Field Based Interconnection of Hybrid Wireless Mesh Networks

Transcription

1 Institut für Technische Informatik und Kommunikationsnetze Field Based Interconnection of Hybrid Wireless Mesh Networks TIK Report 249 Rainer Baumann, Martin May, Bernhard Plattner Computer Engineering and Networks Laboratory Swiss Federal Institute of Technology ETH Zurich, Switzerland 3rd July 26 Abstract Hybrid Wireless Mesh Networks are a promising approach for inexpensive, ubiquitous Internet access. For realizing these networks, a scalable and robust routing protocol is required. In this paper we present a field based anycast routing protocol which bases on the ideas of temperature fields. The proposed protocol is specific to the presented application scenario and meets the stated requirements. The evaluation has been done by mathematical proofs and realistic simulation scenarios using real world city mobility maps extracted from a geographic information system and lifelike traffic models. 1 Introduction In recent years, the demand for ubiquitous communication and Internet access increased dramatically. Today one tries to meet this demand by deploying traditional wireless access point devices. Due to their limited coverage range, many access points are required to provide a good coverage of a large area. This is not really cost efficient. One solution to overcome this problem is to use relaying of other mobile devices for extending coverage. This can be implemented by a routing protocol that allows packets to traverse multiple hops to a close access point. This greatly expands coverage range of each access point while simultaneously reducing cost and simplifying deployment. This is the major idea of hybrid Wireless Mesh Networks (WMNs) [1]. In these networks a majority of the traffic is moving between the mesh nodes and the fixed infrastructure, as opposed to between the mesh nodes themselves such as in ad hoc networks. These hybrid WMNs can also be regarded as an alternative technology for the last-mile broadband Internet access. In WMNs access points are more frequently referred to as gateways. They are stationary, connected by wire to the Internet and have power supply. Thus they are reliable in contrast to wireless nodes participating in the mesh. They may move away or simply shut down. The problem we address in this paper is how to build a scalable, reliable and flexible routing protocol for the specific purpose of gateway interconnection in WMNs. This problem can be dived into two subproblems. First, how to find the route to a gateway and second, how to find the way back. Routing packets toward a gateway is similar to an anycast routing problem [2, 3] with a single service. This single service, the bridging to the Internet, can be modeled as a scalar field. In this field, the Gateways represent local maxima. From each mesh node, the field increases monotonic toward the local gateways. Thus a packet on the forward path simply has to be forwarded following the increasing gradient. Gateways are unlikely to disappear but links of mesh nodes break more or less frequently. Thus, it is more important to route packets over redundant areas with well meshed nodes instead of toward the

2 Figure 1: Hybrid Wireless Mesh Networks - Interconnection of a wireless mesh network with fixed infrastructure for accessing the Internet. closest gateway or toward the area with the highest density of gateways. The necessary information for constructing a scalar field can locally, proactively be exchanged between neighbors. Maintaining such a scalar field only requires few resources in every node. For the path back from a gateway to a mesh node, source routing [4, 5] can be used. The required routing information can be collected by every node traversing the forward path. This information is then stored in the gateways or at a routing server connected to them. Thus, a backward route is only available if the mesh node recently sent a packet to the Internet. This is no limitation, because the vast majority of communication is initiated by a mesh node. If a mesh node wants to act as a server, it any how has to register itself periodically in the Internet. This periodic registrations allows for updating the backward path. Thus mesh nodes are state less with respect to the backward path. For the forward path they just have to maintain a few local information. Only the gateways or the routing servers have to maintain a list of mesh nodes communicating over them. Therefore the proposed protocol scales. Summarizing, conceptually we propose to use a local, proactive anycast routing protocol for routing packets toward the gateways. For the way back, we suggest a source routing protocol which takes advantage of recorded routs from the forward path. We evaluated field based routing in detail with respect to validity, performance and scalability. We have mathematically proved that field based routing is loop free and routes packets toward the destination. In addition we show that the proposed protocol scales without any restrictions, convergence fast and is robust. Finally, we show its applicability in realistic scenarios based on a geographic information system. The rest of this paper is organized as follows. In the next section we describe the general problem of interconnecting hybrid WMNs. In section 3 we then explain the concept and protocol of Field Based Routing. Following we present our evaluations in section 4. Then we discuss our results and possible improvements in section 5 and highlight related work in section 6. Finally, we give a conclusion in 2

3 section 7. 2 Problem Definition Wireless networks can be operated in infrastructure or ad hoc mode. A combination of these modes allows for cost efficient extension of Internet connectivity over a wide area. Such a hybrid mode raises a routing and an addressing problem. Commonly, wireless networks are divided into two categories of operation. The first category form the infrastructure or access modes. In theses modes, wireless devices connect directly to a fixed, wired infrastructure as base stations or access points. The coverage of networks based on these modes is rather limited since wireless devices require a direct link to the infrastructure. Thus for a width coverage, a lot of expensive infrastructure is needed. (In the domain of WMNs we call this category infrastructure based meshing.) The second category of operation is formed by the self organizing, multi-hop ad hoc modes. In these modes, wireless devices communicate ad hoc with each other using other nodes for relaying their packets. This allows for cost efficient extension of the communication range of a wireless device over multiple hops. Thus if the density of participating devices is adequate, these modes allow for flexible and cost efficient communication between the devices in the network. But there is no connectivity to other networks, namely the Internet. (In the domain of WMNs we call this category client based meshing.) Today, a major goal of the wireless technology is cost efficient Internet connectivity with a width coverage. This is the motivation for combining the two categories of operation to a hybrid one. Looking from the side of infrastructure, the idea is to extend coverage over multiple hops. While looking form the multi-hop ad hoc side, the idea is to interconnect the autonomous network with the Internet. This is the major idea of hybrid Wireless Mesh Networks (WMNs) [1]. In theses networks the multi-hop ad hoc domain is interconnected with the Internet over gateways. The major challenge of this interconnection is how to solve the routing and addressing in the multi-hop ad hoc domain. For this paper we assume without restrictions, that all traffic is moving between the wireless devices and gateways. If two devices in the wireless domain wants to communicate directly with each other, they could do this over a server or proxy in the Internet. Alternatively, there is still the possibility to use a common MANET routing protocol as AODV [6] or others. The problem of routing between mesh nodes and gateways can be dived into two subproblems. The first problem is how to route packets toward a gateway, the forward path. This problem is similar to an anycast routing problem with a single service, the bridging to the Internet. For a mesh node it is not of interest which gateway relays its packets but that a gateway does it. The second problem is how to route packets back from a gateway to a mesh node, the backward path. This is a classical unicast routing problem. Different gateways have to route packets to different singel destinations. Beside this routing problem there exists also an addressing problem. In ad hoc networks IP addresses of nodes are usually used as unique identifiers without representing hierarchical topology information as in the Internet. This becomes a problem when interconnecting ad hoc networks with the Internet. Assume a mesh node requests a website from a server in the Internet. A request is forwarded from the mesh node to a gateway and from the gateway to the server. Then the server should send its answer back to a gateway which forwards the reply back to the mesh node. For the reply being routable in the Internet a destination IP address has to be used which also fits topologically. This problem has already been widely discussed in the literature [7, 8, 9, 1, 11, 12, 13, 14, 15] thus we will not discuss it in detail. Promising solutions for this problem base on MobileIP [16, 17] or Network Address Translation (NAT). For more 3

4 Figure 2: Routing in hybrid Wireless Mesh Networks consists of two subproblems: routing to the gateways and back. details please refer to the survey [18]. 3 Field Based Interconnection of Hybrid Wireless Mesh Networks Field Based Routing (FBR) is based on the concept of fields from physics. In this section we explain the underlying concept and our adaption of it to the anycast routing problem to forward packets toward gateways. For the path back from a gateway to a mesh node, we present a concept based on source routing. Following, we describe a concrete implementation of a protocol based on the presented concepts. 3.1 Concept Conceptually we propose to use a local, proactive anycast routing protocol based on a field, for routing packets toward the gateways. For the way back, we suggest a passive source routing protocol which takes advantage of recorded routs from the forward path. Forward Path In physics, a field is an assignment of a physical quantity to every point in spacetime. Thus, a field is viewed as extending throughout the space so that its influence is all-pervading. The physical quantity of a field is usually represented mathematically by a scalar, vector or tensor value. In networking, we do not have an infinite nor a continuous spacetime. The number of network nodes is finite and a field of nodes has to be described in a discrete room. But we may also assign network quantities to nodes. Since the room of a network is neither spatial nor continuous, it only makes sense to use scalar network quantities. A familiar example of a scalar field in physics is the temperature field. At every particles in a room, the temperature field has a single numerical value. The values of the temperature field are higher near sources of heat, such as heating vents, and lower farther away. The propagation of the heat from particles to particles can be calculated by a discrete solution of the Poisson Equation. A major property of this 4

5 solution is that the intensity of the field decreases away from a source resulting in a gradient. Analogical in networking, we can look at nodes in the network as particles and at a destination of a route as a source of heat. Thus, for routing to different destinations independent fields are required. The advantage of the presented concept appear when we apply it to anycast routing. Anycast is a routing scheme whereas data is routed to exactly one node of a group of nodes. This group represents one destination. Routing packets toward a gateway is such an anycast routing problem where the group of nodes consists of the gateways. Analog to the temperature field we can compile three constraints. Constraint 1: There is a field sourced by the gateways. Constraint 2: A mesh node calculates its scalar value of this field based on the values from its neighbors. Constraint 3: The scalar field value of a mesh node has to be lower than the values of its neighbors which contributed to its value. Beside this constraints we also take advantage of the following observation. Gateways are very unlikely to disappear but links of mesh nodes break more or less frequently. This may be due to mobility, the switching off of a node or even increased interference. Thus, it is more important to route packets over redundant areas with well meshed nodes instead of toward the closest gateway or toward the area with the highest density of gateways. This observation can be integrated in the field calculation process. Backward Path Routing packets back from a gateway to a mesh node is a classical unicast routing problem. The selfevident idea is to use the same concept based on fields or a classical unicast routing protocol. But, this would pose real scalability and performance problems in larger networks, because a route has to be maintained for every single mesh node. An alternative would be to take advantage of information form the forward path. This could be done by marking the path of the packets toward the gateways. An even better alternative is to record the path of a packet and store it at the gateways or in a routing server connected to the gateways. Like this the mesh nodes remain state less and only the gateways or a connected routing server has to maintain actual backward routes. An other advantage of this solution is that it causes no additional routing overhead. This solution poses two minor issues which should be mentioned at this place. First, a backward path is only available after a packet has been sent to a gateway. But this is no limitation, because the vast majority of communication is initiated by a mesh node itself. If a mesh node wants to act as a server, it any how has to register its service periodically in the Internet. This periodic registrations allows for updating the backward path. Second, the backward path only gets updated if a packet is sent to a gateway. As well this is no real limitation. All applications based on TCP and almost all other application generate bidirectional packets. For the inprobale case where a mesh node only receives packets and never sends anything back, it could regularly send a ping to the gateways resulting in an update of the backward path. 3.2 Protocol The protocol can also logically be split into a forward and a backward path. For the forward path the gateways source a field. This field is built up by periodically exchanging the field intensity by hellos between the mesh nodes. The mesh nodes calculate distributedly their intensities based on the intensities of their neighbors. Routing on the forward path is implemented on a hop by hop bases. A packet is forwarded to the neighbor with the highest field intensity, resulting in a steepest gradient routing. All packets sent over the forward path record their route. This route is stored in a route server connected to the gateways. The stored routes are used for source routing packets back to mesh nodes. 5

6 Forward Path The field is represented as a 32Bit unsigned integer value. The gateways source it with a constant value of MAX_UINT (2 32 1) (constraint 1). Every node broadcasts its intensity to its neighbors with a certain interval. If a node receives a hello it updates its neighbor table. If the corresponding field intensity of the neighbor has changed, it recalculates its field intensity using the field calculation function. Also if the hellos of a neighbor timed out more then several hello intervals, the entry of this neighbor in the neighbor table is cleared and the field calculation function is called. The main idea of the field calculation function is to prefer routes with high redundancy over short ones. This is achieved by taking into account the field intensities of several neighbors instead of just one (constraint 2). The field calculation function first sorts ascendingly all neighbors based on their field intensities x (equation 1). Then it iterates over them, accumulating its field intensity until the intensities of the remaining nodes are below the accumulated intensity (equation 3, 4). In every step, it first calculates the difference between the accumulated intensity and the intensity of the neighbor. The a multiplicative of this difference is then accumulated (equation 3). From constraint 3 follows that < a < 1. x i >= x i+1 (1) f() = (2) f(i) = f(i 1) + (x i f(i 1)) a (3) f final = f(i) i = max(j; f(j) < x j (4) As already mentioned, areas with high redundancy are given a higher priority. The strength of this effect can be controlled by the parameter a and gets stronger the smaller the parameter is chosen. A concrete example of the field calculation function with a = 1/8 is given in figure 3. Figure 3: Example of Field Calculation Function: step 1, sort neighbors (nbr) by field intensity (x); step 2-5 iterate down the table until the field intensity of the node gets higher or equal to the next neighbor. Given the field, routing is no more difficult. Since all information is local, routing is implemented on a hop by hop base. When a packet has to be forwarded to a gateway the route selection function is called. This function looks up the neighbor table for the neighbor with the highest field intensity. This neighbor is then chosen as the next hop. This is similar to a steepest gradient routing. Constraint 4: A packet is forwarded to the neighbor with the highest field intensity. 6

7 Improvements The protocol also includes two major improvements which are important for stability and convergence. First, if the field intensity of a node drops this may result in a swing down. This can be eliminated by using s similar technique to poison reverse. To each hello, the identifiers of the neighbors which contributed to the field strength of a node are added. Then, the field calculation function of a node has to ignore all neighbors which were sponsored by itself. This can be looked at as a directed, loop free graph which results in a wave like propagation away from the place where the field intensity dropped. Second, if the field intensity of a node decreases, it checks in his neighbor table if a neighbor is affected by this. If this is the case, then the node broadcasts precociously a hello to inform its neighbors about the change of its field intensity. This assures a fast convergence resulting in better routing performance. For minimizing the additional hellos, they can be delayed for a short period like some broadcast intervals to ensure that precocious hellos triggered by the same event are awaited. Backward Path For routing packets back from the gateways to the nodes, we take advantage of the forward path. Each packet traveling on the forward path records its route in the header. Arrived at a gateway, the recorded rout is extracted an stored on a routing server connected to all gateways. This routing server is consulted by the gateways, when a route back to a node is needed. The stored route is then used for source routing packets back to mesh nodes. 4 Evaluation For evaluating the protocol we first validate it by mathematical profs and simulation. Then we show its performance and scalability based on considerations and simulations. Following we present an application study based on realistic simulations of hybrid WMNs for demonstrating the usability of the proposed concept and protocol. Prior, in the next section, we present our simulation environment and configuration. 4.1 Simulation Environment To evaluate the proposed concept and its protocol implementation, we performed detailed simulations using Glomosim [19] and QualNet [2]. In this section we first specify and motivate the used parameters. Then, we present the used configurations, namely the mobility model, the gateway placement and the traffic model. Parameter Selection: An initial set of experiments were conducted in order to find appropriate values for the protocol timing parameters and the field calculation function. These experiments show that it is appropriate to set the hello interval to 1 second and the time out to 3 hello intervals. Setting the hello interval is a classical trade of between overhead and convergence time. The figures 4 and 5 show, that the convergence time from 2 seconds to 1 second still decreases clearly, while there is no huge advantage by further decreasing it to.5 seconds. On the other side the routing overhead is still quiet low. Further we set the delay for precocious hellos to 2 broadcast intervals (= 2 ms). This reduces the number of sent hellos and optimizes the convergence time, while longer delays already have a negative impact on the convergence time (see figures 6 and 7). Based on our evaluation [21] we set the multiplicative a of the field calculation function to a = 1/8. This reduces the convergence time and the overhead while still ensuring high redundancy. Configurations: The simulation environment uses 82.11b radios with a bandwidth of 11 M bps and a nominal range of 25 meters. All other parameters are left at their default value. Since our study focuses on the wireless network, we assume that the wired links between the gateways and the servers in Internet are not a bandwidth bottleneck. Typical simulation durations were between 1 and 7

8 Convergence Time [seconds] Hello Interval [seconds] Figure 4: Convergence time versus hello interval with 3σ confidence interval..25 Routing Overhead [Channel Utilazation Ratio] Hello Interval [seconds] Figure 5: Per node convergence time versus hello interval with 3σ confidence interval. Convergence Time [seconds] Broadcast Intervals (1 ms) Figure 6: Convergence time versus delay of precocious hellos in broadcast intervals with 3σ confidence interval. Hellos Sent per Second Broadcast Intervals (1 ms) Figure 7: Convergence time versus delay of precocious hellos in broadcast intervals with 3σ confidence interval. 8

9 1 seconds and repeated between 1 and 5 times with different seeds. Mobility Model and Gateway Placement: We consider two mobility models for the wireless nodes: a static model and a realistic city mobility model. For the static model we randomly place nodes over an area of 5x5 meters. The gateways are as well randomly placed all over this area. For generating realistic city mobility models we extracted vectorized street maps including speed limitations of several larger cities of Switzerland from the Swiss Geographic Information System [22] (see figure 8). To these maps, we apply the steady-state random trip mobility model [23]. For these models, the gateways were placed at strategic places all over the cities Figure 8: Vectorized street map of zurich with speed limit information based on the swiss geographic infomation system Traffic Model: Our traffic models are different than what is commonly used. We apply a realistic mix of streaming and web traffic between mesh nodes and servers in the Internet. Web traffic consists of requests form mesh nodes and responses from servers in the Internet. The Inter-request times are distinguished between long and short breaks which are each exponentially distributed [24, 25, 21]. The file size of the response is pareto II distributed. The streaming traffic is constant bit rate traffic between mesh nodes and servers in the Internet. The streaming time and the pause time are exponentially distributed [24, 21]. 4.2 Validation Based on [26] we validate the protocol with respect to the following points. 1. The protocol is loop free. 2. The protocol forwards a packet toward its destination. We will prove these two points only for the forward path. Due to the symmetry of the forward and backward path, the proofs hold for both directions. But before we are ready for proving, we have to state a corollary. Corollary 1: Every node has a neighbor with a higher field intensity then its own, otherwise it is a gateway. From constraint 3 follows that a non gateway node always has a neighbor with a higher field inten- 9

10 sity. And from constraint 1 follows that gateways represent a local maxima and vice versa. Proof 1: Loop freedom of a routing protocol can best be profen by contradiction. Assume there is a routing loop, forwarding packet in a circle: node 1 node 2... node n node 1. From corollary 1 and constraint 4 follows that field_intensity_node i < field_intensity_node i+1 and that field_intensity_node n < field_intensity_node 1. But this is a contradiction because from this follows that field_intensity_node 1 < field_intensity_node 1 and this is impossible. Proof 2: Forwarding a packet toward its destination, means for the forward path toward a gateway: node source node 1 node 2... node n node gateway. From corollary 1 we know that for every node i there is a neighbor node i+1 with a higher field intensity or it is a gateway. From this follows that field_intensity_node source < field_intensity_node 1 < field_intensity_node 2 <... < field_intensity_node n < field_intensity_node gateway. Due to this for every forward from node i to node i+1 follows that the difference of the field intensity _field_intensity_node i = field_intensity_node gateway field_intensity_node i decreases _field_intensity_node i > _field_intensity_node i+1 until it reaches a gateway. This determinant assures that with every hop, a packet gets closer to its destination. 4.3 Performance Performance is a major criteria for most protocols. In hybrid WMNs, the users want to have short set-up times, high stability and throughput. In this section, we mainly address these issues. Additionally, in section 4.5, a complete application scenario with performance measurements is presented. In wireless networks, the route set-up time is very important, because of broken links usually provoke a reset-up of a route. In contrast to reactive schemes, the proposed protocol does not have any set-up time since it uses a proactive scheme. Due to its field characteristics, it immediately knows alternative routes for broken links, if available. For optimal performance, convergence is an important issue. For measuring convergence time, we conducted a set of simulations in a static scenario. In a converged state, 1% of all nodes and gateways are turned off. Remember, the hello time out is set to 3seconds. The results in the figure 9 shows that the protocol convergece very fast, even with a highy node denity. 12 Convergence Time [seconds] #nodes per communication range Figure 9: Performance: Convergence time versus nodes density with 3σ confidence interval. For testing the availability of the backward path, we send a requests to a echo server and investigate how many responses come back successfully. In these simulations, the static and the city mobility models have been compared. The high success rate in figure 1 shows, that the backward paths are recent enough. With out restrictions, the few losses can be ascribed to network partition or collisions in the lower layers. 1

11 1.8 Delivery Ratio Static Scenario City Mobility Figure 1: Performance: Availability of backward path measured with the success ratio of a requestresponse to an echo server. City mobility scenarios were used with different utilization (3σ confidence interval). 4.4 Scaling Scalability of a routing protocol for hybrid WMN is a major key for its success. Scalability is important with respect to the number of nodes and gateways participating in the mesh. There are 3 major criteria for scalability: routing overhead, convergence time and resource requirement per node. The last criteria is already optimal solved by the concept and the design of the protocol. A mesh node just has to store a few things for the field of the forward path, since the backward path is state less. For the field, a node stores its own field intensity as well as a neighbor table. This neighbor table contains for every neighboring node the identifier, the field intensity and a flag indicating if it is a sponsor of field intensity. Thus, the required amount of memory linearly depends on the number of neighbors, which is rather small. The required computing power is also no issue, since it is even below the one of common distance-vector routing protocols and far below common link-state routing protocols. Because it only has to deal with local information of one single destination. Convergence is a critical issue in large scale networks. Due to improvement one, the proposed protocol ensures propagation of changes locally, in a wave like form. This assures fast convergence especially with increasing number of participating nodes. For proving the scalability with respect to convergence time, we have conducted a set of simulations in a static scenario. In a converged state, 1% of all nodes and gateways are turned off. The results are presented in the figures 11 and 12. They show that after awating the time out interval, the network reconverges quickly and also with an increasing density of gateways or increasing number of participating nodes. 8 Convergence Time [seconds] Gateway Dichte [#Gateways/node] Figure 11: Scalability: Convergence time versus increasing number of gateways with 3σ confidence interval. The third scalability issue addresses routing overhead. The proposed protocol uses a proactive strategy for the forward path with only one destination, the Internet. Every node periodically broadcast a small hello message to its neighbors. It is logic, that the number of sent hello messages linearly increases with the number of participating nodes. The number of received hello messages depends on the number 11

12 Convergence Time [seconds] # Nodes in Mesh Figure 12: Scalability: Convergence time versus increasing number of nodes with 3σ confidence interval (node and gateway density remains constant). of neighbors, thus on the node density. So the routing overhead per node is constant and thus not increase neither with the number of nodes nor with the number of gateways (figure 13). This is because in contrast to unicast routing protocols, the proposed anycasting strategy only has to maintain a single destination. For the backward path there is now additional routing overhead since it completely relies on the routing information collected on the forward path. # Hellos Recevied per Interval # Nodes in Mesh Figure 13: Scalability: Number of hellos received per node versus increasing number of nodes with 3σ confidence interval. The node density is constant with an average of 7.85 neighbors per node. 4.5 Application For demonstrating the usability of the proposed concept and protocol, we conduct simulations with the realistic city mobility and traffic models presented in section 4.1. As a representative scenario, following, we will present the results for the city of Zurich (figure 8, area 35km 2, 1 mesh nodes, 5 gateways). Figure 14 shows the delivery ratio with respect to the demanded bandwidth per node. Based on the chosen configuration, in average 2 nodes have to share a single gateway. This results in an immense accumulation of demanded bandwidth at the gateways (e.g. from 2kByte/s per node results 3.2M bit payload at a gateway). A comparison between the average path length measured in the simulation and the theoretical minimal one is shown in figure Discussion and Improvements The evaluation has shown, that the presented concept and implementation meets the requirements. In this section, we will briefly disuse the results and possible improvements. The evaluation has shown that the protocol is valid by design. The performance of the protocol looks promising, especially compared to common MANET routing protocols. For the future we plan to investigate in more detail aspects related to the field and route selection. For the field we plan to use different 12

13 Delivery Ratio Traffic per Node [Bytes/s] Figure 14: Application: Delivery ratio versus network load with 3σ confidence interval. 6 Average Path Length Simulation Theory Figure 15: Application: Average path length in simulation and theory. and multiple routing metrics as for example the available bandwidth. Related to this issue is the investigation of different field calculation functions witch weight the effect of a included routing metric as well as the shape of the field itself. Beside this we plan to use different route selection functions mainly for the purpose of load balancing over different links. The evaluation clearly shows that the major criteria, the scalability, has been met. The realistic hybrid WMN scenarios have demonstrated the applicability of the protocol. As next step we are building a prototype network based on the proposed protocol for conducting real world test. 6 Related Work Multi-hop wireless networks have received significant attention over the last few decades. A major focus of research was set on efficient unicast routing techniques [6, 27, 28, 29]. As discussed in this paper, we believe that anycast is the routing paradigm to be used for routing in hybrid WMN. Anycast was first proposed for IP networks [2, 3]. Anycast routing protocols for mobile ad hoc networks are mostly implemented as modifications of existing routing protocol as for example [3, 31]. Unlike Lenders proposed to use gradient based routing for anycasting for service discovery in mobile ad hoc networks [32] which is somehow related to gateway discovery. The idea of gradient based routing came up in the area of sensor networks [33, 34]. Its purpose was to aggregate data sent to a sink for minimizing the amount of transmissions. Research on interconnecting multi-hop wireless networks with fixed infrastructure networks mainly focused on addressing and gateway discovery. For addressing there are already several promising propositions [7, 8, 9, 1, 11, 12, 13, 14, 15]. Our approach for interconnecting hybrid WMN is based on the idea Interconnecting wireless ad hoc networks with fixed infrastructure The routing issue was mostly solved by using an existing unicast routing protocol and enriching it with gateway discovery capabilities [35, 36, 37, 38, 39, 4]. These discovery capabilities base on proactive announcing of gateways or on reactive request/join - response protocols. There is also some work putting these capabilities into the MAC Layer [41]. Our approach mainly differs from these approaches in the used routing paradigm. We propose to use a new anycast routing protocol which uses some ideas from gradient based routing. 13

14 7 Conclusion In the future, the business models of Internet Service Providers might change dramatically. Ubiquitous and cost efficient Internet access can be realized by hybrid Wireless Mesh Networks only requiring a few gateways. A key point for this vision becoming reality is the availability of a scalable and efficient routing protocol for this specific application. In this paper, we have presented the concept and implementation of an anycast routing protocol meeting these requirements. The protocol bases on the concept of fields for routing packets form the wireless to the wired domain. For routing packets back to the wireless domain, we have suggested to use source routing based on routing information collected on the forward path. The validity of this concept has mathematically been profen. For gaining more inside into the problem and evaluation of our proposals, we build up a realistic simulation environment. This environment bases on real world scenarios extracted from a geographic information system. References [1] I. F. Akyildiz, X. Wang, and W. Wang, Wireless mesh networks: A survey, Computer Networks Journal (Elsevier), 25. [2] C. Partridge, T. Mendez, and W. Milliken, Host Anycasting Service, RFC 1546 (Informational), Nov [Online]. Available: [3] R. Hinden and S. Deering, IP Version 6 Addressing Architecture, RFC 2373 (Proposed Standard), July 1998, obsoleted by RFC [Online]. Available: [4] J. Postel, Internet Protocol, RFC 791 (Standard), Sept. 1981, updated by RFC [Online]. Available: [5] R. Perlman, Interconnections: Bridges and Routers, [6] C. Perkins, Ad-hoc on-demand distance vector routing, [Online]. Available: citeseer.ist. psu.edu/perkins2adhoc.html [7] Y. N. Z. Yunlong, M. Chaoguang, Internet accessing for ipv6 manets, in in Proceeding of the Third International Conference on Information Technology: New Generations (ITNG 6). [8] C. P. A. N. A. T. R. Wakikawa, J.T. Malinen, Global connectivity for ipv6 mobile and ad hoc networks, in Internet Engineering Task Force, Internet Drafr July 22. [9] Y. S. C.E. Perkins, E.M. Belding Royer, Internet connectivity for ad-hoc mobile networks, in International Journal of Wireless Information Networks, April 22. [1] A. T. R. W. J. M. A. Nilson, C.E. Perkins, Aodv and ipv6 internet access for ad hoc networks. [11] T. L. P. J. G. M. J. U. Jonsson, F. Alriksson, Mipmanet - mobile ip for mobile ad hoc networks, in in MOBIHOC, ppaugust 2., pp [12] K. A. M. Benzaid, P. Minet, A framework for integrating mobile-ip and olsr, in Networking for Future Wireless Mobile Systems. [13] G. Andrealis, Providing internet access to mobile ad hoc networks, in London Communications Symposium, Sep 22. [14] A. Z. C. Ahlund, Integration of ad hoc network and ip network capabilities for mobile hosts, in in Proceedings of the 1th International Conference on Telecommunications (ICT), Feb

15 [15] R. Baumann, Vanet: Vehicular ad hoc networks, Master s thesis, ETH Zurich, 24. [16] C. Perkins, IP Mobility Support, RFC 22 (Proposed Standard), Oct. 1996, obsoleted by RFC 322, updated by RFC 229. [Online]. Available: [17] J. Solomon and S. Glass, Mobile-IPv4 Configuration Option for PPP IPCP, RFC 229 (Proposed Standard), Feb. 1998, updated by RFC [Online]. Available: http: // [18] Rainer Baumann, Olga Bondareva, Bernhard Plattner, Survey on Addressing for Interconnecting Wireless Access Networks. TIK Report 25, ETH Zurich, Tech. Rep., July 26. [19] X. Zeng, R. Bagrodia, and M. Gerla, Glomosim: A library for parallel simulation of large-scale wireless networks, in Workshop on Parallel and Distributed Simulation, 1998, pp [Online]. Available: citeseer.ist.psu.edu/zeng98glomosim.html [2] I. Scalable Network Technologies, QualNet Simulator, Scalable Network Technologies, Inc., [21] Rainer Baumann, Martin May, Bernhard Plattner, Field Based Interconnection of Hybrid Wireless Mesh Networks. TIK Report 249, ETH Zurich, Tech. Rep., Mai 26. [22] F. O. of Topography, Swiss geographic information system. [Online]. Available: ch [23] J.-Y. L. Boudec and M. Vojnovic, Perfect Simulation and Stationarity of a Class of Mobility Models, in IEEE Infocom, 25. [24] U. Fiedler, P. Huang, and B.Plattner, Towards Provisioning Diffserv Intra-Nets, in Proceedings of IWQoS 1. Karlsruhe, Germany: Springer, June 21, pp [25] A. Feldmann, A. C. Gilbert, P. Huang, and W. Willinger, Dynamics of IP traffic: A study of the role of variability and the impact of control, in SIGCOMM, 1999, pp [Online]. Available: citeseer.ist.psu.edu/feldmann99dynamics.html [26] S. Corson and J. Macker, Mobile Ad hoc Networking (MANET): Routing Protocol Performance Issues and Evaluation Considerations, RFC 251 (Informational), Jan [Online]. Available: [27] D. B. Johnson and D. A. Maltz, Dynamic source routing in ad hoc wireless networks, in Mobile Computing, Imielinski and Korth, Eds. Kluwer Academic Publishers, 1996, vol [Online]. Available: citeseer.ist.psu.edu/johnson96dynamic.html [28] C. Perkins and P. Bhagwat, Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers, in ACM SIGCOMM 94 Conference on Communications Architectures, Protocols and Applications, 1994, pp [Online]. Available: citeseer.ist. psu.edu/perkins94highly.html [29] Z. J. Haas and M. R. Pearlman, The performance of query control schemes for the zone routing protocol, in SIGCOMM, 1998, pp [Online]. Available: citeseer.ist.psu.edu/article/ haas98performance.html [3] V. Park and J. Macker, Anycast Routing for Mobile Services, in Conference on Information Sciences and Systems (CISS), Baltimore, MD, USA, March

16 [31] J. Wang, Y. Zheng, and W. Jia, An AODV-based Anycast Protocol in Mobile Ad Hoc Network, in Proc. of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communication, Beijing, China, September 23. [32] V. Lenders, M. May, and B. Plattner, Service Discovery in Mobile Ad Hoc Networks: A Field Theoretic Approach, in Proceedings of the IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Taormina, Italy, June 25. [33] C. Intanagonwiwat, R. Govindan, and D. Estrin, Directed diffusion: a scalable and robust communication paradigm for sensor networks, in Mobile Computing and Networking, 2, pp [Online]. Available: citeseer.ist.psu.edu/intanagonwiwatdirected.html [34] C. Shurgers and M. Srivastava, Energy efficient routing in wireless sensor networks, in Proc. IEEE Military Communication Conf. (MILCOM), Oct. 21. [35] S.-H. C. J.-C. Chen, S. Li and J.-Y. He, WIANI: Wireless Infrastructure and Ad-Hoc Network Integration, in in Proceedings of IEEE International Conference on Communications (ICC), 25. [36] C.-Y. L. Ren-Hung Hwang, Chiung-Ying Wang and Y.-S. Chen, Mobile ipv6-based ad hoc networks: Its development and application, IEEE Journal on Selected Areas in Communications, vol. 23, no. 11, pp , Nov. [37] A. Z. C. Ahlund, Extending global ip connectivity for ad hoc networks, Kluwer. Telecommunication Systems, Modeling, Analysis, Design and Management, vol. 24, no [38] P. Ratanchandani and R. Kravets, A hybrid approach to internet connectivity for mobile ad hoc networks, in Proceedings of IEEE WCNC, 23. [Online]. Available: citeseer.ist.psu.edu/ ratanchandani3hybrid.html [39] Y. Sun, E. Belding-Royer, and C. Perkins, Internet connectivity for ad hoc mobile networks, 22. [Online]. Available: citeseer.ist.psu.edu/sun2internet.html [4] S. Lee, S. Banerjee, and B. Bhattacharjee, The case for a multi-hop wireless local area network, 274. [Online]. Available: citeseer.ist.psu.edu/lee4case.html [41] B. Awerbuch, D. Holmer, and H. Rubens, The pulse protocol: Energy efficient infrastructure access, 24. [Online]. Available: citeseer.ist.psu.edu/awerbuch4pulse.html [42] Simon Heimlicher, Rainer Baumann, Martin May, Bernhard Plattner, A reliable transport protocol for unreliable networks. tik report 239, ETH Zurich, Tech. Rep., Mai..1 Tools For making this work possible we developed various tools. 1. GIS extractor; a tool allowing to extract vector information about streets from the Swiss Geographic Information System (GIS). 2. City mobility generator; a tool which can generate mobility traces of nodes based on vector data of streets using a random way point model/ 3. Request Reply Server/Client; a UDP based server/client pair which sends web traffic based on statistical experience. 4. Traffic generator; a tool which generates traffic files for Constant Bit Rate (CBR) client/server and Request Reply (RR) client/server. 16

17 5. Addressing 6. NS2 to Glomosim converter; a tool converting mobility and traffic files from an NS2 compatible format to a Glomosim compatible format. 7. NS2 to NAM converter; a tool which directly coverts NS2 movement traces to a Network Animator (NAM) playable format. We also found and fixed a major bug in the actual Glomosim version 2.3. Due to this bug it was not possible to run large, mobility trace based simulations..2 Available Simulation Set-ups For the simulations of this paper we integrated and developed several trace based mobility and traffic models. Mobility Models 1. Static 2. Random Waypoint 3. City Map Mobility Traffic Pattern 1. Web traffic, request response server for UDP based on statistics 2. CBR, unidirectional based on UDP 3. Note: we do not use TCP, since it is not suitable for WMN, we would require a protocol like SAFT [42] 17