Mobile Ad-hoc Network Simulator: mobile AntNet R. Hekmat * (CACTUS TermiNet - TU Delft/EWI/NAS) and Radovan Milosevic (MSc student) Mobile Ad-hoc networks Mobile ad-hoc networks are self-organized networks. Communication in ad-hoc network does not require existence of a central base station or a fixed network infrastructure. Each node of an ad-hoc network is the destination of some information packets while at the same time it can function as relay station for other packets to their final destination. This multi-hop support in ad-hoc networks, which makes communication between nodes outside direct radio range of each other possible, is probably the most distinct difference between mobile ad-hoc networks and wireless LANs. A mobile ad-hoc network may be connected at the edges to the fixed, wired Internet. In this case, mobile ad-hoc networks expand the present Internet and wireless access to the Internet. Mobile ad-hoc networks have certain advantages above traditional communication networks. For example, ad-hoc networks could increase mobility and flexibility, as ad-hoc networks can be brought up and torn down in very short time. Additionally, ad-hoc networks could be more economical in some cases because they eliminate fixed infrastructure costs and could reduce power consumption at mobile nodes. Ad-hoc network simulator To study network performance metrics like throughput, delay and routing protocol overhead in wireless ad-hoc networks we have developed a software simulation tool. This tool has a graphical user interface that allows us to monitor changes in the nodes routing table and data output variations when the network topology and the input traffic rates change. The input parameters for the simulator include: number of nodes in the network, size of the service area, speed of the nodes, capacity and transmission delay of radio link between nodes, input traffic statistics per node, and buffer capacity per node. Routing principles The routing protocol used in our simulator is a modified version of AntNet 1. AntNet is an adaptive approach to routing in packet-switched communication networks that is inspired by the stigmergy model of communication observed in ant colonies. In ant colonies, indirect communication takes place among individuals through modifications induced in their environment. Ants lay a trail of pheromones on their way between a source (nest) and destination (food). Each ant choosing a branch increases the amount of pheromones on that branch and in this way it increases the probability of choosing the same branch for following ants. Small but systematic differences are amplified to reach overall shortest path selection. * 1 G. Di Caro and M. Dorigo, AntNet: Distributed Stigmergetic Control for Communications Networks. Tech.Rep. IRIDIA/98-01, 1998, Université Libre de Bruxelles, Belgium. In our simulator program each node produces on regular intervals artificial ants that are sent to randomly chosen destinations. When a destination is reached, the ant travels back to the source node following the same route in opposite direction. Ants are handled with high priority at nodes and do not experience the same delay as data packets. However, based on the queue size at each node, ants collect information about the delay that a data packet would experience using the same path. This information is used to update two data structures in each node: the routing table and the local traffic statistics. In a network of N nodes, the routing table at each node contains the probabilities to reach any of the possible N-1 destination through each of the k neighbours of that node. Local traffic statistics at each node are the sample mean and the variance of the trip time to all other destinations in the network; plus the best trip time to each destination. This information, which is collected and updated by ants, is used to refresh routing tables continuously. Program output On the graphical user interface of the simulator one can follow changes in the network topology and its direct effects on the throughput, delay and capacity usage in the entire network. Therefore, this simulator helps to get a realistic feeling about the behavior of ad-hoc networks under varying circumstances. The following figure depicts some simulation results that show changes in the throughput and the packet delay as a function of the speed of the network nodes. These results are found for a Poisson traffic arrival rate with an average of 40 kbit/s data input per node. Acknowledgement We express our gratitude towards dr. drs. L.J.M. Rothkrantz at TU Delft/EWI. Our ad-hoc network simulator is built upon an AntNet software implementation by his team for dynamic vehicle routing in fixed networks. September 2003