This work

focuses on unstructured random data storage and query. Since the energy is one of the most pre- cious resources

an MESQ optimization problem is formed whose aim is to select the optimum number of replicas and queries that minimize the total energy cost

subject to unrestrained or restrained storage. In order to make more practical

a localized data dissemination algorithm

called BubbleGeocast

is designed. It is made up of two components: adaptive accurate data diffusion in real-time and rejection-based uniform data diffusion. The first one can control the total number of replicas and branch adaptively to diffuse data as soon as possible. The second one can guarantee each node accepts a packet in the same probability according to the area of its own Voronoi cell. These two can diffuse replicas and queries accurately

fast

uniformly

and robust. Simulations show that BubbleGeocast provide reduced 30% communication costs

30% delay on replicas diffusion

and 50% delay on query on average

within the bound of successful query.