Energy efficient cloud computing for mobile users

用于移动的设备的云计算通过经由无线网络连接将复杂的计算任务卸载到更强大的服务器（云）来提供在移动终端上执行复杂的计算任务的机会。云计算系统设计者的目标包括能源效率（在所有系统组件处：无线设备、无线信道和基础设施以及云服务器）、延迟和执行时间、用户效用和/或满意度、资源利用的公平性等。在该提议中，主要关注的是所有系统级别的能量效率，以及它对其他目标（例如等待时间最小化或公平性）的影响。** 虽然能源使用可能是移动的云计算的主要目标，但由于移动终端电池充电的寿命很短，因此其研究通常是在某些理想化的假设下进行的，以便于分析。我们建议在现实条件下研究移动的云卸载（MCO），这些条件包括：（a）具有自私代理（移动的用户，服务器提供商，基础设施运营商等）的竞争环境;试图优化它们的效用，（B）硬约束的存在，例如任务期限，以及（c）移动的云计算基础设施的放置和供应，例如用于车辆无线通信的微云和路边单元。由多个移动的用户卸载相互依赖的任务导致在多个系统瓶颈处（诸如无线信道、接入点或云服务器处）的竞争行为和策略决策。摆脱中央协调，并在上述现实限制下将决策责任从基础设施设计者/运营者转移到个人用户身上，是本提案的中心主题。在MCO中，移动的用户可以决定不将其任务卸载到云（例如，由于任务最后期限违反），而能够满足所有硬约束的另一个用户可以决定卸载，因为这将通过使用系统能量来执行其任务而增加其效用。在云服务提供商方面，自私的行为表现在努力实现利润最大化和能源消耗最小化，但合作（在博弈论意义上）也是如此，如果它可以带来更好的服务和更大的移动的用户参与，因此，更好的提供商效用。将决策责任委托给个体代理会导致系统资源的次优利用。该提案的重点是研究系统效率低下，由于自私的行为，减轻其影响，通过设计的调度和定价政策，以及设计和分析的有效算法的建设和供应的基础设施所需的移动的云计算。

Cloud computing for mobile devices offers the opportunity of performing complex computational tasks on a mobile device by offloading them to more powerful servers (the cloud) through wireless network connections. The objectives of cloud computing system designers include energy efficiency (at all systems components: the wireless device, the wireless channel and infrastructure, and the cloud servers), latencies and execution times, user utility and/or satisfaction, fairness in resources utilization, etc. In this proposal, the main concern is energy efficiency at all system levels, and its effects on other objectives (such as latency minimization or fairness). ******Although energy use has probably been the primary objective in mobile cloud computing, due to the short life-time of a mobile device battery charge, its study has usually been done under certain idealized assumptions that facilitate analysis. We propose to study mobile cloud offloading (MCO) under realistic conditions that include (a) a competitive environment with selfish agents (mobile users, server providers, infrastructure operators, etc.) trying to optimize their utility, (b) the existence of hard constraints such as task deadlines, and (c) the placement and provisioning of mobile cloud computing infrastructure, such as cloudlets and Road Side Units for vehicular wireless communications. The offloading of interdependent tasks by several mobile users leads to competitive behaviour and policy decisions at several system bottlenecks, such as the wireless channels, the Access Points, or at cloud servers. Getting rid of central coordination and moving the decision responsibility from the infrastructure designer/operator to the individual user under the realistic constraints mentioned above is a central theme of this proposal. In MCO, a mobile user may decide not to offload its task to the cloud (e.g., due to task deadline violations), while another user who can meet all hard constraints may decide to offload, since that would increase its utility by using system energy to execute its task. On the side of cloud service providers, selfish behaviour is displayed in an effort to maximize profits and minimize energy consumption, but so does cooperation (in the game-theoretic sense), if it can lead to better services and larger mobile users participation, and, therefore, better provider utility. The delegation of decision responsibility to individual agents leads to suboptimal utilization of system resources. This proposal is focused on the study of system inefficiencies due to selfish behaviour, the alleviation of their effect through the design of scheduling and pricing policies, as well as the design and analysis of efficient algorithms for the building and provisioning of the infrastructure needed for mobile cloud computing.