Social Computing for Mobile Big Data in Wireless Networks
This work addresses the challenge of optimizing wireless networks through social computing, but it is incremental as it focuses on categorization and directions rather than new methods or results.
The paper tackles the problem of leveraging mobile big data from wireless networks by analyzing its social characteristics, categorizing real cellular network data, and identifying research directions for social computing applications.
Mobile big data contains vast statistical features in various dimensions, including spatial, temporal, and the underlying social domain. Understanding and exploiting the features of mobile data from a social network perspective will be extremely beneficial to wireless networks, from planning, operation, and maintenance to optimization and marketing. In this paper, we categorize and analyze the big data collected from real wireless cellular networks. Then, we study the social characteristics of mobile big data and highlight several research directions for mobile big data in the social computing areas.