NDLI: Exploring the Use of Diverse Replicas for Big Location Tracking Data

Content Provider	IEEE Xplore Digital Library
Author	Ye Ding Haoyu Tan Wuman Luo Ni, L.M.
Copyright Year	2014
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China (Ye Ding; Haoyu Tan; Wuman Luo; Ni, L.M.)
Abstract	The value of large amount of location tracking data has received wide attention in many applications including human behavior analysis, urban transportation planning, and various location-based services (LBS). Nowadays, both scientific and industrial communities are encouraged to collect as much location tracking data as possible, which brings about two issues: 1) it is challenging to process the queries on big location tracking data efficiently, and 2) it is expensive to store several exact data replicas for fault-tolerance. So far, several dedicated storage systems have been proposed to address these issues. However, they do not work well when the query ranges vary widely. In this paper, we present the design of a storage system using diverse replica scheme which improves the query processing efficiency with reduced cost of storage space. To the best of our knowledge, we are the first to investigate the data storage and processing in the context of big location tracking data. Specifically, we conduct in-depth theoretical and empirical analysis of the trade-offs between different spatio-temporal partitioning schemes as well as data encoding schemes. Then we propose an effective approach to select an appropriate set of diverse replicas, which is optimized for the expected query loads while conforming to the given storage space budget. The experiment results confirm that using diverse replicas can significantly improve the overall query performance. The results also demonstrate that the proposed algorithms for the replica selection problem is both effective and efficient.
Starting Page	83
Ending Page	92
File Size	998273
Page Count	10
File Format	PDF
ISSN	10636927
e-ISBN	9781479951697
DOI	10.1109/ICDCS.2014.17
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-30
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Encoding Query processing Context Algorithm design and analysis Big data Organizations Linear programming
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software

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