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首页> 外文期刊>IEEE transactions on mobile computing >A Multi-User Mobile Computation Offloading and Transmission Scheduling Mechanism for Delay-Sensitive Applications
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A Multi-User Mobile Computation Offloading and Transmission Scheduling Mechanism for Delay-Sensitive Applications

机译:时延敏感应用的多用户移动计算分流与传输调度机制

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摘要

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.
机译:本文研究了针对延迟敏感应用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。对于每个任务,移动用户可以选择在本地处理它,或者通过上行链路传输到边缘进行卸载以进行云计算。为了有效地管理系统,要求网络调节器采用全网范围内的最佳方案进行计算分流和传输调度,同时确保所有移动用户都愿意遵循(因为他们可能自然地从战略上受益于自己)。通过考虑本地和边缘计算之间的权衡,无线功能以及移动用户之间的非合作游戏交互,我们制定了一种机制设计问题,以共同确定计算分流方案,传输调度规则和定价规则。建立一个排队模型来分析性地描述数据包级别的网络动态。在此基础上,我们提出了一种新颖的机制,该机制可以在实现战略移动用户之间的博弈平衡的同时,最大化网络社会福利(即网络范围的绩效)。理论和仿真结果验证了我们提出的机制的性能,并证明了其优于同类机制的优越性。

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