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

机译:D2D内容共享方案中基于社交意识速率的内容共享模式选择

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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.
机译:设备到设备(D2D)内容共享已成为一种有前途的解决方案,可以支持多媒体内容在本地服务中的日益普及。考虑到内容位置的随机性,设备的有限存储和传输能力以及利他和自私的用户行为的共存,如何最佳地将需求者与内容提供者相匹配以及如何激发有效的合作对于实现D2D内容共享的全部好处。特别是当基站到设备(B2D),D2D和新颖的多D2D共享模式共存时,内容共享模式选择的问题在这种匹配中起主要作用。在本文中,我们引入了一种社会意识速率的概念,该概念将社会知识的社会自私性与链接速率相结合,以确保物理链接质量和有效的合作。然后,将基于社交意识的基于速率的内容共享模式选择问题建模为最大加权混合匹配问题,该问题可以通过计算简化为受拟阵约束的亚模福利问题。随后,我们开发了一种尽力而为的分布式算法框架,该框架显示了各种计算复杂度和逼近率的替代方案,以满足各种实际需求。

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