|   | CMU-CS-03-112 Computer Science Department
 School of Computer Science, Carnegie Mellon University
 
    
     
 CMU-CS-03-112
 
GEM: Graph EMbedding for Routing and Data-Centric Storagein Sensor networks without Geographic Information
 
James Newsome*, Dawn Song*March 2003
 (Release: February 2003)
  
CMU-CS-03-112.psCMU-CS-03-112.pdf
 Keywords: Sensor networks, routing, data-centric storage
 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.
 
27 pages 
*Department of Electrical and Computer Engineering, Carnegie Mellon University.
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