Reconfiguration in sensor networks

Unrestricted To be practical, sensor networks need to adapt to changes in their environment. This thesis explores reconfiguration in sensor networks to endow them with greater adaptability. We study functional reconfiguration in static networks, and spatial reconfiguration in networks with limitedmobility and networks whose constituent nodes are highly mobile.; In static sensor networks, reconfiguration can be thought of as the ability to dynamically reconfigure nodes in the network to perform different functions over time. We study a tiered sensor network where the roles of microserver and sensor are dynamically assigned. We propose a framework for redesigning services by partitioning the workload in a distributed fashion among the microservers. We apply this distribution formulation to connectivity-based localization and show that it converges to within 10% of the centralized solution in ten iterations. We also show a similar formulation for flow-based routing.; In mobile sensor networks, one potential means of reconfiguration is the ability of the network to reposition its nodes using controlled mobility in service of a particular objective. We address the problem of improving connectivity in a robot network by proposing an algorithm for autonomous reconfiguration that causes an initially connected network to be transformed into a biconnected network. First, we show that the robot network biconnectivity problem is NP-hard. We propose a heuristic that uses bearing-only measurements of node neighbors to achieve biconnectivity. Simulations and experiments suggest that this algorithm performs well even when the bearing measurements are coarse (errors up to 30 degrees have little impact on the outcome). As a practical matter, we describe a novel technique to obtain such bearing measurements from commodity radios on simple robots. The biconnectivity algorithm requires a stable connected network. However, experiments reveal that the routing protocol (in our case OLSR) does not necessarily produce routes that are persistent in time. We conjecture that providing location and direction cues improves route stability in robot networks. Test results bear this out - route switches decrease by up to 20% when the routing protocol is given position and directional cues.