An Improved Method for creating Shared Belief in Communication Constrained Sensor Networks

Networked systems that gather sensor data in order to react to phenomena in their surroundings are faced with a growing need for adaptive behavior to operate in dynamically changing environments. In designing a networked system the data processing chain can be decomposed into functional components. These functional components interact by requesting information they need and fulfilling requests received from other components. Local evaluation of the available data with respect to the different requests and available resources is a key process in each component. An improved evaluation method is presented which is capable of locally balancing the information value against the resource costs of data. The experiments show that the evaluation method with the same amount of communication costs, results in a higher common picture quality with multiple objects and overlapping detection ranges.