Reducing Routing Overhead using Off-Network Route Computation in Sensor Networks

Abstract

This paper presents an architectural solution to address the problem of scalable routing in very large sensor networks. The control complexities of the existing sensor routing protocols, both node-centric and data-centric, do not scale very well for large networks with potentially hundreds of thousands of embedded sensor devices. This paper develops a routing solution Off-Network Control Processing (ONCP) that achieves control scalability in large sensor networks by shifting certain amount of routing functions to an off-network server. A tiered and hybrid routing approach, consisting of coarse grain server based global routing, and distributed fine grain local routing is proposed for achieving scalability by avoiding network wide control message dissemination. We present the ONCP architectural concepts and analytically characterize its performance in relations to both flat and hierarchical routing architectures. Finally, using an ns2 based simulation model we show experimental results indicating that for large sensor networks with realistic data models, the packet drop, latency and energy performance of ONCP can be significantly better than those for a well known flat sensor routing protocol Directed Diffusion.