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Improving Throughput and Controlling Congestion Collapse in Mobile Ad Hoc Networks

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Bonfring International Journal of Research in Communication Engineering Volume 1, Issue Inaugural Special Issue, 2011
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  Bonfring International Journal of Research in Communication Engineering, Vol. 1, Special Issue, December 2011 39 ISSN 2250  –   110X | © 2011 Bonfring Abstract---   Mobile ad hoc networks are collections of mobile nodes that can dynamically form temporary networks without the need for pre-existing network infrastructure or centralized administration. These nodes can be arbitrarily located and can move freely at any given time. Hence, the network topology can change rapidly and unpredictably.  Because wireless link capacities are usually limited, congestion is possible in MANETs. Hence, balancing the load in a MANET is important since nodes with high loads will deplete their batteries quickly, thereby increasing the  probability of disconnecting or partitioning the network. Here a load balancing protocol is proposed to improve the network throughput, decrease average end-to-end delay and reduce congestion in ad hoc networks. This scheme is applied as an extension on top of existing load balanced routing protocols. Simulation results obtained using ns-2 network simulation  platform show a 20-25% improvement in packet delivery ratio and average end-to-end delay. Keywords---   MANET, Congestion, Load balancing,  Network Throughput I.   I  NTRODUCTION  OBILE ad hoc networks (MANETs) are collections of mobile nodes that can dynamically form temporary networks on the fly without the need for pre-existing network infrastructure or centralized administration. They have desirable features such as fast deployment and the ability to communicate while on the move. Over the years, numerous routing protocols have been developed for ad hoc mobile networks. These can be categorized into table-driven and on-demand routing. Table-driven routing protocols maintain consistent, up-to-date routing information in each node by  propagating route updates throughout the whole network. Although a route to every other node is always available, such  protocols incur signaling traffic and power consumption overhead. On the other hand, on-demand routing protocols do not maintain routing information at every node. They create routes only when desired by the source. So that on demand routing protocols can perform better than table-driven  N.S. Kavitha, Assistant Professor-Senior Grade/CSE, Sri Ramakrishna  Institute of Technology, Coimbatore, E-mail: nsksrit@gmail.com  Dr.P. Malathi, Professor/ECE, Sri Ramakrishna Institute of Technology, Coimbatore, E-mail: pmalathi2004@yahoo.co.in  Jim Mathew Philip, Assistant Professor-Senior Grade/CSE, Sri  Ramakrishna Institute of Technology, Coimbatore, E-mail: mail2jim_mp@yahoo.co.in   protocols in MANETs. Several ad hoc routing protocols use route hop count as the routing metric. Although it is intuitive and simple, it does not consider link capacity. In shortest path routing, nodes on the shortest path will get more heavily loaded than others since they are frequently chosen as the routing path. Having a heavy load can exhaust a node‘s resources such as bandwidth, processing power, battery energy, and memory storage. Furthermore, if one of the heavily loaded nodes is congested, it can lead to packet loss and buffer overflow, resulting in longer end-to-end delay, degradation in throughput, and loss of transport connections. Hence, it is important that some form of load balancing is  present in the network. Most of the loads balancing protocols are on-demand-based protocols; that is, they combine load  balancing strategies with route discovery. A route with the least load among multiple possible routes from source to destination is usually chosen. The existing Load-Aware On-Demand Routing (LAOR) is delay based. It is an extension of ad hoc on-demand distance vector (AODV) routing. It has two phases: route discovery and route maintenance. LAOR achieves load balancing by minimizing the estimated total route delay and route hop count. A node initiates route discovery by sending a route request (RREQ) when it does not have a valid route to the destination. Intermediate nodes that receive the RREQ message update the total delay to RREQ and the routing table. Unlike AODV, if an intermediate node receives a duplicate RREQ with a smaller total delay and hop count, it updates this route in the routing table. The destination node then sends a reply message (RREP) when it receives the first RREQ. If duplicate RREQs received at the destination node have smaller total delay and hop count than previous ones, it sends an RREP message to the source node to change the chosen route immediately. When the source node receives the RREP, it initiates data packet transmission. This approach reduces delay due to the efforts made in selecting the best route. Load balanced ad hoc routing protocols use different load metrics: ã Active path: This refers to the number of active routing  paths supported by a node. Generally, the higher the number of active routing paths, the busier the node since it is responsible for forwarding data packets from an upstream node to a downstream node. ã Traffic size: This refers to the traffic load present at a node and its associated neighbors (measured in bytes). ã Packets in interface queue: This refers to the total number of packets buffered at both the incoming and outgoing wireless Improving Throughput and Controlling Congestion Collapse in Mobile Ad Hoc Networks    N.S. Kavitha, Dr.P. Malathi and Jim Mathew Philip M  Bonfring International Journal of Research in Communication Engineering, Vol. 1, Special Issue, December 2011 40 ISSN 2250  –   110X | © 2011 Bonfring interfaces. ã Channel access probability: This refers to the likelihood of successful access to the wireless media. It is also related to the degree of channel contention with neighboring nodes. ã Node delay: This refers to the delays incurred for p acket queuing, processing, and successful transmission. Existing load balanced ad hoc routing protocols use the above-mentioned load metrics to model load. In a broader context, the term load can be interpreted as: ã Channel load: Represents the load on th e channel where multiple nodes contend to access the shared media. ã Nodal load: Relates to a node‘s activity. Specifically, it refers to how busy a node is in processing, computation, and so on. ã Neighboring load: Represents the load generated by communication activities among neighboring nodes. Figure 1.1: Example of MANET II.   P ROBLEM S TATEMENT  This section provides an introductory overview of the congestion problem.  A.   The congestion problem In a network with shared resources, where multiple senders compete for link bandwidth, it is necessary to adjust the data rate used by each sender in order not to overload the network. Packets that arrive at a router and cannot be forwarded are dropped, consequently an excessive amount of packets arriving at a network bottleneck leads to many packet drops. These dropped packets might already have traveled a long way in the network and thus consumed significant resources. Additionally, the lost packets often trigger retransmissions, which mean that even more packets are sent into the network. Thus network congestion can severely deteriorate network throughput. If no appropriate congestion control is performed this can lead to a congestion collapse of the network, where almost no data is successfully delivered. Congestion occurs when a link or node is carrying so much data that its quality of service deteriorates. Typical effects include queuing delay,  packet loss or the blocking of new connections. In dynamic networks, path reliability often fluctuates due to path reconfigurations. Path reconfigurations can result in sudden load changes along paths. This may happen during the transition between areas with different node density. Traffic routed through the sparser region may increase the load of the intermediate nodes. On the other hand, traffic redirected in a denser area will result to increased contention. These effects can be resolved using load balancing technique. Injecting traffic during transient periods of poor path quality will degrade the network resources. In static networks, significant changes in paths are less likely to occur. But in the case of dynamic networks path can be changed more often due to the mobility. Throughout the detailed route of travel, alternating paths may experience considerable reliability fluctuations over small periods of time. This is due to the varying quality of the wireless links due to the mobility. When congestion occurs on the Internet, it is usually concentrated on one single router. In contrast, congestion in MANETs affects a whole area because of the shared medium.  Not nodes are overloaded, but regions of the network. Although this depends on the network type, packet losses which are not caused by network congestion can be much more frequent in wireless networks. This can lead to wrong reactions of TCP congestion control. Moreover, observing  packet losses is much harder, because transmission times and thus also round trip times vary much more. Furthermore, due to the comparatively low bandwidth of mobile ad-hoc networks, one single sender is able to  —   be it accidentally or intentionally  —  cause a collapse of the network due to congestion. The extreme effect of a single traffic flow on the network condition can cause severe unfairness between flows. Thus wireless multihop networks are much more prone to overload-related problems than traditional wire line networks like the Internet. Therefore an appropriate congestion control is absolutely vital for network stability and acceptable  performance. III.   R  ELATED W ORK   The exiting Load-Aware On-Demand Routing (LAOR) implements congestion monitoring during the route discovery  process. It determines if a node is congested by first comparing the estimated total node delay and the number of packets  buffered at the interface queue of two serial nodes on the RREQ packet forwarding path. A node is considered congested if the total delay of a node is greater than the upstream node or the queue length is more than 80 percent of its buffer size. When a node becomes congested, it discards the RREQ message. This approach reduces the routing overhead and distributes the load evenly in the network. However, reliable delivery of RREQ messages to the destination node is not guaranteed by LAOR [3]. Finally, the LAOR protocol models load in terms of delay, including the queuing delay, contention delay, and transmission delay. This metric is considered more accurate [4] than others since it considers the channel and nodal loads,  but not neighboring load. In addition, it incurs extra overhead due to an additional timestamp field used to determine the  packet arrival and transmission times. Hence, its complexity is high. The route load metric used in LAOR is a single valued  Bonfring International Journal of Research in Communication Engineering, Vol. 1, Special Issue, December 2011 41 ISSN 2250  –   110X | © 2011 Bonfring metric and refers to the total path delay. LAOR uses this node delay, previous node delay and the number of packets being queued in the current node to determine the congested node in the path [6]. These congested nodes drop any incoming route requests; intermediate nodes after receiving route requests updates the load information in the packets and resends them to all neighbors. The intermediate node will also check the load value and will drop the packet if its load value is worst than the currently stored one, if better than the packet will be resent. At destination any new coming route request carrying a new path will be compared with the currently active path. If better in terms of load then this path will be sent to the source as route reply. Although there are many proposed routing protocols for MANETs, most of them consider the shortest-path with minimum hop count as the route selection criterion. Even though this hop metric is easy to implement and reliable in dynamic environments, the queuing delay and the contention delay at the intermediate nodes are not taken into account for route selection. Thus, a minimum hop path may sometimes incur a higher end-to-end delay than some alternate paths. Moreover, routing protocols based on minimum number of hops cannot fairly distribute the routing load among mobile hosts. An unbalanced distribution of traffic may lead to higher  packet dropping rate and faster battery power depletion on certain mobile nodes [3]. IV.   P ROTOCOL D ESCRIPTION  The exiting Load-Aware On-Demand Routing (LAOR) implements congestion monitoring during the route discovery  process. It determines if a node is congested by first comparing the estimated total node delay and the number of packets  buffered at the interface queue of two serial nodes on the RREQ packet forwarding path. A node is considered congested if the total delay of a node is greater than the upstream node or the queue length is more than 80 percent of its buffer size. When a node becomes congested, it discards the RREQ message. This approach reduces the routing overhead and distributes the load evenly in the network. However, reliable delivery of RREQ messages to the destination node is not guaranteed by LAOR. Load balancing in proposed method is also performed during route discovery. When a node has packets to send and there is no available route, a route request packet is flooded throughout the network. Route request is also forwarded by intermediate nodes after they have appended their load values to the request message. However, intermediate nodes are not allowed to send route replies back to the source even if they have routes to the destination in their route caches. The destination node then decides to reply to route requests based on the comprehensive route load value. The destination node replies to the first request or to the request that has a smaller route load than previous requests. Once the source node receives the destination node‘s reply, it then utilizes the selected route to transmit data. If one or more links in the selected route is broken, the source node is notified by a route error packet, resulting in the source updating its route cache and reinitiating a new route discovery to discover a new least loaded route. V.   S IMULATION R  ESULTS A  ND E VALUATIONS  In this section, benefits of proposed load balancing  protocol are shown by comparing the simulation results with LAOR. Analysis of the protocol is done by studying the efficiency of routing metrics like throughput and packet delivery ratio. Energy efficiency of our protocol is evaluated using energy metrics average energy consumed variance and network lifetime. Throughput is the rate at which a computer or network sends or receives data. It is a good measure of the channel capacity of a communication link. It is usually rated in terms of how many bits they pass per second(Bit/s). In our project, throughput is the amount of data moved successfully from one node to another node in a given time period. In the existing system, initially the nodes spend much time in finding the node to communicate, so throughput is decreased at the  beginning of data transmission.  A.   Simulation Scenario This protocol is simulated using ns2[14] which supports complete physical, data link and MAC layer models for simulating wireless ad hoc networks. We have constructed a 100 X 100 m mobile ad hoc network of 50 nodes randomly  placed, which can be simulated in ns-2.33. These nodes correspond to the mobile nodes. For the traffic model, we consider constant bit rate (CBR) data sources each sending  packets at a fixed rate of 4 packets/sec. The data packet size is 512 bytes.  B.   Simulation Results We compare three performance metrics for evaluations: 1) Throughput: is the average rate of successful message delivery over a communication channel. 2) Packet delivery ratio: The measured ratio of the number of data packets delivered to the destinations to the number of  packets generated by all traffic sources. 3) Energy: Energy plays a major role in the lifetime of a mobile ad hoc network. Fig 4.1 shows the throughput. Throughput is the rate at which a computer or network sends or receives data. It is a good measure of the channel capacity of a communication link. It is usually rated in terms of how many bits they pass per second(Bit/s). Here, throughput is the amount of data moved successfully from one node to another node in a given time  period. In the existing system, initially the nodes spend much time in finding the node to communicate, so throughput is decreased at the beginning of data transmission. Fig 4.2 shows the energy. Energy plays a major role in the lifetime of a mobile ad hoc network. From the graph, it is clear that energy is reduced considerably. Thus, our proposed system is energy efficient when compared to the existing system as described earlier. The sudden increase and decrease in these graph means that the load may vary from one region to another region according to the number of nodes. Fig 4.3  Bonfring International Journal of Research in Communication Engineering, Vol. 1, Special Issue, December 2011 42 ISSN 2250  –   110X | © 2011 Bonfring shows the packet delivery ratio. Fig 4.4 shows graph showing Time Vs Packet Drop. Figure 4.5 Shows the Graph Comparing Packet Delivery of Existing and Proposed Protocols. Figure 4.1: Graph Showing Throughput Figure 4.2: Graph Showing Energy Figure 4.3: Graph showing Packet Delivery Ratio Fig 4.4: Graph showing Congestion (Time Vs Packet Drop) Table 4.1: Table comparing congestion Existing congestion Proposed congestion X Y X Y 0 5 10 15 20 25 30 0 500 750 810 920 930 970 0 5 10 15 20 25 30 0 100 160 200 230 300 330 Fig 4.4 shows the congestion. By using the proposed Load Balancing Protocol, congestion is reduced. Figure 4.5: Graph comparing Packet Delivery Ratio VI.   C ONCLUSION  In this paper, the existing LAOR protocol is compared with the proposed load balancing protocol. While offering better representation of actual load, LAOR incurs higher complexity in capturing load information. Comparing the operations of  protocols, only the proposed protocol achieves load balancing during route maintenance. Other protocol balance load only during route discovery. In wired networks, multicast is used very rarely, because it is often not supported by the network. But in mobile ad-hoc networks, where the network can be tailored to the application and bandwidth is especially scarce, it might in fact turn out to be vital for group communication scenarios. Congestion control for these non-unicast communication scenarios is also an open research issue. VII.   R  EFERENCES   [1]   A. H. Altalhi and G. Richard III, ―Load -Balanced Routing through Virtual Paths: Highly Adaptive and Efficient Routing Scheme for Ad Hoc Wireless Network  s,‖ 23 rd  IPCCC, 2004. [2]   H. Hassanein and A. Zhou, ―Routing with Load Balancing in Wireless Ad hoc Networks,‖ Proc. 4th ACM MSWiM ‗01 , Rome, Italy, 2001, pp. 89  –  96. [3]   J.- H. Song, V. Wong, and V. Leung, ―Load -Aware Ondemand Routing (LAOR) Protocol for Mobile Ad Hoc Networks,‖ Proc. 57th IEEE VTC-Spring, Jeju, Korea, Apr. 2003, pp. 1753  –  57. [4]   K. Chen and K. Nahrstedt. EXACT: An Explicit Rate-based Flow Control Framework in MANET (extended version). Technical Report
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