In this paper, a mobile edge computing framework with multi-user computation offloading and transmission scheduling for delay-sensitive applications is studied. In the considered model, computation tasks are generated randomly at mobile users along the time. For each task, the mobile user can choose to either process it locally or offload it via the uplink transmission to the edge for cloud computing. To efficiently manage the system, the network regulator is required to employ a network-wide optimal scheme for computation offloading and transmission scheduling while guaranteeing that all mobile users would like to follow (as they may naturally behave strategically for benefiting themselves). By considering tradeoffs between local and edge computing, wireless features and noncooperative game interactions among mobile users, we formulate a mechanism design problem to jointly determine a computation offloading scheme, a transmission scheduling discipline, and a pricing rule. A queueing model is built to analytically describe the packet-level network dynamics. Based on this, we propose a novel mechanism, which can maximize the network social welfare (i.e., the network-wide performance), while achieving a game equilibrium among strategic mobile users. Theoretical and simulation results examine the performance of our proposed mechanism, and demonstrate its superiority over the counterparts.

中文翻译：

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一种用于延迟敏感应用的多用户移动计算卸载和传输调度机制

在本文中，研究了一种用于延迟敏感应用程序的具有多用户计算卸载和传输调度的移动边缘计算框架。在所考虑的模型中，计算任务是随时间在移动用户处随机生成的。对于每项任务，移动用户可以选择在本地处理它或通过上行链路传输将其卸载到边缘以进行云计算。为了有效地管理系统，网络监管者需要采用全网优化方案来进行计算卸载和传输调度，同时保证所有移动用户都愿意遵循（因为他们可能自然而然地为了使自己受益而采取战略性行动）。通过考虑本地和边缘计算、无线功能和移动用户之间的非合作游戏交互之间的权衡，我们制定了一个机制设计问题来共同确定计算卸载方案、传输调度规则和定价规则。建立了一个排队模型来分析性地描述数据包级网络动态。基于此，我们提出了一种新机制，可以最大化网络社会福利（即全网性能），同时实现战略移动用户之间的博弈均衡。理论和仿真结果检验了我们提出的机制的性能，并证明了其优于同行。这可以最大化网络社会福利（即全网性能），同时实现战略移动用户之间的博弈均衡。理论和仿真结果检验了我们提出的机制的性能，并证明了其优于同行。这可以最大化网络社会福利（即全网性能），同时实现战略移动用户之间的博弈均衡。理论和仿真结果检验了我们提出的机制的性能，并证明了其优于同行。