POSTER TEMPLATE BY: Efficient Counter-Based Flooding for Mobile Ad Hoc Networks S. Al-Humoud, M. Ould Khaoua and L. M. Mackenzie University of Glasgow, Glasgow, G12 8RZ, U.K. {sara, mohamed, MANET Acknowledgement Flooding We can look at the problem as a pyramid, where the base is the general field of MANET research. Above this is routing, one of the main research areas within MANETS. Broadcasting is a backbone operation in MANETS generally and in Routing specifically. Flooding is one of the most common mechanisms for broadcasting. Finally the pyramid top which is the proposed solutions to the basic flooding problem. This solution is divided into several schemes that are shown in the radial diagram The broadcast storm problem related to basic flooding is shown below Broadcasting is a common operation in Mobile Ad hoc Networks. It is used in host paging and sending alarm signals as well as in routing protocols like DSR, AODV and ODMRP to disseminate control messages. The most common mechanism for broadcast is through flooding. However, Flooding may lead to much redundancy, contention, and collision, and it leads to what is called the broadcast storm problem. Assuming that the area covered by a node’s transmission can be formed by a circle, figure 1 shows the signal overlapping caused by flooding, where area 7 is the most congested area. Figure 2 shows optimal broadcasting, where the red node is the source host, and yellow node is a relay host. Flooding simply means that each node receives a broadcast message it rebroadcasts it again. Although flooding has a high delivery ratio, it leads to many problems. In order to reduce the overhead incurred by flooding, several techniques have been proposed including probabilistic, counter- based, distance-based, location-based, and cluster-based schemes. Flooding Broadcasting Routing MANET Broadcasting A MANET (Mobile Ad Hoc Network) consists of a set of mobile nodes communicating in a multi-hop way without any fixed infrastructure such as access points or base stations. Characteristics of MANET  No centralized control & administration  Self-organizing and self-restoring  Transmission through multiple hops  Frequent link breakage and change of network topology Applications of MANET  Battlefield communication  Sensor networks  Personal area networking using PDAs, laptops and handphones, etc  Cellular network and wireless Hot Spot extension Proposed solutions to plain Flooding Distance- Based schemes Probabilistic schemes Counter- Based schemes Location- Based schemes Cluster- Based schemes Proposed Schemes probabilistic Scheme Counter-Based Scheme Location-Based Scheme On receiving a broadcast message for the first time, a host will rebroadcast it with probability P. Clearly, when P = 1, this scheme is equivalent to flooding. Distance-Based Scheme Cluster-Based Scheme Contribution In counter-based scheme a counter c is used to keep track of the number of times the broadcast message is received. A counter threshold C is chosen. Whenever c  C, the rebroadcast is inhibited. In distance-based broadcast the decision to rebroadcast is done based on relative distance between hosts. The rebroadcast decision is done using the locations of broadcasting hosts. Such an approach may be supported by positioning devices such as GPS receivers This scheme is based on graph modeling. Using the cluster formation algorithm a cluster is formed and within this cluster, a nominated head can rebroadcast to cover all other hosts in that cluster if its transmission experiences no collision. To propagate the broadcast message to hosts in other clusters, gateway hosts take responsibility. There is no need for a non-gateway member to rebroadcast the message. Our contribution is to determine the best counter threshold using neighbouring information. In general, a sparse network has a different threshold than a dense network. We are studying the effect of varying the counter threshold value according to neighbourhood information on the overall overhead, reliability and reachability. The larger the threshold value, the less the rebroadcast savings, and the more redundant rebroadcasts. Our goal is to find a way of adapting the threshold according to the number of adjacent neighbours. For example referring to the figures below, it would seem reasonable that c1 should be larger than c2. DCS 50th Anniversary Poster Competition June 2007 Figure 1: Signal overlapping Figure 3: Research focus Figure 4: Dense Network, Threshold = c1 Figure 5: Sparse Network, Threshold = c2 Figure 2: Optimal broadcasting I would like to thank: M. Bani Yassein, and R. Al-Qassas for their help and useful comments