Evaluation of a Tracking Architecture in Wireless Sensor Networks

摘要

A wireless sensor network is a collection of tiny and cheap devices deployed over a physical surface and able to gather and process in a collaborative way some information about a specified phenomenon occuring in their surroundings. Particularly, in tracking applications, the end-user is interested in the statistics of mobile targets crossing the region monitored by the network (i.e. trajectory forecast, speed, etc.). Those statistics share the common need for causally and temporally correlated data. In this paper, we evaluate the energetics cost of TRAC, a high level tracking architecture designed to respond to the requirements of tracking applications. We compare TRAC to a basic flooding-based mechanism, which does not offer any guarantee on the correlation of the disseminated data. Via theoritical analysis and simulations we show that the complexity of TRAC is O(2~x) while the complexity of the flooding-based solution is O(x~3) (where x~2 is the number of nodes in the network). These results emphasize the extra cost of high level properties. We conjecture that a careful aggregation of the data managed by TRAC drops its complexity to O(x~2) and we provide some hints to implement these optimizations.