile ad hoc network (MANET) protocols. OPNET Modeler is used in this paper. It is a network simulator developed at Massachusetts Institute of Technology that can model and simulate communication networks, devices, and protocols. OPNET Modeler is based on a series of hierarchical editors that directly parallel structure of actual networks and protocols. OPNET Modeler shows animations of simulation status and graphs of simulation results estimated in this study, while references number 15 use Ns-2 and self similarity traffic for evolution of MANET Routing protocols. 2. in MANETs Routing protocols in MANET are divided into four categories: proactive, reactive, hierarchical and geographic routing protocols [10]. The most popular ones are AODV, DSR (reactive), OLSR (proactive) and GRP (geographic).reactive protocols like DSR and AODV find routes only when requested and data need to be transmitted by source host using distance-vector routing algorithms. Proactive protocols like OLSR are table driven protocols and use link state routing algorithms. Geographic routing protocols use node position (i.e., geographic coordinates) for data forwarding [10]. A node forwards a packet with considering its neighbors and destination physical positions. In se protocols packets are sent to known geographic coordinates of destination nodes [11]. We will focus in this paper on following MANET routing protocols: 2.1. DSR Dynamic Source Routing (DSR) DSR is an entirely on-demand ad hoc network routing protocol composed of two parts: Route Discovery and Route Maintenance[12]Dynamic Source Routing (DSR) is a reactive protocol that discovers and maintains routes between nodes on demand [13]. It relies on two main mechanisms, Route Discovery and Route Maintenance. In order to discover a route between two nodes, DSR floods network with a Route Request packet. This packet is forwarded only once by each node after concatenating its own address to path. When targeted node receives Route Request, it piggybacks a Route Reply to sender and a route is established. Each time a packet follows an established route, each node has to ensure that link is reliable between itself and next node. DSR provides three successive steps to perform this maintenance: link layer acknowledgment, passive acknowledgment and network layer acknowledgment. If a route is broken, n node which detects failure sends (by piggybacking) a Route Error packet to original sender [14] OLSR (Optimized Link State Routing) OLSR is a proactive routing protocol and is also called a table driven protocol because it permanently stores and updates its routing table. OLSR keeps track of its routing table in order to provide a route if needed. OLSR can be implemented in any ad hoc network. Due to its nature, OLSR is called a proactive routing protocol [4]. Based on definition and use of dedicated nodes, y are called multipoint relays (MPRs). MPRs are selected nodes which forward broadcast packets during flooding process. This technique allows reduction of packet overhead as compared to a pure flooding mechanism, where every node retransmits packet when it receives first copy. In contrast with classic link state algorithm, partial link state information is distributed into network [15]

3 2.3. Ad Hoc on-demand Distance Vector Routing (AODV) AODV provides on-demand route discovery in mobile ad hoc networks [16]. Like most reactive routing protocols, route finding is based on a route discovery cycle involving a broadcast network search and a uncast reply containing discovered paths. Similar to DSDV, AODV relies on per-node sequence numbers for loop freedom and for ensuring selection of most recent routing path. AODV nodes maintain a route table in which next-hop routing information for destination nodes is stored. Each routing table entry has an associated lifetime value. If a route is not utilized within lifetime period, route expires. Orwise, each time route is used, lifetime period is updated so that route is not prematurely deleted [17]. When a source node has data packets to send to some destination, it first checks its route table to determine wher it already has a route to destination. If such a route exists, it can use that route for data packet transmissions. Orwise, it must initiate a route discovery procedure to find a route [17] Temporally Ordered Routing Algorithm (TORA) TORA is anor source-initiated on-demand routing protocol, built on concept of link reversal of Directed Acyclic Graph (ACG) [18]. In addition to being loop-free and bandwidth-efficient, TORA has property of being highly adaptive and quick in route repair during link failure, while providing multiple routes for any desired source/destination pair. These features make it especially suitable for large highly dynamic mobile ad hoc environments with dense populations of nodes. The limitation in TORA s applicability comes from its reliance on synchronized clocks. If a node does not have a GPS positioning system or some or external time source, or if time source fails, algorithm cannot be used [17]. TORA is designed to operate in a highly dynamic mobile networking environment. It is sourceinitiated and provides multiple routes for any desired source destination pair. The key design concept of TORA is localization of control messages to a very small set of nodes near occurrence of a topological change. To accomplish this, nodes need to maintain routing information about adjacent (one-hop) nodes. The protocol performs three basic functions: Route creation, Route maintenance and Route erasure [19] 3. Performance Parameters OPNET modeler supports different parameters for measurement performance evaluation of MANET network under different routing protocols. These parameters have different behaviors for overall network performance [8]. We evaluate three parameters in our study on overall network performance. These parameters are delay, network load, and throughput Delay The packet end-to-end delay is time from generation of a packet by source up to destination reception, so this is time that a packet takes to go across network. This time is expressed in seconds (sec) [8] Network Load Network load represents total load in bit/sec submitted to wireless LAN layers by all higher layers in all WLAN nodes of network [20]. When re is more traffic coming into network, and it is difficult for network to handle all this traffic it is called network load. An efficient network can easily cope with large traffic coming in, and to make best possible network, many techniques have been introduced [8]

4 3.3. Throughput Throughput: Representing total data traffic in bits/sec successfully received and forwarded to higher layer by WLAN MAC [21] 4. The Simulation Methodology The Optimized Network Engineering Tool (OPNET v14.5) software used for simulations implemented in this paper. The first step is to create and design network. Figure (1) showss simulation environment of one scenario containing 25 mobile nodes and one fixed WLAN server running GRP. We used MANET model library provided by version 14.5, wlan_wkstn_adv node model which represents a workstation with client-server applications running over TCP/IP and UDP/IP. The workstation supports one underlying WLAN connection at 1 Mbps, 2 Mbps, 5.5 Mbps, and 11 Mbps. we configure entire node in scenario to work with 5.5 Mbps. The network size is of 1500 x 1500 meters. After that IPv4 addressing was assigned to all nodes. We use The Rx Group Config node to speed up simulation time. This scenario is used to compute set of possible receivers that a node can communicate with, so all possible receivers that have a channel match with transmitter channel(s), and fall within distance and path loss thresholds are receivers that a node can communicate with. It is configured to eliminate all receivers that are over 1500 meters away. The "Application Config" node is used to specify applications using available application types. FTP application type was chosen to all nodes in network with multiple FTP sessions, and FTP was selected as traffic High Load. We ran four scenarios, for each type of routing protocol, in every scenario re were 25, 50, 75 and 100 mobile nodes. Alll attributes remained same except for number of nodes, which was increased. The routing protocol of network also changed. Each scenario was run for 30 minutes (simulation time). The MANET network under AODV, DSR, OLSR, GRP, and TORA were tested against three parameters i.e. delay, network load and throughput. Figure 1. Simulating 25 Nodes Results_ The First Scenario for MANET 25 Nodes Throughput Figure (2) shows WLAN throughput for first scenario. The peak value of throughput when number of nodes is 25 under OLSR is equal to bit/sec and it remains constant along simulation period, under GRP equal to bits/sec but value degrades to bit/sec and remains approximately constant along simulation period. Under AODV, throughput were 0 until minute 8 of simulation period n value changed to peak value equals to bit/sec but it didn t remain constant along simulation period. Under DSR value of throughput like AODV was 0 until 7 minutes of simulation period n value changed to peak value equal to bit/sec but it didn t remain constant along simulation period. Under TORA value of throughput was 0 until 7 minutes of simulation period n value changed to peak - 4 -

5 15133bit/sec but it didn t remain constant along simulation period. Figure (2) shows a good stable throughput for MANET running OLSR as routing protocol of network. Figure 2. Wireless LAN Throughput in bit/sec for MANET 25 Nodes Delay Figure (3) shows delay of WLAN for first scenario. The value of delay when number of nodes is 25 under OLSR is smallest value and is equal to seconds and remains constant along simulation period. Under GRP, peak value was equal to seconds and re were very slight changes in GRP delay to value seconds and remained constant along simulation period. Under AODV, peak value of delay was seconds and remained constant to this value along simulation period. Under TORA, peak value of delay was equal to seconds and ree was a change in this value equal to seconds and remaining constant along simulation period. Under DSR, delay was at 7 minutes, n re were slight changes in DSR delay to peak value which remained constant to this value along simulation period Load Figure 3. Time Average in Wireless LAN Delay in sec for MANET 25 Nodes Figure (4) shows load of WLAN for first scenario. The value of load when number of nodes is 25 under OLSR is largest value with a peak value equal to bit/sec and remaining constant along simulation period. Under GRP, value of load start with its peak value equal to bit/sec and starting to decrease along simulation period to reach value 4137 bit/sec which remains constant to this value along simulation period. Under AODV, load begins with its smallest value which is equal to 0 until minute 7 of simulation period n starts to increase to reach its peak value equal to 3034 bit/sec and remaining constant along simulation period. Under TORA, load begins with its smallest value which is equal to 1048 bit/sec until minute 7 of simulation period n starts to increase to reach its peak value which is equal to 2985 bit/sec and - 5 -

6 remains constant along simulation period, under load begins with its smallest value equals to 0 until minute 7 of simulation period n startss to increase to reach its peak value equals to 2404 bit/sec and remains constant along simulation period. Figure 4. Time Average in Wireless LAN Load in bit/sec for MANET 25 Nodes The Second scenario for MANET 50 nodes Throughput Figure (5) shows WLAN throughput for second scenario. The peak value of throughput when number of nodes is 50 under OLSR is equal to bit/sec and remains constant along simulation period, and comparing this value with value of throughput for 25 nodes we notice a difference between two values. The value for 50 nodes is higher than throughput for 25 nodes, and this is because of increase in number of nodes. Under GRP, peak value of throughput is equal to bits/sec comparing with 25 nodes re is increase with value. This is of course because of increase in number of nodes, but value degrades to bit/sec and remains approximately constant along simulation period. Under AODV throughput was 0 until minute 6 of simulation period n value changed to peak value to be equal to 8629 bit/sec and remained constant along simulation period. Under TORA, value of throughput was equal to 5538 at starting of simulation period n increased to value 8401 bit/sec and remained constant along simulation period. Under DSR, value of throughput was 0 until 7 minutes of simulation period n value changed to peak 3855bit/sec and remained constant along simulation period. This figure showed a good stable throughput for MANET running OLSR as routing protocol of network and increased of this value. Figure 5. WLAN Throughput in bit/sec for MANET 50 Nodes - 6 -

7 4.2.2 Delay Figure (6) shows delay metric of WLAN for second scenario. The value of delay when number of nodes is 50 under OLSR is smallest value and is equal to seconds and remains constant along simulation period, but a slight increase in delay is noticed comparing with 25 nodes. Under GRP peak value is equal to seconds and re are very slight changes in GRP delay to seconds but it remains constant along simulation period. Under AODV peak value of delay was seconds at 6 minutes of simulation period. There was a slight decrease in value of AODV delay to reach seconds and it remained constant to this value along simulation period. Under TORA, peak value of delay was equal to seconds and re was a change in this value to equal seconds. Under DSR delay was at minute 6, but re was an increase in DSR delay to peak value seconds. Figure 6. Time Average in Wireless LAN Delay in sec for MANET 50 Nodes Load Figure (7) shows load of WLAN for second scenario. The value of load when number of nodes is 50 under OLSR is largest value with a peak value equal to bit/sec and remaining constant for simulation period. Under GRP, value of load starts with its peak value equal to bit/sec and starting to decrease along simulation period to reach value 7760 bit/sec and remaining constant to this value along simulation period. Under AODV, load begin with its smallest value equal to 0 until minute 7 of simulation period n starting to increase to reach its peak value equal to 4983bit/sec. Under TORA, load begins with a value equal to 3644 bit/sec n starting to increase to reach its peak value equal to 5956 bit/sec. Under DSR load begins with its smallest value equal to 0 until minute 6 of simulation period n starting to increase to reach its peak value equal to 3605 bit/sec and remaining constant along simulation period. Under AODV, load begins with its smallest value equal to 0 until minute 6 of simulation period n starting to increase to reach its peak value equal to 5209 bit/sec and remaining constant along simulation period. Figure 7. Time Average in WLAN Load in bit/sec for MANET 50 Nodes - 7 -

8 4.3.. The Third Scenario for MANET 75 Nodes Throughput Figure (8) shows WLAN throughput for third scenario. The peak value of throughput when number of nodes is 75 is under OLSR and is equal to /sec (starting with value bit/sec) and remaining constant along simulation period. Comparing this value with value of throughput for 50 nodes, we notice differences between two values. The throughput value for 75 nodes is higher than throughput for 50 nodes, and this is because of increase in number of nodes. Under GRP throughputt starts with value bits/sec and decreases to value bit/sec comparing with 50 nodes re are increase with value and this is of course because of increase in number of nodes. Under AODV, throughput was 0 until minute 3 of simulation period n value changed to peak value equal to 2637 bit/sec. The value n kept increasing to reach value 23162bit/sec and remained constant along simulation period. Under TORA, value of throughput was equal to bit/sec at start of simulation period n increased to value bit/sec and remained constant along simulation period. Under DSR, value of throughput was 0 until 6 minute of simulation period n value changed to become 518 bit/sec and kept increasing to reach to its peak value 7009 bit/sec and remained constant along simulation period. This figure showed a good stable throughput for MANET running OLSR as a routing protocol for network. Figure 8. WLAN Throughput in bit/sec for MANET 75 Nodes Delay Figure (9) shows delay of WLAN for third scenario. The value of delay when number of nodes is 75 under OLSR is smallest value and is equal to seconds and remains constant along simulation period. Under GRP delay value starts with seconds, n re are slight changes in GRP delay to value seconds which remains constant along simulation period. Under AODV, peak value of delay was seconds at minute 3 of simulation period. There is a slight decrease in value of AODV delay to reach second and remaining constant to this value along simulation period. Under TORA peak value of delay was equal to seconds at beginning of simulation period and re were changes in this value to decreasee along simulation period to reach value second. Under DSR, delay was at minute 6 n increased in DSR delay to reach to peak value second

9 Figure 9. Time Average in WLAN Delay in sec for MANET 75 Nodes Load Figure (10) shows load of WLAN for third scenario. The value of load when number of nodes is 75 under OLSR is largest value starting with bit/sec to reach peak value equal to bit/sec and remaining constant along simulation period. Under GRP value of load starts with its peak value equal to bit/sec and starts to decrease along simulation period to reach value bit/sec and remains constant to this value along simulation period. Under AODV, load begins with its smallest value equals to 0 until minute 3 of simulation period n starts to increase to reach its peak value equal to 8840 bit/sec. Under TORA, load begins with value equal to 8266 bit/ /sec n starts to increase to reach its peak value equal to bit/sec. Under DSR, load begins with its smallest value equal to 0 until minute 6 of simulation period n starts to increase to reach its peak value equal to 8820 bit/sec. Under AODV, load begins with its smallest value equal to 0 until minute 3 of simulation period n starts to increase to reach it peak value equal to 8790 bit/sec and remaining constant along simulation period. Figure 10. Time average in WLAN Load in bit/sec for MANET 75 nodes The Fourth scenario for MANET 100 nodes Throughput Figure (11) shows WLAN throughput for fourth scenario. The peak value of throughput when number of nodes is 100 under OLSR is equal to /sec (starting with value bit/sec) and remains constant along simulation period. Comparing this value with value of throughputt for 75 nodes, we notice a difference between two values. The throughput value for 100 nodes is higher than throughput for 75 nodes. This is because of increase in number of nodes. Under GRP, throughput starts with value bits/sec and decreases to value bit/sec. Comparing with 75 nodes re was an increase with throughput value, and this of - 9 -

10 course, is becausee of increase in number of nodes. Under AODV, throughput was 0 until minute 2 of simulation period n value changed to peak value equal to 2416 bit/sec and keeps increasing to reach value of 45508bit/sec and remain constant along simulation period. Under TORA value of throughput was bit/sec at start of simulation period n increased to value of bit/sec and remained constant along simulation period. Under DSR, value of throughput was 0 until minute 3 of simulation period n value changed to 1371 bit/sec and kept increasing to reach its peak value 12286bit/sec and remain constant along simulation period. This figure showed a good stable throughput for MANET running OLSR as routing protocol of network. Figure 11. Wireless LAN Throughput in bit/sec for MANET 100 nodes Delay Figure (12) shows delay of WLAN for fourth scenario. The value of delay when number of nodes is 100 under OLSR is smallest value and equal to second and remains constant along simulation period. Under GRP delay value starts at second and n slightly changes in GRP delay to value second and remains constant along simulation period. Under AODV, peak value of delay was second at minute 3 of simulation period, and n re was a slight decrease in value of AODV delay to reach second and remain constant to this value along simulation period. Under TORA, peak value of delay equals to second at begging of simulation period and re was change in this value to decrease along simulation period to reach value second. Under DSR, delay was at.63minutes n re was an increase in DSR delay to reach peak value second Load Figure 12. Time average in WLAN delay in sec for MANET 100 nodes Figure (13) shows load of WLAN for fourth scenario. The value of load when number of nodes is 100 under OLSR is largest value starting with bit/ /sec to reach peak value equal to bit/ /sec and remaining constant along simulation period. Under GRP, value of load starts with its peak value equal to bit/sec and starting to decrease along simulation period to reach value bit/sec and remaining constant to this value along

11 simulation period. Under AODV, load begins with its smallest value equal to 0 until minute 2 of simulation period n starting to increase to reach its peak value equal to bit/sec. Under TORA, load begins with value equal to bit/sec n starting to increase to reach its peak value equal to bit/sec. Under DSR, load begins with its smallest value equal to 0 until minute 3 of simulation period n starting to increasee to reach it peak value equal to bit/sec. Figure 13. Time average in Wireless LAN Load in bit/sec for MANET 1000 nodes 5. Conclusionss The simulation study of our paper for MANET network under five routing protocols AODV, DSR OLSR, TORA and GRP were deployed using FTP traffic analyzing. We checked behavior of se protocols with respect to three performance metrics: delay, network load and throughput. Figures of 2 to 13 show behavior of MANET under all routing protocols for different numbers of mobile nodes. Obviously some routing protocols performed better than ors. From above analysis of routing protocols, OLSR outperforms fourth AODV, DSR, TORRA and GRP in both delay and throughput. 6. References [1] [2] [3] [4] [5] [6] [7] [8] M. Gerl and J.T. Tsai, Multicluster, mobile, multimedia radio network ACM Wireless Networks Vol 1, No3,ppp , 1995 Natarajan Meghanthan," A Simulation-based Performance Analysis of Multicast Routing in Mobile Ad hoc Networks",International Journal of Informationn Processing and Management (IJIPM),Volume 1, Number 1, July 2010 Xiaogeng Zhao, An Adaptive Approach for Optimized Opportunistic Routing Over Delay Tolerant Mobile Ad Hoc Networks, Computer Science Department, Rhodes University, PhD sis, December 2007 M. G. Kaosar, H. M. Asif, T R. Sheltami, A. S. H. Mahmoud. Simulation-Based Comparative Study of On Demand for MANET. International Conference on Wireless Networking and Mobile Computing (ICWNMC'05) Chennai, India. Vol. 1, pp , 2005 S. Lee, J. Hsu, R. Hayashida, M. Gerla, and R. Bagrodia, Selecting a Routing Strategy for Your Ad Hoc Network, Computer Communications, vol. 26, no. 7, pp , May C. E. Perkins and P. Bhagwat. Highly Dynamic Destination-Sequenced Distance-Vector Routing (DSDV) for Mobile Computers, ACM SIGCOMM Computer Communication Review, Vol 24, Isse 4, pp , October 1994 Wesam Almobaideen, Khaled Hushaidan, Azzam Sleit, Mohammad Qatawneh," A Cluster-Based Approach for Supporting QoS in Mobile Ad Hoc Networks", International Journal of Digital Content Technology and its Applications(JDCTA). Volume 5, Number 1, January 2011 Sajjad Ali & Asad Ali, Performance Analysis of AODV, DSR and OLSR in MANET, department of Electrical Engineering with emphasis on Telecommunication, Blekinge Institute of Technology Sweden, MSc Thesis,

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