Social-Aware Rate Based Content Sharing Mode Selection for D2D Content Sharing Scenarios

• Published in: IEEE transactions on multimedia Vol. 19; no. 11; pp. 2571 - 2582
• Main Authors: Wu, Dan, Zhou, Liang, Cai, Yueming
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.11.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Approximation algorithms; Centralization; Complexity theory; Computational modeling; Cooperation; Device-to-device (D2D) content sharing; Device-to-device communication; Distributed algorithms; Electronic mail; Matching; matroid; Modal choice; Multimedia; sharing mode selection; Social network services; social-aware rate; submodular maximization
• ISSN: 1520-9210; 1941-0077
• DOI: 10.1109/TMM.2017.2700621

Device-to-device (D2D) content sharing has become a promising solution to support the growing popularity of multimedia contents for local services. Considering the randomness of content location, the limited storage and transmission capability of devices, and the coexistence of altruistic and selfish user behaviors, how to optimally match the demanders to the providers of contents and how to stimulate an efficient cooperation are of importance for achieving the full benefits of D2D content sharing. Especially when the base-station-to-device (B2D), D2D, and novel multi-D2D sharing modes coexist, the issue of content sharing mode selection plays the predominant role in such matching. In this paper, we introduce a notion of social-aware rate, which combines the social selfishness from the social knowledge with the link rate to ensure the physical link quality and the effective cooperation together. Then, the social-aware rate-based content sharing mode selection problem is modeled as a maximum weighted mixed matching problem, which can be computationally reduced to a submodular welfare problem subject to a matroid constraint. Subsequently, we develop a best-effort distributed algorithm framework, which displays alternatives of various computation complexities and approximation ratios to satisfy the diverse practical needs.