Filter indexing: a scalable solution to large subscription based systems

Authors:
Wanxia Xie;Shamkant B. Navathe;Sushil K. Prasad
Affiliations:
College of Computing, Georgia Institute of Technology, Atlanta, GA;College of Computing, Georgia Institute of Technology, Atlanta, GA;Dept. of Computer Science, Georgia State University, Atlanta, GA
Venue:
DASFAA'05 Proceedings of the 10th international conference on Database Systems for Advanced Applications
Year:
2005

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Abstract

Filtering is a popular approach to reduce information traffic in subscription-based systems, especially if most subscribers are located on mobile devices. The filters are placed between the subscribers and the subscription server. With increasing number of filters from subscribers, filtering may become a bottleneck and challenge the scalability of such systems. In this paper, we propose to use filter indexing to solve this problem. We propose and study four filter-indexing schemes: Ad-Hoc Indexing Scheme (AIS), Group Indexing Scheme (GIS), Group-Sort Indexing Scheme (GSIS) and B' Tree Indexing Scheme (BTIS). We evaluate the performance of these four indexing schemes with respect to scalability and other factors. Among the proposed schemes, we find that GSIS is the most efficient indexing scheme for searching and BTIS has the best performance for updating and inserting filters.