PDL Abstract

GEM: Graph EMbedding for Routing and Data-Centric Storage in Sensor Networks Without Geographic Information

Proceedings of the First ACM Conference on Embedded Networked Sensor Systems (SenSys 2003). November 5-7, 2003, Redwood, CA.

James Newsome, Dawn Song

Electrical and Computer Engineering
Carnegie Mellon University
Pittsburgh, PA 15213


The widespread deployment of sensor networks is on the horizon. One of the main challenges in sensor networks is to process and aggregate data in the network rather than wasting energy by sending large amounts of raw data to reply to a query. Some efficient data dissemination methods, particularly data-centric storage and information aggregation, rely on efficient routing from one node to another. In this paper we introduce GEM (Graph EMbedding for sensor networks), an infrastructure for node-to-node routing and data-centric storage and information processing in sensor networks. Unlike previous approaches, it does not depend on geographic information, and it works well even in the face of physical obstacles. In GEM, we construct a labeled graph that can be embedded in the original network topology in an efficient and distributed fashion. In that graph, each node is given a label that encodes its position in the original network topology. This allows messages to be efficiently routed through the network, while each node only needs to know the labels of its neighbors. To demonstrate how GEM can be applied, we have developed a concrete graph embedding method, VPCS (Virtual Polar Coordinate Space). In VPCS, we embed a ringed tree into the network topology, and label the nodes in such a manner as to create a virtual polar coordinate space. We have also developed VPCR, an efficient routing algorithm that uses VPCS. VPCR is the first algorithm for node-to-node routing that guarantees reachability, requires each node to keep state only about its immediate neighbors, and requires no geographic information. Our simulation results show that VPCR is robust on dynamic networks, works well in the face of voids and obstacles, and scales well with network size and density.

KEYWORDS: semantic, context, file system, search, attribute-based naming

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