CHAPTER 3 IMPROVED AODV BASED ON LINK QUALITY METRICS

Transcription

1 63 CHAPTER 3 IMPROVED AODV BASED ON LINK QUALITY METRICS 3.1 INTRODUCTION The current ad hoc wireless routing protocols usually select the route with the shortest-path or minimum hop count to the destination but, this choosing of routes in this criterion tends to include longer hop length links. These links that are involved tend to be of bad signal quality. These links possess usually a poor SNR that causes higher frame error rates and lower throughput. Tsai et al (2006) examined routing protocol based on hop count that comprises the quality of the links employed in the protocol. The elimination of routes through bad links must be done to enhance the routing protocols. The hand-off concept is also incorporated during route maintenance to prevent link breakages in the proposed protocol. Hauspie et al (2002) introduced a metric for link quality estimation and a quick and consistent protocol to compute it practically was also presented. The proposed protocol description is based on AODV. One of the metrics based on link quality have been defined to enhance AODV routing algorithm so that it can handle link quality between nodes to evaluate routes. Performance of the proposed algorithm is compared to AODV. 3.2 AODV ROUTING PROTOCOL AODV is based on the Bellmann Ford Distance Vector algorithm, adapting it to work in a mobile environment. It is a reactive routing protocol; a

2 64 route to destination is discovered only on demand, when a node wants to forward a data packet to destination. The freshness of the route is maintained by use of sequence numbers to each of the routing information; it also ensures loop free routing. The AODV routing protocol saves storage space and energy. AODV does not need a central administrative system to control routing process. Hello messages used for maintenance do not cause large overhead in the network. Topological changes in the network are fast as updates happen at only the affected nodes. AODV can be used even in low processing and low bandwidth utilization. The disadvantages are its latency and scalability. Various enhancements have been proposed using AODV protocol. An improved AODV for load balancing have been proposed by Rani et al (2007) for route discovery using aggregate interface queue length. AODV- BRL was proposed by Yujun et al (2010) to increase the adaptation of routing protocols to topology changes by enhancing AODV-BR AODV Route Messages In the AODV protocol, three different types of messages are used; namely, the RREQ), the RREPs, and the RERRs. These message types are all transported with UDP, the user datagram protocol, a minimal messageoriented transport layer protocol, and thus the normal Internet protocol (IP) header processing is applied. If the source and destination nodes of a connection have one or more active routes between each other, the AODV protocol remains passive. But whenever a route to a certain destination is required, AODV gets active. The node running AODV, broadcasts a RREQ through the network to find a possible route to a specified destination. The route is found by two different

3 65 ways, first, when the RREQ message attains the destination itself, or second, when an intermediate node with latest route information to the destination is joined. The latest route means a valid route entry for the destination whose related DSN is at least as high as the DSN contained in the concerned RREQ message. The route is activated by unicasting a RREP message back to the source of the RREQ message. Each node in the network, which receives the RREQ message, saves a route back to the originator of the request in its routing table. The RREP message can be similarly unicasted from the destination along a path to that originator, or also from any intermediate node that can satisfy the request. Every node observes the link status of the next hop in an active route. Whenever one of the links in active route breaks, a RERR message is sent to notify all other nodes that a break of that link has transpired. The RERR message lists the destinations which are no longer attainable by the route that contains the broken link. In order to make this reporting mechanism possible, each node maintains a precursor list, which contains the IP address for each of its neighbors that possibly could use the node as the next hop towards a specific destination. This information is very easily obtained during the process for the generation of a RREP message. Whenever the RREP contains a nonzero prefix length, the originator of the RREQ message, which solicits the RREP message information, is implied among the precursors for the subnet route. A node using the AODV protocol can also send a RREQ for a multicast IP address, though certain specific rules are to be followed. Nevertheless, it is important to allow correct multicast operations by intermediate nodes that are not allowed as source or destination nodes for IP multicast addresses, then the process for multicast IP address is similar to that of any other destination IP address.

4 66 AODV is a table driven routing protocol, and thus, it deals also with the routing table management. Routing table information must be maintained even for short-lived routes, such as routes that are created to temporarily store reverse paths towards nodes originating RREQs. AODV uses the following fields with each routing table entry: Destination IP Address, DSN, Valid Destination Sequence Number flag, Network Interface, Other state and routing flags (e.g., valid, invalid, repairable, being repaired), Hop Count (number of hops needed to reach destination), Next Hop, List of Precursors and Lifetime. Figure 3.1 shows an example of AODV routing table. Destination IP Address DSN Valid DSN Flag Other Flag0s Network Interface Hop Count Next Hop List of Precursor Lifetime IoO IeO IoO Figure 3.1 Example of an AODV routing table Managing the sequence number is very important to assure loopfreedom, especially when links break and the node cannot deliver information about its sequence number. On link breakage or deactivation of a destination node, the route becomes invalidated. Operations which contain the sequence number of such a destination node mark it as inoperative on the table entry Route Request (RREQ) message format The format of the Route Request message is illustrated in Figure 3.2 and contains the following fields: J Join flag used in multicast. R Repair flag used in multicast.

5 67 G Gratuitous RREP flag indicates whether it is unicast to the node specified in the Destination IP Address field. D Destination only flag indicates that only the destination may respond to this RREQ. U Unknown sequence number indicates that the destination sequence number is unknown. Reserved When sent as 0 it is ignored on reception. Hop Count The number of hops from the source node to the node handling the request. RREQ ID A sequence number uniquely identifying the particular RREQ. Destination IP Address The IP address of the destination node. Destination Sequence Number The latest sequence number received in the past by the source node for any route towards the destination. Originator IP Address The IP address of the source node. Originator Sequence Number The current sequence number to be used in the route entry pointing towards the originator of the route request.

6 68 Type R A Reserved Prefix Size Hop Count Destination IP Address Destination Sequence Number Originator IP Address Lifetime Figure 3.2 Route Request Message RREQ Route Reply (RREP) message format The format of the Route Reply message is illustrated in Figure 3.3 and contains the following fields: R Repair flag used for multicast. A Acknowledgment required. Reserved When sent as 0 it is ignored on reception. Prefix Size If nonzero, the 5-bit Prefix Size specifies that the indicated next hop may be used for any node with the same routing prefix as the requested destination. Hop Count The number of hops from the source node to the Destination node. Destination IP Address The IP address of the destination for which a route is supplied. Destination Sequence Number The destination sequence number associated to the route.

7 69 Originator IP Address The IP address of the node which originated the RREQ for which the route is supplied Lifetime The time in milliseconds for which nodes receiving the RREP consider the route to be valid. TYPE J R G D T Reserved Hop Count RREQID Destination IP Address Destination Sequence Address Originator IP Address Originator Sequence Number Figure 3.3 Route Reply Message RREP Route Error (RERR) message format The format of the Route Error message is illustrated in Figure 3.4, and contains the following fields: N No delete flag, it is set when a node has performed a local repair of a link, and upstream nodes should not delete the route. Reserved When sent as 0 it is ignored on reception. Dest Count The number of unreachable destinations included in the message; must be at least 1. Unreachable Destination IP Address The IP address of the destination that has become unreachable due to a link break.

8 70 Unreachable Destination Sequence Number The sequence number in the route table entry for the destination listed in the previous Unreachable Destination IP Address field. The RERR message is sent whenever a link break causes one or more destinations to become unreachable from some of the node s neighbors. Type R A Reserved Prefix Size Hop Count Destination IP Address Destination Sequence Number Originator IP Address Lifetime Figure 3.4 Route Error Message RERR Route reply acknowledgment message format The Route Reply Acknowledgment (RREP-ACK) message is sent in response to a RREP message with the A bit set, when the route is not able to complete the route discovery cycle due to unidirectional links. The format of the Route Error message is illustrated in Figure 3.5, and contains the following fields: Reserved Sent as 0; ignored on reception. Type Reserved Figure 3.5 Route Reply Acknowledgement RREP-ACK

9 LINK QUALITY ESTIMATION IN WIRELESS NETWORKS Accurate and fast packet delivery ratio estimation used in evaluating wireless link quality, is a prerequisite to increase the performance of multi-hop and multi-rate wireless networks. The link quality information is highly important to the higher layer's performance. Accurate and fast response link quality estimation will enhance the wireless communication system performance. Unfortunately, contemporary PDR estimation methods, i.e., beacon-based packet counting in Estimated Transmission Time (ETT) by Coute et al (2003) and Expected Transmission Count (ETX) by Bicket et al (2005) metrics have unsatisfactory performances. This is because they use one type of packet to estimate the link quality for all the links which use packets that have different rates and sizes. Meanwhile, it only looked at the problem for the stationary scenarios whereas in real life, lots of communication devices can be mobile. To accurately estimate the link quality for all the links, lots of issues need to be considered. Firstly, the dynamics of the wireless links and the estimation methods should provide accurate estimation. They should respond fast when the link quality of a certain link changes. The estimation methods need to consider the impacts from the data rates, packet size, mobility and change in the environment. All these factors make the link quality estimation a hard task Link Quality based Transmission Power Adaptation Many wireless devices are mobile and battery powered now-a-days by (Jacobsson 2008), which means that service duration is highly dependent on the energy consumption and battery capacity. However, the fact that battery capacity is still limited (e.g. in many applications, namely, the battery of Nokia N95 normally cannot last for more than 24 hours). For IEEE and

10 72 IEEE , the link layer decides the transmission power in OSI model. The selected transmission power should not be higher than the maximum power level indicated in the government's regulation. Some wireless technologies allow adapting the transmission power levels to achieve better system performance. Energy saving is still an important issue in wireless communication. On the other hand, power adaptation can also reduce the interference between different communication nodes if the appropriate transmission power levels are selected which generates the lowest energy emission to the environment. Many methods have been proposed to save energy and reduce the interference for the IEEE and IEEE radios, such as power-aware routing and sleep mode. The problem is how to incorporate the wireless link quality information into the power saving mechanism. Despite the dynamic nature of the wireless link quality, the algorithm should try to select the appropriate transmission power level to transmit packets based on the received packet counting method, instead of using a fixed default power level for all packets, which is common in IEEE and IEEE Lower transmission power levels may result in more retransmissions, but still energy can be saved in many scenarios. Moreover, interference is also reduced. The decision of appropriate transmission power level can be made via the wireless link quality information Link Quality based Data Rate Adaptation Some wireless technologies also allow multiple data rates to transmit packets. The selection of appropriate data rate to achieve higher transmission efficiency is called data rate adaption. For example, some links are quite easy to lose packet with certain high data rates while they can deliver all the

11 73 packets in some low data rates. It is obvious to see that there is also a tradeoff between the transmission speed and error rate. The selection process for the best data rate that has the best combination of transmission speed and packet error rate is rate adaptation. Successful rate adaptation can bring in the highest throughput over a certain wireless link. This adaptation needs to be adaptive also since the link quality of the channels is dynamic. For the data rate adaptation, IEEE networks provide multirate options and several rate adaptation mechanisms provide the ability to select the rate intelligently. Prior works on the rate-adaptation focus on stationary scenarios, such as mesh networks. The effect of the smoothing of the rate adaptation is not a well-studied topic in the mobile scenarios such as IEEE mobile multi-hop networks Link Quality based Route Selection The routing layer in OSI model is set to select the route for packet forwarding. A good selection will result in higher throughput, lower delay from the end-to-end point of view. Link quality information can be very useful in this process. Based on lower layer's information, the routing layer decides the route between the source and the destination node. Previous works have proved that the hop count method which is widely used in wired network is not suitable in wireless network. This is because the wireless network has a different link quality and each link has its own link quality characteristic. Link quality based route selection will perform better than pure hop count routing metric. However, the performance enhancement in the routing layer by the introduction of the accurate and fast response link quality estimation is unknown. The measurement results show that accurate link quality information estimation method lead to a better route selection in the

12 74 form of increased end-to-end throughput compared to the traditional method, which respond slowly to the link dynamics. 3.4 ACTIVE ROUTE TIME-OUT (ART) Even though reactive protocols discover routes as and when required they still keep some of the route state information for a specific period of time. This reduces the overheads of route establishment as the route that is remembered can be used again if it is still valid in the near future. The duration of time for which the route state is maintained after communication between source and destination plays an important role in reducing network overheads (Claude, et al., 2002). However Ad hoc networks are highly mobile and the speed at which the nodes move about the network make it difficult to fix a specific time value for which the route state information is to be maintained. In AODV the route state information is maintained for a time period mentioned in the Active Route Timeout (ART) whereas in DSR timeout is maintained in the Route Cache Timeout. Perkins et al (1994) suggested a guide to set timer values for MANETs using AODV routing protocols. The timer value considered the network account parameters like diameter, per-hop time, and nodes number. Chin et al (2002) implemented AODV on a test-bed where timer values are set and adjusted using trial-and-error based on network con gurations finally concluding that a timer setting values formal methodology was a must. When node mobility is high, AODV has better latencies for low traffic load and higher overhead when mobility is high by Boppana et al (2001). In this study, the performance AODV routing protocol is investigated for effect of ART for nodes which move in constant speed and in varying speed. Experiments are conducted for varying number of nodes. The

13 75 performance of the network in terms of packet delivery ratio, end-to-end delay and packet dropped is evaluated. An inherent feature of mobile ad hoc networks is the frequent change of network topology leading to stability and reliability problems of the network. Highly dynamic and dense network have to maintain acceptable level of service to data packets and limit the network control overheads. This capability is closely related as how quickly the network protocol control overhead is managed as a function of increased link changes. Dynamically limiting the routing control overheads based on the network topology improves the packet delivery of the network. Reactive protocols keep route state information for some time to avoid the overhead of route establishment, as networks are never static or mobile. When a route successfully links two end points, it is remembered in case of reuse in the future. Similarly routing protocols too hold on to route state information for some time to avoid route establishment overheads. If the state is kept for a short time, the route might still be network valid but unavailable for the next connection. If kept too long, underlying topology might change with packets being lost before a new route is created. The AODV routing protocol uses two processes to build and maintains route state. First route discovery process allows route establishment by source and destination nodes for which the source floods a RREQ over a network, with the destination unicasting a RREP to the source, permitting intermediate nodes to store a route state between endpoints. Each node continues in this state for a specific time duration given by an ART value. The timer is reset back to ART whenever a route is used, the former being a static parameter defining how long a route is maintained in the routing table after the final packet transmission on this route.

14 76 As ART value increases, broken routes are used often by traffic originating nodes. On such occasions, the application waits for a new route discovery and invalidation of the earlier route. Though this might appear small, statistically affected node applications result in major disruptions when it happens. This initial delay can be amortized over all packets including those which originated after route discovery. Hence, initial delays are inevitable within statistics for later data stream packets. 3.5 METHODOLOGY In this section two modifications in the AODV routing protocol are investigated. It is proposed to investigate the performance of a highly mobile network using AODV routing protocol under different active route timeout and propose an enhanced routing algorithm Varying Overhead Ad hoc On Demand Distance Vector (VO-AODV) routing protocol. It is also proposed to investigate AODV routing based on LQ metric. The details of the proposed system are presented in the following sections Link Quality Accurate and fast wireless Link Quality Assessment (LQA) for wireless channels would bring in huge bene ts for mobile Wireless Ad Hoc Networks in the form of improved end-to-end performance. Each node in the network evaluates link quality according to Link Quality Metrics (L qm ). Link quality could be any parameter to assess the link such as signal strength, signal-to noise ratio, bit error rate, frame error rate, or a combination of them. For example, SSA by Dube et al (1997) uses signal strength while SBRSOLSR by Singh et al (2006) depends on signal-to-noise ratio. Furthermore, link quality can be averaged over time to mitigate random variability. In some cases, the signal strength of each received packet is used

15 77 as the link quality metric. If the signal strength of a received packet falls below a threshold, a route refresh process is triggered by Zhang et al (2008). A direct application of LQA is link quality-based routing. Hop count-based routing may produce routes with poor links. Hence, some prior proposals suggested to try to minimize the number of transmissions needed to reach from the destination to the source, such as ETX proposed by Couto et al (2005). Furthermore, not only the packet losses are considered for route selection, but also the data rate, such as the ETT by Bicket et al (2005). In ETX and ETT as well as most other works, link quality estimation is based on hello packet delivery ratio. Slow reaction to link dynamics and inaccuracy are the problems of such probe-based estimations. It may take long for a node to learn the quality of a new link or to adapt to the link conditions. Link quality is a dominant parameter, as it defines a given link s and devices ability to support traffic density for the connected period. Link state between two neighbours is affected by parameters like distance, battery power and mobility. The next parameter in route selection is connections number in the same path, to choose to save resources of intermediate nodes over this stretch by distributing network traffic over other nodes. Hence this increases system lifetime and also end to end delay. Link quality between two neighbours is the ability of the link to be stable as long as possible, have less bit errors and reach the destination with high signal strength. Literature evaluates link quality according to received signal strength, as transmission power of a wireless medium is directly proportional to link quality, as a high strength signal is stable and has less bit errors. The following equation gives reception power which represents link quality, L qm, for a transmitted signal with power P t for a distance d:

16 78 Lqm Pt * Gr * Gt * 4 * * d 2 (3.1) where G t is antenna gain of the transmitter, G r is antenna gain of the receiver, and is wavelength. From this equation, evaluating link quality based on received signal strength is also descriptive for other network factors like: Battery power: This is important as a node with low energy in its battery has limited transmission range affecting its link quality with the neighbourhood. But on the other hand, it cannot forward data for long. When battery level is low, transmission power is also low proportionately leading to low reception power. Hence this is not a high quality link. The distance: Reception power is relative to distance between nodes as when distance increase, link quality decreases. The mobility: Link between two nodes is affected by nodes mobility as link quality decreases when neighbours move away from each other and increases when they come closer. The link quality is measured using the extended hello message Proposed Improved AODV Model: VO-AODV In an Ad hoc network the throughput is affected by the speed at which the nodes move. As the nodes move over the network the topology also changes continuously which affects the overall network performance and is dependent on the routing protocol being used. In theory, reactive routing protocol should perform better than other routing protocols in a high mobility network. The route life represented by ART in AODV routing protocol plays an important role in managing fast change in topology. Typical values of ART

17 79 are 3 seconds which is not justified as the ART value is network dependent. In a static network the ART value can be arbitrarily high and in very fast moving node (assuming the node is a car) ART values has to be less than 1 second. To overcome this problem in reactive routing protocols, the Varying Overhead AODV (VO-AODV) is proposed. The additional steps involved over the routing overhead in each node are: At time t 1, for a duration n, compute power from all nodes S itransmitting data to node D. Let the power computed from each node be P i. The total power from all nodes for the duration is P i. At time t 2, for a duration n, compute power received from the same sources. Let the power computed for each node be P j from one packet received. The total power computed is given by P j. x Pj Pi Compute If x is positive increase ART from reference value by x/ P imax If x is negative decrease ART from reference value by x/ P imax provided the computed value does not go below minimum set threshold value The distance between a source and destination can be computed using the transmitter power output, transmitter antenna gain, receiver sensitivity, receiver antenna gain and free space loss. At two instances t 1 + n and t 2 + n, the power is computed from each of the source nodes transmitting data to the receiver node. If most of the

18 80 sources are close to each other, the probability of routes going stale is lower and hence ART can be increased. Since, measuring power at two instance of time, it is possible to predict whether the sources are moving towards the receiver node or away from it. The ART is changed accordingly based on the number of sources moving towards the destination or away from it Experimental Setup The experimental setup is used for performance evaluation of the conventional AODV, L qm AODV and VO-AODV routing protocols. OPNET simulator is used to implement the proposed routing protocol for comparison with L qm AODV and AODV routing protocol and to check the effectiveness of the proposed method Traffic Traffic Patterns describe how the data is transmitted from source to destination. The widely used traffic pattern in MANET CBR and its qualities of by Clausen 2012 and Singla and Kakkar (2010) are: Unreliable: since it has no connection establishment phase, there is no guarantee that the data is transmitted to the destination, Unidirectional: there will be no acknowledgment from destination for confirming the data transmission and Predictable: fixed packet size, fixed interval between packets, and fixed stream duration. A traffic generator was developed to simulate CBR sources. The sources and the destinations are randomly selected with uniform probabilities.

19 81 There were ten data sessions, each with the traffic rate of four packets per second. The size of data payload was 512 bytes Mobility Model Mobility models describe the movement pattern of the mobile users, their location; velocity and acceleration by Bindral et al (2010) and Agrawal et al (2009). They play a vital role in determining the performance of a protocol and also differentiated in terms of their spatial and temporal dependencies. Spatial dependency is a measure of how two nodes are dependent in their motion. When the two nodes are moving in the same direction, then they have high spatial dependency. Temporal dependency is a measure of how current velocity (magnitude and direction) are related to previous velocity. The two nodes are having the same velocity and direction means that they have high temporal dependency. The commonly used mobility model in MANET is Random Way point Mobility (RWM). RWM model is the commonly used mobility model in which every node randomly chooses a destination and moves towards it from a uniform distribution (0, V max ) at any moment of time, where V max is the maximum allowable velocity for every node by Agrawal et al (2009). Each node stops for a duration defined by the 'pause time' parameter when it reaches the destination. After the pause time it again chooses a random destination and repeats the whole process until the end of the simulation.

20 Performance metrics For evaluation of the proposed link quality AODV routing protocol performance, two metrics are considered: 1. Packet Delivery Ratio (PDR) 2. Average End to End Delay PDR is the ratio of data packets delivered to the destination to those generated by the sources and is calculated as follows: Number of Packets Received Packet Delivery Fraction= *100 Number of Packets Sent (3.2) Average End-to-End delay is the average time of the data packet to be successfully transmitted across a MANET from source to destination Mallapur et al (2010). It includes all possible delays such as buffering during the route discovery latency, queuing at the interface queue, retransmission delay at the MAC (Medium Access Control), the propagation and the transfer time. The average end to end delay is computed by, D i n Ri Si 1 msec n (3.3) where D is the average end-to-end delay, n is the number of data packets successfully transmitted over the MANET, ' i ' is the unique packet identifier, R i is the time at which a packet with unique identifier ' i ' is received and S i is the time at which a packet with unique identifier ' i ' is sent. The Average Endto-End Delay should be less for high performance.

21 Simulation Setup The hypothesis was implemented using OPNET. Fifty nodes with random mobility were implemented in a sqm area. Each node has a transmit power of watts. Each node randomly transmits raw unformatted data to every other node in the network. Simulation in each scenario was carried out for 600 second. Simulations were carried out with ART =3 second and the proposed method. Simulation parameters for packet delivery fraction & end to end delay investigations are as given below in Table 3.1: Table 3.1 Simulation Parameters Parameters Value Simulator OPNET Mobility Model Random Waypoint Study Protocols AODV, L qm AODV& VO-AODV Bandwidth 2 Mbps Simulation Time 600 seconds Simulation Area 1500 m X 1500 m Max speed 10 m/sec Traffic Source CBR Node Pause time 0, 10, 25, 50, 100 sec Packet Size 512 byte No. of nodes 50 AODV routing protocol builds and maintains route state based on two processes. First route discovery process allows source and destination nodes to establish a route. Then the source floods a RREQ over the network

22 84 and destination node unicasts a RREP allowing intermediate nodes to store a route state between endpoints. Each node keeps this state for a specific time given by ART value. The main effects/interactions of AODV timers, packet arrival rate, and node speed on many performance metrics are studied. Packet arrival rate specifies the rate at which a source node generates data packets to be routed. Node speed is mean network node speed. The following response variables are considered: data packets average end-to-end delay and flow throughput. The flow throughput is defined as average number of bytes transmitted per second. The ART parameter is arbitrarily set to 3 seconds. The node model is shown in Figure 3.6 and Figure 3.7 illustrates the state machine diagram for the IP Module. The state machine of traffic generation is shown in Figure 3.8. Figure 3.6 Node model in OPNET

23 85 Figure 3.7 The state machine diagram for the IP Module Figure 3.8 The state machine of traffic generation

24 86 The snapshot of the simulation screen for total cache replies sent and proposed L qm AODV routing is shown in figure 3.9 and 3.10 respectively. Figure 3.9 Snapshot of Simulation Screen for Total Cache Replies Sent Figure 3.10 Snapshot of the code for the Proposed L qm AODV routing

25 RESULTS AND DISCUSSION Simulations are run to investigate the protocol s performance under RWP when the pause time increases. The results present the performance of the protocol in the Table 3.2. Table 3.2 Packet Delivery Ratio for varying Node Pause Time Node Pause Time ( in second) Packet delivery ratio AODV VO-AODV L qm AODV Table 3.2 gives the result of PDR and it is observed that the PDR increases with the increase in pause time for both VO-AODV and L qm AODV. The performance of L qm AODV improves by 1.3% when compared to AODV and by 0.79% when compared to VO-AODV when node pause time is 20 sec. Similarly the performance of L qm AODV improves by 2.22% when compared to AODV and by 0.36% when compared to VO-AODV when node pause time is 100 sec. Table 3.3 tabulates the End to End Delay. Table 3.3 End to End Delay for varying Node Pause Time Node Pause Time End to End Delay in second AODV VO-AODV L qm AODV

26 88 Table 3.3 gives the result of end to end delay for pause times varying from 20 to 100 sec. It is observed that the end to end delay decreases with the increase in pause time for both VO-AODV and L qm AODV. The end to end delay of L qm AODV is less by 5.98% when compared to AODV and by 0.03% when compared to VO-AODV when node pause time is 20 sec. Similarly the end to end delay of L qm AODV is less by 8.01% when compared to AODV and by 2.07% when compared to VO-AODV when node pause time is 100 sec. Table 3.4 tabulates the Jitter for the network. Table 3.4: Jitter for varying Node Pause Time Node Pause Time Jitter in second AODV VO-AODV L qm AODV Table 3.4 gives the result of Jitter for pause times varying from 20 to 100 sec. It is observed that Jitter decreases with the increase in pause time for all variations of AODV simulated. Jitter of L qm AODV is less by 55.14% when compared to AODV and by 19.71% when compared to VO-AODV when node pause time is 20 sec. Similarly Jitter of L qm AODV is less by 13.94% when compared to AODV and by 2.45% when compared to VO- AODV when node pause time is 100 sec. L qm AODV has least Jitter. It can be deduced from the above tables of the simulation results of PDR, End to end delay and jitter that the performance of the network improves with the proposed enhancement of the AODV protocol. The

27 89 incorporation of the link metrics for routing has positive effect on the performance with increase in PDR and decrease in end to end delay and Jitter. The same setup was used with Node pause time of 100 for finding route discovery time, total route cache sent and total packet dropped for AODV, VO-AODV and L qm AODV. The simulations were run for 600 sec. Table 3.5 shows the simulation results. Table 3.5 Route Discovery Time Simulation time (sec) AODV VO-AODV L qm AODV #N/A

28 90 Table 3.6 Total Route Cache Sent Simulation time(sec) AODV VO- AODV L qm AODV

29 91 Table 3.7 Total Packet Dropped Simulation time(sec) AODV VO AODV L qm AODV From Tables , it is observed that the route discovery route time for the proposed VO-AODV and L qm AODV is very less when compared

30 92 to classical AODV. Though the total route cache sent is high for the proposed routings, the total packet dropped is considerably less than that of AODV. Experiments we also conducted by increasing the number of nodes. Table 3.8 tabulates the obtained outputs. Table 3.8 Results obtained for different number of nodes Packet Delivery Ratio Number of Nodes AODV VO-AODV L qm AODV Number of Nodes End to End Delay (in seconds) Number of Nodes Jitter (in Seconds) From table 3.8 it can be concluded that the proposed algorithm scales will as the number of nodes is increased. 3.7 SUMMARY Dynamically limiting the routing control overheads based on the network topology improves the packet delivery of the network. In this chapter, it is proposed to investigate the performance of a highly mobile network using

31 93 AODV routing protocol under different node pause time and propose an enhanced routing algorithm Varying Overhead Ad hoc On Demand Distance Vector (VO-AODV) routing protocol. Simulations were run and the proposed routing was compared with AODV and L qm AODV. An improvement in packet delivery ratio and end to end delay is observed in the proposed VO- AODV. In this study, it was proposed to improve the link quality by incorporating a link quality metric with ad hoc on demand distance vector routing protocol. A new link quality metric is defined to enhance AODV routing algorithm so that it can handle link quality between nodes to evaluate routes. Simulations were run and the proposed routing was compared with AODV. An improvement in packet delivery ratio is observed in the proposed LQ- AODV. Route discovery time is lower and the packet dropped is also considerably reduced for the proposed routing. Further work needs to be carried out to reduce the end to end delay.