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Coverage is an important issue in wireless sensor networks. The most commonly used coverage model in the literature defines a point to be covered if its Euclidian distance to at least one sensor is less than a fixed threshold. This is a conservative definition of coverage which implicitly assumes that each sensor makes a decision independent of other sensors in the field. Sensors can cooperate to make an accurate estimation, even if any single sensor is unable to do so. We have previously proposed a new notion of information coverage and investigated its properties. In this paper, we study sensor density requirements for complete information coverage of a field with random sensor deployment. We provide an upper bound on the probability that an arbitrary point in a randomly deployed sensor field is not information covered and find the relationship between the sensor density and the average field vacancy. Simulation results validate our theoretical analysis and show that significant savings in terms of sensor density for complete coverage can be achieved with information coverage.
Date of Publication: August 2007