Efficient algorithms for scheduling XML data in a mobile wireless broadcast environment

Qin, Yongrui and Wang, Hua and Zhang, Ji and Tao, Xiaohui and Zhang, Wei Emma and Taylor, Kerry and Sheng, Quan Z. (2015) Efficient algorithms for scheduling XML data in a mobile wireless broadcast environment. In: 21st IEEE International Conference on Parallel and Distributed Systems (ICPADS 2015), 14-17 Dec 2015, Melbourne, Australia.

Abstract

This paper tackles the key scheduling problem of
reducing the overall wait time of mobile clients in wireless data broadcast systems. Existing algorithms for data broadcast usually come with various constraints. Specifically, periodic broadcast generally makes assumptions that the clients’ queries are already
known and the distribution of access frequencies of their queries can be obtained in advance while on-demand broadcast requires that all interested clients submit their queries before they tune in and access data on air. However, in periodic broadcast, new mobile clients may join in and existing mobile clients may leave anytime; in on-demand broadcast, high uplink communication
cost may occur as all clients have to submit their queries
every time. Based such observations, in this work, we study
the scheduling problem of XML data broadcast in a hybrid
mode, where the system supports both periodic broadcast and ondemand broadcast services at the same. By taking the structural similarity between XML documents into account, only a small portion of mobile clients would be involved in the scheduling process and all mobile clients can be served more effectively. In this way, communication cost at the client side can be reduced greatly. A formal theoretical analysis of the proposed technique is presented. Based on the analysis, a novel clustering-based scheduling algorithm is developed. Moreover, we utilize an aging method to predict the distribution of incoming queries based
on small samples of queries from mobile clients. Finally, we
evaluate the approach through a set of experiments and the results show that it can significantly improve access efficiency for mobile clients.


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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Agricultural, Computational and Environmental Sciences
Date Deposited: 29 Feb 2016 05:36
Last Modified: 13 Feb 2017 02:33
Fields of Research : 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
08 Information and Computing Sciences > 0805 Distributed Computing > 080502 Mobile Technologies
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
URI: http://eprints.usq.edu.au/id/eprint/28470

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