Geographical data collection in sensor networks with self-organizing transaction cluster-heads
Proceedings of the 2009 ACM symposium on Applied Computing
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As wireless sensor networks continue to grow in size, we are faced with the prospect of emerging wireless networks with hundreds or thousands of nodes. Geographic routing algorithms are a promising alternative to tradition ad hoc routing algorithms in this new domain for point-to-point routing, but deployments of such algorithms are currently uncommon because of some practical difficulties. This dissertation explores techniques that address two major issues in the deployment of geographic routing algorithms: (i) the costs associated with distributed planarization and (ii) the unavailability of location information. We present and evaluate two new algorithms for geographic routing: Greedy Distributed Spanning Tree Routing (GDSTR) and Greedy Embedding Spring Coordinates (GSpring). Unlike previous geographic routing algorithms which require the planarization of the network connectivity graph, GDSTR switches to routing on a spanning tree instead of a planar graph when packets end up at dead ends during greedy forwarding. To choose a direction on the tree that is most likely to make progress towards the destination, each GDSTR node maintains a summary of the area covered by the subtree below each of its tree neighbors using convex hulls. This distributed data structure is called a hull tree. GDSTR not only requires an order of magnitude less bandwidth to maintain these hull trees than CLDP, the only distributed planarization algorithm that is known to work with practical radio networks, it often achieves better routing performance than previous planarization-based geographic routing algorithms. GSpring is a new virtual coordinate assignment algorithm that derives good coordinates for geographic routing when location information is not available. Starting from a set of initial coordinates for a set of elected perimeter nodes, GSpring uses a modified spring relaxation algorithm to incrementally adjust virtual coordinates to increase the convexity of voids in the virtual routing topology. This reduces the probability that packets will end up in dead ends during greedy forwarding, and improves the routing performance of existing geographic routing algorithms. The coordinates derived by GSpring yield comparable routing performance to that for actual physical coordinates and significantly better performance than that for NoGeo, the best existing algorithm for deriving virtual coordinates for geographic routing. Furthermore, GSpring is the first known algorithm that is able to derive coordinates that achieve better geographic routing performance than actual physical coordinates for networks with obstacles. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)