doi: 10.4304/jsw.9.9.2378-2383
Warehousing Massive Mobile Datasets
Abstract—Nowadays, scientists can collect and analyze massive mobile data generated by various sensors and applications of smart phones. smart phones have become an important platform for the understanding of social activities, such as community detection, social dynamics and influence. It is extremely important to store and retrieve mobile data efficiently for various data mining tasks. In this paper, we propose Mobile Data Warehouse (MobileDW) model which is based on GraphChi, a system designed for large-scale graph computation on one PC. We propose multi-shard data structure and Time-based Parallel Sliding Windows (TPSW) to store Social data such as call logs and SMS. We further propose Mobile Index (MIndex) structure and Mobile Position Compression Algorithm (MPCA) to warehouse Position data such as GPS, Bluetooth etc. The MIndex structure can compress Position data significantly. The data compression process is based on the following observations: (1) The position of the individual users within a certain period of time often unchanged. (2) A crowd of people tend to move and stay together. Experimental results demonstrate the effectiveness and efficiency of Mobile Data Warehouse.
Index Terms—MobileDW; MIndex; MPCA, TPSW
Cite: Zhipeng Liu, Dechang Pi, "Warehousing Massive Mobile Datasets," Journal of Software vol. 9, no. 9, pp. 2378-2383, 2014.
General Information
ISSN: 1796-217X (Online)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
CNKI, Google Scholar, ProQuest,
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Directory, WorldCat, etcE-mail: jsweditorialoffice@gmail.com
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