In this article we propose a novel paradigm of socially-motivated cooperative mobile edge computing, where the social tie structure among mobile and wearable device users is leveraged for achieving effective and trustworthy cooperation for collaborative computation task executions. We envision that a combination of local device computation and networked resource sharing empowers the devices with multiple flexible task execution approaches, including local mobile execution, D2D offloaded execution, direct cloud offloaded execution, and D2D-assisted cloud offloaded execution. Specifically, we propose a system model for cooperative mobile edge computing where a device social graph model is developed to capture the social relationship among the devices. We then devise a socially- aware bipartite matching based cooperative task offloading algorithm by integrating the social tie structure into the device computation and network resource sharing process. We evaluate the performance of socially-motivated cooperative mobile edge computing using both Erdos-Renyi and real-trace based social graphs, which corroborates the superior performance of the proposed socially-aware mechanism.

中文翻译：

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社交合作的移动边缘计算

在本文中，我们提出了一种基于社会动机的协作移动边缘计算的新颖范例，其中利用移动和可穿戴设备用户之间的社交联系结构来实现有效且可信赖的协作，以执行协作计算任务。我们设想本地设备计算和网络资源共享的组合为设备提供了多种灵活的任务执行方法，包括本地移动执行，D2D卸载执行，直接云卸载执行和D2D辅助云卸载执行。具体而言，我们提出了一种用于协作移动边缘计算的系统模型，其中开发了一种设备社交图模型来捕获设备之间的社交关系。然后，我们通过将社交联系结构集成到设备计算和网络资源共享过程中，设计出一种基于社交意识的双向匹配的协作任务卸载算法。我们使用Erdos-Renyi和基于真实轨迹的社交图评估社交动机的协作移动边缘计算的性能，这证实了所提出的社交意识机制的优越性能。