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Article Dans Une Revue IEEE Wireless Communications Année : 2014

Mobility prediction in telecom cloud using mobile calls

Résumé

The proliferation of the telecom cloud has fostered increasing attention on location-based applications and services. Due to the randomness and fuzziness of human mobility, it still remains open to predict user mobility. In this article, we investigate the large-scale user mobility traces that are collected by a telecom operator. We find that mobile call patterns are highly correlated with the co-location patterns at the same cell tower at the same time. We extract such social connections from cellular call records stored in the telecom cloud, and further propose a mobility prediction system that can run as an infrastructure-level service in telecom cloud platforms. We implement the mobility pattern discovery into a cloud-based location tracking service that can make online mobility prediction for value-added telecom services. Finally, we conduct a couple of case studies on mobility-aware personalization and predictive resource allocation to elaborate how the proposed system drives a new mode of mobile cloud applications
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Dates et versions

hal-01262374 , version 1 (26-01-2016)

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Daqiang Zhang, Min Chen, Mohsen Guizani, Haoyi Xiong, Daqing Zhang. Mobility prediction in telecom cloud using mobile calls. IEEE Wireless Communications, 2014, 21 (1), pp.26 - 32. ⟨10.1109/MWC.2014.6757894⟩. ⟨hal-01262374⟩
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