Energy-Efficient Data Dissemination Schemes for Nearest Neighbor Query Processing

Indexing provides for selective tuning but suffers from the drawback that, in order to conserve battery power, the client has to wait for and tune to the index segment. In location-aware mobile services (LAMSs), it is important to reduce the query response time since a late query response may contain out-of-date information. In this paper, we present a broadcast-based spatial query processing scheme designed to support nearest neighbor (NN) query processing. With the proposed schemes, broadcast data items are sorted sequentially based on their locations and the clients can selectively tune to the desired data item without the need for an index segment. For the purpose of selective tuning, we present the exponential sequence scheme (ESS) and cluster-based Fibonacci sequence scheme (CFS) schemes. The ESS and CFS schemes attempt to conserve battery power. The performance of our schemes is investigated in relation to various environmental variables such as the distributions of data objects, the average speed of the clients, and the size of the service area. The resulting latency and tuning time are close to the optimum values, as our analysis and simulation results indicate