Seed selection for data offloading based on social and interest graphs
| Autor: | Minchao Lu, Caoyuan Li, Jianwei Chen, Jianbo Li, Ying Li |
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| Rok vydání: | 2018 |
| Předmět: |
Theoretical computer science
Computer science Mobile broadband Applied Mathematics Cellular traffic 020206 networking & telecommunications 02 engineering and technology Computer Science Applications Biomaterials Data sharing Interpersonal ties Mechanics of Materials Modeling and Simulation 0202 electrical engineering electronic engineering information engineering Cellular network 020201 artificial intelligence & image processing Electrical and Electronic Engineering Duration (project management) Selection (genetic algorithm) TRACE (psycholinguistics) |
| Popis: | Copyright © 2018 Tech Science Press The explosive growth of mobile data demand is becoming an increasing burden on current cellular network. To address this issue, we propose a solution of opportunistic data offloading for alleviating overloaded cellular traffic. The principle behind it is to select a few important users as seeds for data sharing. The three critical steps are detailed as follows. We first explore individual interests of users by the construction of user profiles, on which an interest graph is built by Gaussian graphical modeling. We then apply the extreme value theory to threshold the encounter duration of user pairs. So, a contact graph is generated to indicate the social relationships of users. Moreover, a contact-interest graph is developed on the basis of the social ties and individual interests of users. Corresponding on different graphs, three strategies are finally proposed for seed selection in an aim to maximize overloaded cellular data. We evaluate the performance of our algorithms by the trace data of real-word mobility. It demonstrates the effectiveness of the strategy of taking social relationships and individual interests into account. |
| Databáze: | OpenAIRE |
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