A TAXONOMY OF ROUTING PROTOCOLS FOR MOBILE AD HOC NETWORKS in VS .NET

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A TAXONOMY OF ROUTING PROTOCOLS FOR MOBILE AD HOC NETWORKS
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reaches a speci ed threshold value, it means that the route is stable. If the neighbor goes out of the range, then the tick value is reset to zero. Hence a tick level above the threshold value is an indicator of a rather stable association between these two nodes. Once a destination has received the broadcast query packets, it has to decide which path to select by checking the tick-associativity of the nodes. The route with the highest degree of associativity is selected since it is considered the most stable of the available routes. ABR is quite an effective algorithm in selecting routes because it focuses on the route stability to a great extent. However, some inherent drawbacks include memory requirements for the routing tables, excessive storage needs for storing the ticks, and additional computation to maintain the tick count along with greater power requirements.
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Signal Stability-Based Adaptive Routing (SSBR) [11]. The SSBR differs when compared with the conventional routing algorithms. The main routing criteria is the signal and location stability. The basic routing framework is similar to any other standard on-demand routing protocol: The route request is broadcast throughout the network, the destination replies back with the route reply message, and then the sender sends data through the selected route. However, the signal strength (link quality) between neighboring nodes plays a major role in the route selection process in this protocol. SSBR is comprised of two subprotocols: Dynamic Routing Protocol (DRP) and Static Routing Protocol (SRP). The DRP interacts with the network interface device driver dealing with signal strengths through an API to determine the actual strength of a received signal. Using this signal information, the DRP maintains a signal stability table that categorizes each link with the neighboring nodes as strong or weak. This table is updated with every new packet received. For instance, if a HELLO packet is received, the signal strength is monitored and the signal stability table is upgraded, whereas for other packets such as route update packets, data packets, and so on, the packet is sent to the SRP for further processing. The SRP performs the routine tasks such as forwarding packets according to the existing routing table, replying to route requests, and so on. The route request is given an option on the type of link it requests that is, strong, weak or a combination of both. If the route request speci es only strong links, all the route request packets coming from a perceived weaker link are dropped. Thus, the nal discovered path consists of only strong links. If there are multiple paths from source to destination using strong links, the destination can choose among them. The destination can simply choose the rst route request it receives. If, however, no strong links are found, the protocol could fall back on other available weaker links. Two enhancements to the selection process are proposed. In the rst case, the link strength (strong or link) is added for each hop into the route request packet and then forwarded toward the destination. In this case, the destination does not select the rst route request packet received, but waits for a period of time to choose the best route among all the route requests within a set time interval. The second improvement
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AD HOC NETWORKS ROUTING PROTOCOLS
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suggests that any intermediate node can make an unnecessary route reply for a route it already has a prior information about. The SSBR algorithm uses a similar scheme as the ABR algorithm to determine the reliability of links before selecting a particular route. While the former uses signal strength, the latter uses ticks; however, the goal of selecting a route with greatest reliability remains the same. The Ant-Colony-Based Routing Algorithm (ARA) [12]. This work presents a novel technique for ad hoc routing by using the concepts of swarm intelligence and the ant colony based meta heuristic. These ant colony algorithms focus on solving the complex problems by cooperation and without any direct communication. Ants communicate with each other using stigmergy, a means of indirect communication between individuals by modifying their operational environment. Ants nd the shortest path to a destination by making the use of pheromones (Figure 5.4). Initially, the ants randomly choose the path. On the way, they drop off pheromones. The ants chosen the shortest path reach the destination earlier than the others and travel back along the same path. They keep releasing additional pheromones on this path gradually increasing the pheromone concentration. The successive groups of ants coming from the source recognize the path with greater pheromone levels due to the higher concentration and hence start taking this route which ends up as the best route. This method of selecting the shortest path is used to determine the optimal route for ad hoc networks. This technique performs well with the dynamic link changes due to node mobility along with scalability issues. Using the ant colony meta heuristic, the pheromone change of an edge e(vi , vj ) when moving from node vi to vj can be derived as follows: i,j := i,j + . The
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