An Adaptive Routing Strategy Based on Dynamic Cache in Mobile Ad Hoc Networks*

Transcription

1 An Adaptive Routing Strategy Based on Dynamic Cache in Mobile Ad Hoc Networks* YueQuan Chen, XiaoFeng Guo, QingKai Zeng, and Guihai Chen State Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, China Abstract. The dynamic changes of the topology caused by the movement of nodes makes routing become one of the key problems in the mobile Ad Hoc Networks (MANET). So how to optimize routing becomes a hot and difficult topic, among which optimizing routing cache is one of the key techniques. In this paper, we propose an adaptive dynamic cache routing (DCR) strategy based on DSR (Dynamic Source Routing), which can evaluate the link expiration time rapidly. The experimental results show that the DCR has considerable improvement in control packets, packet delivery ratio, packet drops and end-toend average delay in the MANET. 1 Introduction Mobile Ad Hoc Networks (MANET) are self-organized wireless networks which are multi-hops and without infrastructure [1]. Due to the absence of infrastructure, nodes can move frequently, and the topology can change dynamically. Thus, research on routing becomes a difficult and hot topic [2]. Normally, there are two main routing strategies: proactive routing and reactive routing. Proactive routing is implemented by exchanging routing tables, such as DSDV [3], WRP [4], etc. Reactive routing is ondemand routing, such as DSR [5], AODV [6], TORA [7], etc. It has been shown that reactive routing is more suitable for MANET than the proactive one [8]. In reactive routing, as the on-demand routing is based on request/reply recycle, the routing discovery cost is large, which will decrease the performance of network. If many nodes send requests at the same time, networks will congest easily. In the MANET, researchers use three main methods to decrease discovery cost: 1) Optimizing cache (such as DSR, AODV, etc). Every node has a cache to store the path from itself to destination. When it receives the route request and has a path to the specified destination, it will reply the corresponding path to source node from its cache, and if one link breaks, it can switch to an alternative path so that it can decrease the route * Supported by NSF of China (No ), Hi-Tech Program of china (2002AA141090), National Grand Fundamental Research 973 Program of China (No.2002CB312002) and TRAPOYT Award of China Ministry of Education. J. Cao et al. (Eds.): ISPA 2004, LNCS 3358, pp , Springer-Verlag Berlin Heidelberg 2004

2 358 Y. Chen et al. request cost and error paths, and consequently reduces the end-to-end delay. 2) Local flooding (such as LAR [9], ZRP [10], etc). The flooding broadcast locally will reduce the discovery cost. 3) Multipath (such as SMR [11], AOMDV [12], etc]. Using multiple paths to send data parallel or concurrently and alternative path will reduce the number of requests. Cache routing strategy, such as DSR and AODV, can reduce the discovery cost. But there are some shortcomings, for example it hasn t an efficient cache strategy and efficient automatic link expiration mechanism, so there are many researches on it. Hu. et al [13] proposed an on-demand routing protocol on cache strategy in MANET, which limited their study on expiration mechanism to a fixed level of node mobility, while a static optimal lifetime is not suitable for high mobility. Liang [14] proposed a best static optimal link expiration time based on numeric method, but it is not suitable for high mobility either. Valera et al [15] proposed a cooperative cache strategy, but it doesn t consider link expiration. Cao et al discussed how to improve performance of network using cache in application layer [16], but it is unsuitable for cache in network layer. In this paper, we propose an adaptive dynamic cache routing strategy (DCR) based on DSR. According to DCR, the network performance can be improved by using the link-based cache organization, source or intermediate nodes caching efficient paths, and by evaluating link life-time and setting the link timeout automatically to reduce error packets and decrease end-to-end delay. Compared with DSR, DCR can reduce control packets by 10%-50%, improve packet delivery ratio by 10%-20%, decrease 20%-60% packet drops and end-to-end delay by 50%-70%. This paper is organized as follows. Section II introduces the DSR protocol and cache problem. Section III describes the DCR link organization, cache strategy and the link expiration mechanism. Section IV analyzes the DCR Protocol. Performance evaluation by simulation is presented in Section V and conclusions and future work are given in Section VI. 2 Introduction to DSR and Cache Problem DSR is an on-demand reactive routing protocol which is based on request/reply method. Because DSR is a classical protocol which has better performance in reactive routing [8], we take it as a reference protocol to propose our strategies and mechanisms (DCR) which are also suitable for other reactive routing protocol. 2.1 Introduction to DSR DSR routing protocol has two main phases: routing discovery and routing maintenance. Routing Discovery Firstly, the source node broadcasts flooding route request to destination. After an intermediate node receives the request, it will check its cache to see whether it has paths to the destination. If it has a path to the destination, it will reply the corre-

3 An Adaptive Routing Strategy Based on Dynamic Cache 359 sponding path to the source node; otherwise it will put its address into route request packet header, and broadcast the route request again. After the route request reaches the destination, the destination extracts the efficient information from route request packet and reply to source node through the route request path. Then intermediate node receives the route reply packet and puts the efficient routes into its cache. Afterwards, it forwards this route reply packet to upper node. When the route reply packet reaches the source node, the source node collects these paths and put them into its cache for the purpose of sending data later. Routing maintenance If a node detects some broken links through MAC layer, it will judge whether its salvage bit is set or not. When the bit is not set, it will search another path leading to the destination and forward the data packet through it. Otherwise, it will drop this data packet and informs the upper node and source node to process the broken link. 2.2 DSR Cache Problem As DSR cache is based on path organization, the intermediate node or source node will not process anything while caching the route reply packet. Meanwhile its cache has no automatic link expiration either and will delete the error link when receiving the error packets. So DSR cache is easy, but it has some problems as follows: Inefficient Cache Organization: In DSR, it will delete the whole path which includes error links when receiving the error packets even though there may be only one link broken in this path and other links are also existed, which will result in that the path organization can t use the link information efficiently. Easy Cache strategy: if intermediate nodes or source node receive route reply packets, it will cache this path without any further process. But in MANET, the longer the path is, the larger the broken probability of this path will be. No automatic link expiration mechanism: In DSR, it take the link for existence until receiving error link information. But the links are broken and connected dynamically in MANET. So if there is no automatic link timeout, it will increase the end-to-end delay and the number of error packets. Due to the above mentioned reasons, we propose a Dynamic Cache Routing strategy which is based on link organization, selective cache strategy and automatic link expiration mechanism. 3 DCR Protocol Description DCR, based on DSR, differs from DSR mainly in three aspects from DSR: link organization, cache strategy and auto link expire mechanism.

4 360 Y. Chen et al. 3.1 DCR Link Organization In DSR, its cache organization is based on path (Fig. 1). This organization is easy to manage, and its routes can be directly selected when needed. The key problem is the low efficiency. In this paper, we add some features, such as the link counter and time counter, into the link organization described in [13]. The link counter indexes the numbers of one link in its cache. If a new link is added, we will initiate its link counter to one, and increase its link counter by one if the same link is added again and decrease its link counter by one when link expiration time is triggered. When receiving some link error packet or its link counter decreasing to zero, we will delete the link from the cache. The time counter indexes the link expiration which will be described in section 3.3. After these processes, we can use the link efficiently. S A B D T1 1 C 11 S 2 A B 1 D T1 1 1 S A C D T2 T2 Fig. 1. Path-based Cache Organization Fig. 2. Link-based Cache Organization For example, in the path-based organization (Fig. 1), if link B D is broken, the cache has no path to the destination T1 which results in route rediscovery and the cost increases. But in the link-based organization (Fig. 2), we can use BSF [17] (Bread First Search) to compute the shortest path from the source node to destination T1 in network topology. Thus we can achieve the path S A C D T1 and reduce the number of route discovery, decrease control packets and improve cache link efficiency greatly. 3.2 DCR Path Cache Strategy The source node and intermediate node cache strategy have been modified as follows. When intermediate node receives route reply packet, the path with the distance from this node to destination node less than 1 will be chosen to be cached based on local principle. In this way the probability for the error path can be decreased by avoiding too long path. When the intermediate node receives the route request packets, it will do the following process: if the minimum hops from the source to the intermediate node plus the minimum hops from the intermediate node to the destination already available are less than 2, then it will reply the corresponding path to source node. When the source node receives route reply packets, if this route reply packet to desti-

5 An Adaptive Routing Strategy Based on Dynamic Cache 361 nation is the first one, then cache it directly, otherwise we cache it if the route reply hops are less than 3. The 1 1,, 2 3 is constant number Adaptive Link Expiration Mechanism For two nodes at one link, if one node leaves the covering region of the other node, the link will be broken. Due to the nodes mobility, the link is broken and connected dynamically. But DSR does not consider these problems, and will not delete the broken link until it receives the error packet. This results in increasing the error packets and the end-to-end delay. Setting the link expiration time is very important: when the topology changes greatly (the pause time is shorter), if the link time is set too long, the error packets increase and the data are retransmitted, and, consequently, the delay increases; when the topology changes little (the pause time is longer), if the link lifetime is set too little, we can t use the link information efficiently, so we add an adaptive link expiration mechanism. In this paper, we propose the following method to evaluate the link time: When the topology changes greatly, the link is broken and connected dynamically. Suppose S n = Link.expire n - Link.start n, where the Link.start n is the starting time of link stored in the cache and the Link.expire n is the time of link whose link counter becomes zero or that receives the error packet which contains the error link information; LinkTime n is set to evaluate the link lifetime, Diff n is set to the difference of S n and LinkTime n, V n is set to variance, TimeOut n is set to the timeout of link, α, β, γ is constant number between 0 and 1. 1 Diff n = S n LinkTime n-1. (1) LinkTime n = α* LinkTime n-1 + (1 α) * S n (2) V n = β* V n-1 + (1-β) * Diff n (3) TimeOut n = γ *(LinkTime + V ) if (Diff 0) (4) n n LinkTimen Vn if (Diff < 0) When the topology changes little, that is when the pause time is larger than if we set the link expire time to related pause time, we can use the link efficiently and decrease the error packets. TimeOut = PauseTime + δ (5) The PauseTime is pause time of node in random WayPoint model [5], δ and δ is a constant. 1 1 Practical number will be discussed in section 5.

6 362 Y. Chen et al. 4 Analysis of DCR Protocol Lemmas 1. When the topology changes greatly, the formula (4) can converge to link time expiration rapidly. Proof. As the node mobility is random WayPoint model, LinkTime can be represented as an average exponent series [18], so LinkTime n can converge. We set it to L, and calculate the expectation value of the formula, so E(LinkTime n ) = α* E(LinkTime n-1 ) + (1 α) * E(S n ) E(LinkTime n ) = E(LinkTime n-1 ) = L (n ) E(LinkTime n ) E(S n ) (n ) Using the same treatment to formula (3), we can get: E(V n ) S n LinkTime n-1 Lemma 2. When the topology changes a little, formula (5) can use the link information efficiently. Proof. When the topology changes little, the probability of link broken is little. As we have observed (it will be discussed in section 5.2), when the topology changes little, the link expiration time is related to pause time greatly. For we want to use the link information efficiently and avoid sending data to the error link, we add δ to pause time. The simulation shows a better result. Lemma 3. The time complexity of DCR is O(N) and the space complexity is O(N), N = V, V is the set of mobile nodes. Proof. By using the link-based organization and the link counter, and applying the link graph to store the link information, so the space complexity is O (N). And by using the BFS to search the path from the source node to the destination node in the cache, the time complexity becomes O (N). Compared with DSR whose space complexity is O (K N), where K is average length of path, the space complexity of DCR is better than that of DSR. And as the time complexity of searching path in DSR is also O (N), both of them are the same. Thus it has been shown that DCR can converge to link lifetime and set the link expiration time more efficiently than DSR. 5 Performance Evaluation of DCR We use GloMoSim simulator [20] to evaluate the performance of DCR. In this simulation, the wireless bandwidth is 2Mbps, the transmit distance is 250m and the MAC layer is IEEE In regions, 50 nodes can move randomly, and the

7 An Adaptive Routing Strategy Based on Dynamic Cache 363 model mobility is random WayPoint model. In this model, the nodes are uniformly distributed, and when one node moves to one place, it will stay there for some time and move again. In our simulation, we set the min speed as 5m/s, the max speed as 10m/s, pause time from 0s to 300s, and interval of simulation as 30s, simulation time as 300s and 30CBR, and every CBR traffic as 1kb/2s. 5.1 Performance Criteria We evaluate the performance of DSR and DCR according to the parameters in [21]. Here, two important parameters of the packet delivery ratio and end-to-end delay are used for evaluating the performance of networks. The former one represents the capability of transmitting data, the latter represents the processing capability of packets. The control packet cost is also an important parameter. Due to the node mobility and network instability in MANET, we use the control packet to rediscover the route and maintain the route in on-demand routing algorithm. So we must decrease the control packets, including the route request packets, route reply packets and error packets. In our simulation, we use the ratio of control packets to the total received packets to evaluate the control packet cost, and the packet drops to index the case of packet dropping. In section 3.2, the 1 is 5, 2 is 10, 3 is In section 3.3, α is 0.625, β is And as the lifetime of link complies with exponential distribution, a better performance can be got when the value of γ is We set δ to 10s and to 210s. 5.2 Results and Analysis of Simulation In Fig. 3, as the pause time increases, the control packets of both DCR and DSR decrease. This phenomenon can be explained as follows. As the pause time increases, the whole network topology becomes more and more stable, causing the request packets and the control packets decrease. As a whole, the control packets, in the DCR is less than 10%-50% than that in the DSR, especially when pause time is shorter (pause time 60s is an abnormal case which will be discussed at the end of this section).because the link expiration time in DCR converges rapidly, the error packets decrease, too. But when topology changes greatly, the route requests increasing cause the control packets to increase. However, the control packet is still less than that of DSR by 10%; and when the pause time increases, the topology becomes stable and the DCR requests decrease. Therefore error packets decrease, which results in the control packets decreasing by 30%-50% than that of DSR. In Fig. 4, as the pause time increases, the packet delivery increase rapidly in DSR, while DCR delivery ratio keeps at 86%-92% in all time. And because the link expiration time in DCR converges rapidly, when pause time is 0s, DCR can also keep on high delivery ration. Therefore, the route can refresh rapidly, which can keep the link exist in packet transmitting. But in DSR, it doesn t consider the automatic link expiration, resulting in the link broken while transmitting the data and the packet delivery 2 1, 2, 3 is based on experience. 3 α, β is similar of setting the parameter of RTT in TCP.

8 364 Y. Chen et al. ratio decreasing. When the pause time is 60s, the packet delivery ratio decreases in both DCR and DSR. The reason is because of the network congestion; as the pause time increases, the delivery increase more rapidly, however, DCR increases 10% more than DSR in packet delivery ratio. As a whole, DCR increases the packet delivery ratio by 10%-20% than DSR. Fig. 3. Control Packets in DCR VS DSR Fig. 4. Packet Delivery in DCR VS DSR In Fig. 5, in DSR, as the pause time increases, the packet drops decrease. But in DCR, when the pause time is little, the packet drops keep small, because the link can be automatically broken, the topology can be rediscovered, thus the route is renewed. However, when the pause time is 60s, the probability of packet drops are higher caused by the network congestion. As a whole, DCR can decrease 20%-60% packet drops more than DSR. In Fig. 6, DCR can keep a lower delay all the time. When the pause time is little, due to node mobility and topology changes, the distance from source to destination is short, so the delay is decreased. However, when the pause time is larger, the topology changes very little, making the end-to-end distance and delay longer. But the delay still keeps at low values. This is because that DCR can auto-break the error link timely to avoid transmitting data through the error path, resulting in the decrease the end-to-end delay. But DSR dose not consider this case; the packets are transmitted through the error path, which results in the end-to-end delay increasing. As a whole, DCR can decrease the delay by 50%-70%. In general, when pause time is 60s, the network is congested, which increases DSR control packets, while that of DCR changes less. In this case, link can not be automatically broken timely. Therefore the packet delivery ratio decreases, error packets increase and end-to-end delay also increases. In other cases, DCR uses the efficient cache organization, auto link broken mechanism and efficient cache strategy to achieve less control packets, higher packet delivery, less packet drops and average end- to-end delay.

9 An Adaptive Routing Strategy Based on Dynamic Cache 365 Fig. 5. Drop Packets in DCR VS DSR Fig. 6. End-to-end Delay in DCR VS DSR 6 Conclusion and Future Work Due to node mobility and topology instability in MANET, optimizing cache can improve the performance of routing. In this paper, we propose an adaptive dynamic cache strategy (DCR), which is based on link organization cache, selective cache strategy and adaptive method to evaluate the link expiration time. Comparison of DCR with DSR using simulations shows that DCR can decrease control packet by 10%-50%, increase packet delivery ratio by 10%-20%, decrease packet drops about 20%-60%, and decrease end-to-end delay by 50%. Currently we are not clear about and will further study: 1) How to use cache error informing mechanism for decreasing the error packets. 2) How to use the reactive renewing route to cache the efficient path in advance for reducing the number of requests. 3) What is the quantified influence of cache on security and QoS. References 1. Z.J. Haas et al. Wireless Ad Hoc Networks. John Wiley, R. Ramanathan and J. Redi. A Brief Overview of Ad Hoc Networks: Challenges and Directions. IEEE Commun. Magzine, 40(5), C.E. Perkins and P. Bhagwat. Highly dynamic destination-sequenced distance-vector routing for mobile computers. In Proc. ACM SIGCOMM 94, T.W. Chen and M. Gerla. Global State Routing: A New Routing Scheme for Ad-hoc Wireless Networks. In Proc.IEEE ICC'98, IEEE Press, D. Johnson, D.A. Maltz and Y.C.Hu. Dynamic source routing in Ad hoc wireless networks. IETF Mobile Ad Hoc Networks Working Group, Internet Draft, work in progress, C.E. Perkins, E.M. Royer and S. Das. Ad-hoc on demand distance vector routing. RFC3561, July V.D. Park and M.S. Corson. A highly adaptive distributed routing algorithm for mobile wireless networks. In Proc. IEEE INFOCOM'97, IEEE Press, 1997.

10 366 Y. Chen et al. 8. J.Broch, D.A.Maltz, D.B.Johnson, Y.Hu, and J. Jetcheva. A performance comparison of multi-hop wireless ad hoc network routing protocols. In Proc. ACM Mobicom 98, ACM Press, Y.B.Ko and N.H.Vaidya. Location-aided routing (LAR) in mobile ad hoc networks. Kluwer Academic Publishers, 6(4), Z. Haas and M. Perlman. The zone routing protocol for ad hoc networks. Internet Draft, Work in Progress, March S.J. Lee and M. Gerla. Split Multipath Routing with Maximally Disjoint Paths in Ad hoc Networks. In Proc. IEEE ICC 01, IEEE Press, M. K. Marina and S. R. Das. On-demand Multipath Distance Vector Routing for Ad Hoc Networks. In Proc. ICNP 01, IEEE Press, Y.-C.Hu and D.B. Johnson. Caching strategies in on-demand routing protocols for wireless ad hoc networks. In Proc. ACM Mobicom 00, ACM Press, B. Liang and Z.J. Haas. Optimizing Route-Cache Lifetime in Ad Hoc Networks. In Proc. IEEE Infocom 03, IEEE Press, A. Valera, Winston K.G. Seah and S. Rao. Cooperative Packet Caching and Shortest Multipath Routing in Mobile Ad hoc Networks. In Proc. IEEE Infocom 03, IEEE Press, G.H. Cao, L.H. Yin and C.R. Das. Cooperative Cache-Based Data Access in Ad Hoc Networks. IEEE Computer, 37(2), IEEE Press, T.H. Cormen, C.E. Leiserson, R.L. Rivest, and C. Stein. Introduction To Algorithms (second edition). MIT Press, G.E.P. Box and G.M. Jenkins. Time Series Analysis forecasting and Control. Holden Day publisher, K.S. Trivedi. Probability and Statistics with Reliability, Queuing and Computer Science Applications. John Wiley & Sons, UCLA Parallel Computing Laboratory and Wireless Adaptive Mobility Laboratory. Glo- MoSim: A Scalable Simulation Environment for Wireless and Wired Network Systems S.Corson, J.Macker. Mobile ad hoc networking (MANET):Routing protocol performance issues and evaluation considerations. RFC2501, January 1999.