Energy efficient indexing on air
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Balancing push and pull for data broadcast
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Data on Air: Organization and Access
IEEE Transactions on Knowledge and Data Engineering
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Spatial queries in wireless broadcast systems
Wireless Networks - Special issue: Pervasive computing and communications
DSI: A Fully Distributed Spatial Index for Location-Based Wireless Broadcast Services
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Air-Indexing on error prone communication channels
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
Computers & Mathematics with Applications
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Air indexing techniques have been developed for energy efficient query processing of mobile clients(MCs) in the wireless data broadcast. In the air indexing for spatial data, previous studies have involved various problems, long broadcast cycle by large index size and unnecessary data listening by the query processing based on coordinates, which are mapped on space-filling curves from the real coordinates of data instances. In this paper, Cell-based Distributed Spatial Index(called CEDI) is proposed for wireless broadcast services. CEDI is very compact in size by keeping pointers of the groups of data instances instead of the pointer of each data instance. CEDI has distributed structure and supports multiple search paths by the replication of the pointers of data groups. CEDI does not have unnecessary data instances in the result due to processing queries based on the real coordinates of data instances. Therefore CEDI is very efficient for energy and has reduced access time to desired data. Moveover, CEDI has the robustness for link-error in error-prone wireless transmission environments. For the performance evaluation, simulation experiments using a real dataset and a uniform distribution dataset under various link-error probabilities are conducted. Experimental results show that CEDI outperforms the existing scheme in the energy efficiency and data access time. In particular, CEDI is much more resilient to link-errors.