On incremental processing of continual range queries for location-aware services and applications

A set of continual range queries, each defining the geographical region of interest, can be periodically re-evaluated to locate moving objects. Processing these continual queries efficiently and incrementally hence becomes important for location-aware services and applications. In this paper, we study a new query indexing method, called CES-based indexing, for incremental processing of continual range queries over moving objects. A set of containment-encoded squares (CES) are predefined, each with a unique ID. CES´s are virtual constructs (VC) used to decompose query regions and to store indirectly pre-computed search results. Compared with a prior VC-based approach, the number of VC´s visited in an index search in CES-based indexing is reduced from (4L²-1)/3 to log(L)+1, where L is the maximal side length of a VC. Search time is hence significantly lowered. Moreover, containment encoding among the CES´s makes it easy to identify all those VC´s that need not be visited during an incremental query reevaluation. We study the performance of CES-based indexing and compare it with a prior VC-based approach.