Proactive Distance-Vector Multipath Routing for Wireless Ad Hoc Networks

Transcription

1 Proactive Distance-Vector Multipath Routing for Wireless Ad Hoc Networks Ralph Jansen, Sven Hanemann and Bernd Freisleben Department of Mathematics and Computer Science, University of Marburg Hans-Meerwein-Str., D-353 Marburg, Germany ABSTRACT Routing in wireless ad hoc networks of mobile nodes is complicated by the fact that the transmission ranges and the communication bandwidth is limited, and that the network topology is highly dynamic due to continuously moving nodes. In this paper, a new approach is presented to equip proactive distance-vector routing algrithms with the capability of using multiple paths to each target. The basic idea of our multipath routing proposal is to split up a path between a source and a target node into two paths at every forwarding node. In contrast to other multipath approaches, our solution uses already available topology information and thus does not require any additional routing messages to be sent. The benefits of our approach with respect to load distribution, bottleneck avoidance, fairness and communication breakdowns are demonstrated via simulations. KEYWORDS wireless networks, ad hoc networks, routing, multipath routing Introduction Wireless ad hoc networks consist of an ensemble of mobile nodes operating in a particular area without using any existing infrastructure. Each mobile node acts as an intermediate router forwarding messages received by other nodes. Thus, a wireless ad hoc network is only operational if nodes offer their forwarding capabilities to other nodes. The special conditions of wireless communication like limited transmission range, limited bandwidth and possible interference require dedicated routing algorithms that take these conditions into account. Routing protocols for wireless ad hoc networks can be broadly classified into reactive and proactive algorithms. Reactive routing algorithms rely on flooding to establish new routes that replace invalid routes due to node movement. Proactive routing algorithms usually constantly update routing tables among nodes. Both methods consume a certain percentage of the available bandwidth for routing purposes, which increases with node movements. Existing reactive routing algorithms like DSR [] and AODV [] invoke their route determination procedure only on demand through a query/reply approach. They have been optimized by computing multiple and link disjoint paths during the initial path finding process [7, 5] to counter the increasing bandwidth demands caused by route finding and establishment for rising node movement speeds. If multipath routing is used in reactive routing algorithms, there will be a basic advantage: Since routes are calculated on demand every time when a new route must be determined, the calculation of additional routes towards the same target increases the number of messages for route calculation required anyhow only slightly. Therefore, it is reasonable to calculate all available routes within one search request and use them as long as they are operational. Another approach [3] is to add proactive route maintenance and selection methods to a reactive routing protocol like DSR to reduce the number of broken paths. However, bandwidth consumption is increased with this approach. Proactive routing algorithms like DSDV [] maintain routes between nodes all the time. In fact, most proactive protocols try to maintain a shortest path to each destination all the time. This is achieved by continuously monitoring the network topology. In contrast to reactive algorithms, proactive approaches are capable of repairing a broken route within short time, due to the continously collected network topology information. Several proposals to use multiple paths in proactive algorithms have already been presented [4, 3, 6]. In the most advanced of these approaches [4], distance vector routing is extended to offer the computation of all possible alternative paths with instant loop freedom. In this paper, we present a new approach to add a multipath capability to proactive distance vector (DV) routing algorithms. Such routing algorithms are well suited for wireless networks [8,, 6]. The basic idea of our multipath proposal is to split up a path between a source and a target node into two paths at every forwarding node of the path (if the network topology offers sufficient alternatives), resulting in multiple paths between source and target. Whenever multiple paths are available, the forwarded data packets are later randomly distributed to each available path. This prevents the cost of additional messages

2 for load distribution, and still enables a fair load distribution in the long run. Thus, in contrast to the approach proposed in [4], our solution offers multipath routing based on the already available topology information, which does not require any additional routing messages to be sent at all. Just one additional step must be added to the processing of routing update messages to obtain an alternative packet forwarding possibility at each node. This minimizes bandwidth consumption and is thus a major advantage in wireless networks with battery powered nodes. For this reason, loop protection is provided by our proactive distance-vector routing algorithm [6] instead of building it into the multipath extension. Using simulations, we will demonstrate the benefits of the proposed multipath routing approach with respect to load distribution and communication breakdowns. The paper is organized as follows. Section presents an overview of our proactive distance-vector protocol, the tree exchange routing algorithm (TERA) and describes how the proposed strategy can be realized. Section 3 discusses the performance results obtained from a series of simulations regarding load distribution. Section 4 presents additional simulations to analyze the error behavior of multiple path routing. Section 5 concludes the paper and outlines areas for future research. The Tree Exchange Routing Algorithm The tree exchange routing algorithm (TERA) [6] is based on asynchronous distributed distance vector routing but uses several additional tables to allow path reconstruction. This avoids the count to infinity problem which causes a very slow adaptation to new network topologies and forbids the use of simple distance vector algorithms including the standard routing information protocol (RIP) [] in networks with fast topology changes. Figure shows the advantage of tree based routing. The path from any destination i to root A is stored in the. Any path can be backtraced to the root using these entries, enabling the detection and avoidance of any loop. To describe TERA, we assume that there is a network of nodes, each having an unique identifier k. These nodes are able to communicate with each other via links. The links are assumed to have a cost which is also called distance. The distance between a source and a destination is given by d ij and must be positive. Nodes with d ij < are called neighbors. If there is no direct way of communication between nodes i, j, the distance is assumed to be predecessor entries V A i infinite d ij =. The distance of a node to itself is assumed to be zero: d ii =.. Data Structure The status of a node with an unique identity k is defined by the following tables: A E B 4 3 F H C G Table entries of A i Di A Ni A Vi A A - - B B A C 4 E F D 5 E C E E A F 3 E E G 3 E E H E E Figure. Path recovery in tree exchange routing The routing table Di k, showing the best available distances to destination i. The successor table Ni k, showing the id of the neighbor which is used to forward to destination i. The predecessor table Vi k, showing the predecessor node of the chosen shortest path to i. There are two further tables to store all collected information available by messages coming from neighbors. These tables are later used to calculate the three routing tables mentioned above: The neighbor distance table NDij k shows the best available distance to destination i offered by neighbor j. The neighbor predecessor table NVij k shows the predecessors in the shortest path to i offered by node j. Table N i can be recalculated by backtracing all paths through V i, so that table N i does not need to be forwarded to neighbors.. Initialization All communications between nodes are described in an event-based manner. The state of any node is described by Di k(t),nk i (t),vk i (t),ndk k ij (t) and NVij (t). At startup t =each node initalizes its tables: Di k() := i, k i k, and Dk k := k D

3 N k i () := none i, k Vi k() := none i, k NDij k () := i, j, k NV k ij () := none i, j, k.3 Updating Neighbors After initialization, the iteration is started. In the first step, all nodes send the tables Di k, V i k to their neighbors. At startup, these tables contain only one valid element, the sending node itself. Each node stores the received information in the tables NDij k k and NVij. If node k receives tables Dj i (t ),V j i (t ) from neighbor j containing the minimum spanning tree used for routing by neighbor j, the tables of k are updated as follows. First, all old entries have to be deleted: NDij k (t) := i NVij k (t) := none i After that, the new tree is inserted: All distances reported by neighbor j must be increased by the distance from k to neighbor j: ND k ij (t) := Dj i (t ) + d kj i. The predecessors remain unchanged NVij k j (t) := Vi (t ) i. After that, a predecessor entry must be corrected. This is necessary because the root of a received minimum spanning tree has no predecessor entry. But at node k the new root of all received trees is node k: NVjj k (t) := k Finally, node k recalculates a new minimum spanning tree using the information stored in NDij k k (t) and NVij (t). The new minimum spanning tree is stored in tables D i k(t), Ni k k (t) and Vi (t). If a calculation leads to different tables compared to the results from the previous iteration, the tables D i k(t), Vi k(t) must be sent to all neighbors which are {i d ki < }. All distance vector algorithms use this iteration process which causes information distribution in a step by step manner. With each iteration, the information about remote neighbors travels one hop forward through the network. Due to the recalculation in each node, only important information will be sent to neighbors; this is the first step to bandwidth efficiency in routing. It is not necessary to always resend a full minimum spanning tree if an update occurred. There are algorithms available to reduce update messages to minimal sizes [9] and still guarantee consistency of trees among the communicating nodes. However, a description of message compression is beyond the scope of this paper..4 Calculation of Minimum Spanning Trees Recalculation of the minimum spanning tree is done with an adapted shortest path algorithm of Dijkstra []. Every node k has a collection of reported minimum spanning trees of its neighbors stored in table NDij k k and NVij. The trees have been altered during reception to be subtrees under the root of node k. The algorithm of Dijkstra can be immediately applied to extract the minimum spanning tree regarding node k. The shortest path algorithm is executed at each node. Since all calculations are done at one point in time, indices regarding status t are omitted. First, the tables Di k, N i k, V i k of node k are cleared: Di k := i Ni k := none i Vi k := none i Table Di k lists the estimated distances to all destinations. These estimations may change during calculation if a better path to a certain destination is found. All nodes with unchanged distances are members of a list of permanent nodes P k. The algorithm also uses a candidate list C k containing the identity of all nodes which are candidates for becoming permanent. At start, the distance of the root node k is set to zero Dk k := and P k := {k}. The list of candidates is filled with the identities of neighbors of node k: C k := C k {i d ik < } and the distance estimation is set to all existing links of node k: Di k := d ik {i d ik < }. The successors are set to the neighbors Ni k := i {i d ik < }. The predecessors are set to k: Vi k := k {i d ik < }. The calculation of the minimum spanning tree is performed in a loop until there are no more nodes which can become permanent: the candidate with the minimal distance offer is searched BD k := min[d k i ] {i i Ck }, BI k := is the identity of the node with the minimal distance BD k. the best candidate is made permanent P k := P k {BI k } the candidate is removed from the candidate list C k := C k \{BI k } all successors of BI k become candidates C k := C k {i i/ P k and NV k the distance for these new candidates must be set D k i := DV k i (N k BI k ) {i i/ P k and NV k

4 the successors for these new candidates must be set N k i := N k (BI k ) {i i/ P k and NV k the predecessors for these new candidates must be set V k i := NV k i (N k BI k ) {i i/ P k and NV k After having executed this loop, a new minimum spanning tree regarding node k is available in tables D i k(t), Ni k(t), V i k (t). Now, the new tables are compared to the tables of the previous calculation to check whether the distance of nodes or their position within a tree has changed..5 Update Criteria With unrestricted shortest path calculation, the tables Di k k (t) and Vi (t) must be sent to all neighbors if at least one of the following criteria is true: i : D k i (t) Dk i (t ) i : N k i (t) N k i (t ) i : Vi k (t) V i k (t ) () Updates are optimized by changing these criteria, thus not allowing every small change to be forwarded immediately. Consequently, updates may be limited to a threshold D which defines the maximum tolerable change in distance that can be suppressed. Thus, with reduced path optimization the tables Di k k (t) and Vi (t) must be sent to all neighbors if at least one of the following criteria is true: i : Di k(t) Dk i (t ) Di k(t) > D i : Ni k (t) Ni k (t ) () The criteria i : Ni k(t) N i k (t ) remains unchanged because any variation in N i k is a substantial tree modification that cannot be ignored. This term also guarantees that information about new or vanished nodes are immediately forwarded to neighbors..6 Route Maintenance There are two major events that must be handled by a routing algorithm during network operation. A routing algorithm must be able to include new destinations into the routing tables and delete lost destinations from them..6. Adding Nodes If a new neighbor is detected by node k, some corrections at NDij k k and NVij are required to integrate the new link into route calculation. First, the new neighbor with identity n must be inserted into the neighbor distance table with ND k nn := d kn, and a predecessor must be set to link this neighbor as a new subtree with NV k nn := k. A new minimum spanning tree must be calculated in this case, as described in section.4. If the new neighbor offers some better paths, the check of the update criteria described in section.5 will be positive, and this new information is sent to all neighbors..6. Deleting Nodes A connection loss from node k to a neighbor n will change the link cost d kn to infinity. Node k must update its tables to check whether current routes include forwarding to the unreachable neighbor. Table NDin k must be set to iand table NVin k must be set to none i. Then, a new minimum spanning tree is calculated by node k as described in section.4. If the update criteria check described in section.5 detects that routes must be corrected, the neighbors are updated with this information..7 Extensions for Multipath Routing To add the multipath capability to the algorithm described above, an additonal forwarding table must be added to the data structure: the alternative successor table ANi k, showing the id of the neighbor which is used to forward to destination i via an alternative path. Whenever a neighbor j sends an update to node i, an additional computation step must be performed after the recalculations of routing tables described in section.4 have taken place to find alternative paths. First, all destinations which are marked as unreachable in the first routing table also get marked as unreachable in the alternative table: AN k i = none i N k i = none After that, table NDij k is searched for all targets which are reachable in the first table. If the distance information stored in NDij k offers the same path lengths as the primary distance table Di k, neighbor j is used for alternative forwarding, otherwise the alternative path is marked as unusable: AN k i = { j j :(j N k i ND k ij = Dk i ) none otherwise This extension will detect one alternative path with the same distance as the primary path. The exclusive use of paths with the same distance as the primary path may sound as a hard limitation, but this limit is a very effective protection mechanism against routing loops, and this mechanism

5 does not require any additional messages. A detailed analysis of routing loop protection in multipath routing can be found in [4]. To forward a packet to destination i, the routing algorithm will check whether alternative paths are available. One path is available for destination i if Ni k none and an alternative path is available if ANi k none. If only one path is available, the packet has to be sent to the next node (i.e. Ni k ). If an alternative path is available, the next hop will be chosen randomly. Therefore, outgoing packets will be split into two paths, one half will be sent to Ni k and the other half to ANi k. 3 Analysis of Load Distribution Number of pakets Load 8 9 To get a better understanding of the possible degree of load distribution for routing algorithms with and without a multipath extension, we performed a series of simulation runs with our wireless network simulator [, 5, 4]. The simulated network is a grid of x nodes, as shown in figure. This (theoretical) scenario is well suited for a basic analysis, because a grid offers many paths with equal length for load distribution. During the simulation, we noticed that any movement of nodes will automatically lead to some kind of load distribution, because nodes swapping position will also swap their communication tasks. Thus, any movement of nodes is not allowed in this first simulation scenario, to keep the analysis restricted to load distribution through routing only. In later simulations we will analyze the duration of communication breakdowns which undoubtly are influenced by node movements, so the simulations in section 4 will be performed with node movements included. S R Figure 3. Load distribution without multipath routing Load Number of pakets Figure 4. Load distribution with multipath routing S Figure. Network topology During each simulation run two connections are set up: the first one sends. packets from the upper left corner to the lower right corner, while the second one sends. packets from the upper right corner to the lower left corner. The routing algorithm without the multipath option chooses one path for each connection, as marked in R figure. The simulation setup enforces that there must be one point in the network (at least one node) where the two connections have to cross each other. In this simulation run, the routing algorithm calculates paths which overlap at four nodes near the upper left corner. The next two figures present the results of our load analysis with and without multipath routing. To visualize the different network load of the nodes, we have chosen a three-dimensional chart. The x grid of nodes is placed on the base floor and the height of each node represents the network load of this node as the total number of forwarded packets during the entire simulation run. The results of the first simulation run without the multipath option is shown in figure 3. As stated above, there are four nodes near the upper left corner, each of which is part of both communication links and must forward the maxi-

6 mum of. packets. These four nodes are the bottleneck of this communication scenario. Each node can only provide a fixed forwarding capacity to the network, and thus the four nodes can only provide 5% of their forwarding capacity to each of these two connections. The second simulation run was performed with the same parameters but the multipath capability of the routing algorithm was switched on. Figure 4 shows the improved load distribution. There are no more bottlenecks, and the nodes with maximum network load are the corners of the grid: the source and the target of both connections. The path of each connection is split up at each step, resulting in perfectly distributed load among the network. The fairness of load distribution in wireless networks is an open field of research. Ad hoc networks are assembled from battery powered mobile nodes, thus packet forwarding is limited by the available battery power. Multipath routing with additional algorithms to get a guaranteed fair load distribution will need additional messages, which counteracts the idea of saving battery power. Our approach offers a simple solution to this problem. If the network topology offers multiple paths with equal length to a target node, the forwarding load is distributed equally to the available paths. The limitation to equal length will lead to improved fairness, because the use of paths with increased length will put additional load to the network by enforcing (otherwise unnecessary) nodes to participate in the forwarding process. All nodes will additionally profit from this approach by avoiding bottleneck nodes which tend to be central nodes within the network. Without load distribution, they will quickly loose their battery power, leading to longer routes which are required to surround the center of the network. 4 Analysis of Communication Breakdowns The last simulation run was performed to demonstrate the different behavior of communication breakdowns with and without multipath routing. The experiments were conducted with the following parameters: a network of 5 nodes transmission ranges of meters each nodes randomly moving on a field of x meters simulation runs with average node movement speeds ranging from. to meters per second one hour simulated movement and network activity the TERA routing algorithm with and without multipath extensions was used beaconing for neighbor detection at a rate of 6 seconds The first simulation run analyzed the number of packet losses with and without multipath routing. A very interesting fact is that the total number of packet losses is equal in both simulations, regardless of multipath usage. This can be explained by the fact that routing in general will not change the probability of packet loss for any transmission between neighbors, so the loss probability is always constant. avg. comm. breakdown times in s TERA without Multipath TERA with Multipath movement speed in m/s Figure 5. Duration of communication breakdowns In a second experiment, we analyzed the average duration of a communication breakdown during network activity. The results of these simulations show a significant difference between routing with and without multipath usage. Figure 5 presents the average duration of communication breakdowns for these simulations. Single path routing shows a significantly increased breakdown duration. If a route breaks down, a single path routing algorithm will need some time until it can provide a new route. Meanwhile packets are lost, leading to a large breakdown duration. Multipath routing splits up its packets to different paths. A route breakdown of one path will result in loosing only the number of packets which has been sent to the broken path. Therefore, communication will suffer from increased packet loss, but communication is still possible. All error recovery algorithms are built to deal with this kind of network error, e.g. all implementations of TCP will resend lost packets until a data transfer is completed. Without the use of multipath routing an error correction mechanism like TCP has to stop its activity until the route has been recovered. With multipath extensions, a communication can be used as long at least one alternative path is available. The error correction procedure automatically resends lost packets. This will result in increased message delay, but not in a full communication breakdown.

7 5 Conclusions This paper presented an extension to standard distance vector routing algorithms based on using multiple paths. We introduced the proactive TERA routing algorithm and explained the necessary modifications to enable multipath routing. The proposed extensions do not require any additional messages, so the multipath capability can be set up at almost no additional cost. The benefits of multipath routing for wireless ad hoc networks were analyzed via simulations. In a first step, we performed experiments to show the effects of multipath routing with respect to load distribution, bottleneck avoidance and fairness. In a second step, we showed the improved performance of multipath routing with respect to communication breakdowns. There are several areas for further research. For example, an important issue are especially designed error correction algorithms for optimal data transfer via multiple paths. Another problem worth investigating is whether several (instead of two) paths are beneficial in particular scenarios. Finally, additional simulations of different network configurations, movement patterns and transfer scenarios are required to analyze the effects of multipath routing in more detail. References [] David A. Maltz David B. Johnson. Mobile Computing, T. Imielinski and H. F. Korth edt., chapter Dynamic Source Routing in Ad Hoc Wireless Networks, pages Kluwer Academic Publishers, Boston, 996. [] Bernd Freisleben and Ralph Jansen. Analysis of routing protocols for ad hoc networks of mobile computers. In Proceedings of the 5th IASTED International Conference on Applied Informatics, pages Iasted-Acta Press, 997. [3] T. Goff, N.B. Abu Ghazaleh, D. Phatak, and R. Kahvecioglu. Preemptive routing in ad hoc networks. In Proc. of ACM SIGMOBILE, pages 43 5, Rome,. [4] R. Jansen. Routing Algorithms for Wireless Ad Hoc Networks with Cooperating Mobile Nodes (in German). PhD thesis, Department of Electrical Engineering and Computer Science, University of Siegen,. [5] Ralph Jansen. Simulating adaptive routing in highly dynamic wireless networks. In Proceedings of the 998 European Simulation Multiconference, pages , Manchester, United Kingdom, June 998. Society for Computer Simulation (SCS). [6] Ralph Jansen and Bernd Freisleben. Bandwidth efficient distance vector routing for ad hoc networks. In Proceedings of the Wireless and Optical Communications Conference (WOC), pages 7, Banff, Canada, June. IASTED, Iasted-Acta Press. [7] M. K. Marina and S. R Das. On-demand multipath distance vector routing for ad hoc networks. In Proc. of the International Conference for Network Protocols (ICNP), pages 4 3. Riverside, USA,. [8] Shree Murthy and J.J. Garcia-Luna-Aceves. An efficient routing protocol for wireless networks. In Mobile Networks and Nomadic Applications (NOMAD), Special issue on Routing in Mobile Communication Networks, volume /4, 996. [9] Shree Murthy and J.J. Garcia-Luna-Aceves. An efficient routing protocol for wireless networks. In Mobile Networks and Applications, Special issue on Routing in Mobile Communications Networks, volume /, pages 83 97, 996. [] Chalres E. Perkins and E. M. Royer. Ad hoc ondemand distance vector (AODV) routing. Proc. of the Second Annual IEEE Workshop on Mobile Computing Systems and Applications, pages 9, February 999. [] Charles Perkins and Pravin Bhagwat. Highly dynamic destination-sequenced distance-vector routing for mobile computers. In Proceedings of the Symposium on Communication Architectures and Protocols, pages ACM SIGCOMM, 994. [] Martha Steenstrup. Routing in Communication Networks. Prentice Hall, Englewood Cliffs, New Jersey, 995. ISBN [3] Srinivas Vutukury and J. J. Garcia-Luna-Aceves. A simple approximation to minimum-delay routing. In SIGCOMM, pages 7 38, 999. [4] Srinivas Vutukury and J. J. Garcia-Luna-Aceves. MDVA: A distance-vector multipath routing protocol. In INFOCOM, pages ,. [5] J. Wu. An extended dynamic source routing scheme in ad hoc wireless networks. In Proceedings of the 35th Hawaii International Conference on System Sciences, pages 96 97, Hawaii,. [6] William T. Zaumen and J. J. Garcia-Luna-Aceves. Loop-free multipath routing using generalized diffusing computations. In INFOCOM (3), pages 48 47, 998.