FlexInd: A Flexible and Parameterizable Air-Indexing Scheme for Data Broadcast Systems

  • André Seifert
  • Jen-Jou Hung
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3896)


In wireless data broadcast systems, popular information is repetitively disseminated through possibly multiple communication channels to mobile clients using various types of battery-operated devices. Access latency and tuning time are two conflicting performance metrics used in such systems to measure their efficiency. In practice, different application and usage scenarios may require different performance trade-offs between the two metrics: some may tolerate slightly longer access latencies to benefit from lower energy requirements, while others may favor shorter access latencies at the cost of higher energy expenditures. To provide data broadcast service providers with the freedom to trade-off between both metrics in an adjustable way, we propose a new flexible and parameterizable air- indexing scheme, called FlexInd. FlexInd is a hybrid indexing method that takes advantage of three separate air-indexing approaches, namely (a) no-indexing, (b) exponential indexing, and (c) flexible distributed indexing, to optimize either access latency or tuning time with certain performance guarantees on the other metric. Based on the access latency or energy conservation requirements imposed on the system, FlexInd chooses among the three indexing schemes the one which yields the best performance results with the access latency or tuning time bounded by a given limit. A performance study confirms that FlexInd is able to achieve lower average access latencies and tuning times than existing indexing schemes since it provides greater flexibility in trading-off access efficiency for power expenditure and vice versa.


Data Item Access Latency Mobile Client Indexing Scheme Index Tree 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • André Seifert
    • 1
  • Jen-Jou Hung
    • 2
  1. 1.Database Research GroupUniversity of KonstanzKonstanzGermany
  2. 2.Department of Information ManagementNational Taiwan University of Science and TechnologyTaipeiTaiwan, R.O.C

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