Randomized routing algorithms in mobile ad hoc networks

We consider the problem of finding a path from a source to a destination node in a set of mobile wireless nodes. Many solutions to this problem proposed in the literature fall into the position-based routing paradigm, where in each step, the decision of which node to go to next is based only on the position or geographic coordinates of the current node c , its neighboring nodes N ( c ), and the destination node d . We propose several new randomized position-based algorithms for routing in mobile ad hoc networks. Our algorithms combine the greedy heuristic of minimizing the distance remaining to the destination and the directional heuristic of staying close to the direction of the destination with the use of randomization to retain some flexibility in the chosen routes. We classify our randomized algorithms based on the strategy they use to define a subset of neighboring nodes as the candidate nodes. The sector-based algorithms select the candidate nodes from a specified sector, whereas the AB ( above-below ) algorithms choose two candidate nodes, one from above and the other from below the line between the current node and the destination. On convex subdivisions, a sub-class of AB algorithms can be shown to deliver packets to their destinations with probability 1. Our experiments on unit disk graphs, and their associated Yao graphs, Gabriel graphs, and Planarized Local Delaunay Triangulations, show that the delivery rates of all the randomized algorithms we study are significantly better than the deterministic greedy and directional routing algorithms. For some of the algorithms we propose, this improvement comes at the price of only a small deterioration in the stretch factor of the route. Thus, some of our algorithms obtain a good balance between the delivery rate and the stretch factor

Load balancing in multi-hop wireless ad hoc networks

In this thesis we study the load distribution and load balancing problem in wireless ad hoc networks. Using a discrete unit disk graph model of the network, we analyze the distribution of load induced by greedy routing in the network with an all-to-all communication pattern between the nodes. We derive an estimate for average load of the nodes in the network. We also calculate the expected load of a node as a function of its geometric coordinates in the network. We express the actual load of a node in the network as a random variable and obtain the parameters of this random variable. Using this random variable we derive an estimate for the maximum load of the nodes in the network. Our result is more accurate than previous studies which were based on a continuous model of the network. We analyze how different parameters of the network, i.e., number of nodes, transmission range, and different routing algorithms can affect the parameters of the load distribution. We give a technique to reduce the variance of the load distribution, and hence decrease the maximum load of the nodes in the network. Our technique can be combined with any location-based routing algorithm. We also introduce a class of algorithms that improve the maximum expected load of nodes in the network. Experimental results show that our algorithms outperform other existing algorithms in reducing the maximum load of the networ