CIF: Small: Collaborative Research: Communicating While Computing: Mobile Fog Computing Over Wireless Heterogeneous Networks

CIF：小型：协作研究：计算时通信：无线异构网络上的移动雾计算

• 批准号: 1527625
• 负责人: Gesualdo Scutari
• 金额: $ 22.48万
• 依托单位: SUNY at Buffalo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2015-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1527625&HistoricalAwards=false
• 关键词: CIF; Small; Collaborative; Research; Communicating

An increasing number of applications, including surveillance, medical monitoring, automatic translations and gaming, rely on the capability of mobile wireless devices to carry out computation-intensive tasks in a timely manner. This requirement conflicts with the expectation that mobile devices should run on a battery without needing frequent recharging. A promising solution to this challenge is mobile cloud computing, that is, the offloading of computation-intensive tasks to a cloud service provider by means of wireless transmission. However, the energy and latency entailed by wireless transmission may offset the potential gains of mobile cloud computing. This project proposes to tackle the outlined problem via the development of effective, low-complexity, scalable and flexible offloading strategies that operate over a mobile fog computing architecture, in which small-cell base stations are endowed with computing capabilities to offer proximate wireless access and computing. The insights gained from the successful completion of this project will be beneficial for a gamut of other exciting problem domains that require large-scale optimization, including big data mining, signal processing, machine learning, and smart grid. The research agenda is complemented by a multidisciplinary educational plan that targets both undergraduate and graduate students via hands-on learning and experimentation activities. Industrial collaboration is also envisaged through internship and co-op opportunities. The inter-layer optimization of the computation and communication resources in a mobile fog computing network yields unstructured nonconvex mixed-integer problems, which are unexplored and challenging, and whose formulation depends on whether the mobile applications are splittable, i.e., divisible into subtasks that can be individually offloaded, or not. Since the problems at hand do not lend themselves to the application of existing iterative optimization techniques, such as Difference-of-Convex programming, a class of scalable and flexible solution methods with controllable convergence, complexity and overhead is introduced based on a novel successive convex approximation framework. In the case of splittable applications, the analytical and algorithmic framework is augmented by the application of message passing strategies that leverage the call graph representation of the mobile applications.

越来越多的应用程序，包括监视，医疗监控，自动翻译和游戏，依靠移动无线设备的功能及时执行计算密集型任务。这一要求与期望移动设备应在电池上运行而无需频繁充电的期望发生冲突。解决这一挑战的一个有希望的解决方案是移动云计算，即通过无线传输将计算密集型任务的卸载卸载到云服务提供商。但是，无线传输所带来的能量和延迟可能会抵消移动云计算的潜在增长。该项目建议通过开发有效，低复杂性，可扩展性和灵活的卸载策略来解决概述的问题，这些策略通过移动雾计算体系结构运行，其中小型电池基站具有可提供接近无线访问和计算的计算能力。从该项目的成功完成中获得的见解将对其他需要大规模优化的令人兴奋的问题域（包括大数据挖掘，信号处理，机器学习和智能电网）有益。研究议程与多学科教育计划相辅相成，该计划通过动手学习和实验活动针对本科和研究生。还通过实习和合作机会设想工业合作。移动雾计算网络中计算和通信资源的层间优化产生的非结构化的非convex混合企业问题，这些问题尚未探索和具有挑战性，并且其配方取决于移动应用程序是否可以分开，即是否可以将可以单独卸载的子任务划分为子任务。由于手头的问题不适合应用现有迭代优化技术的应用，例如凸面编程差异，因此基于新颖的连续连续的convex近似框架，引入了具有可控收敛性，复杂性和开销的一类可扩展和灵活的解决方案方法。在可分配的应用程序的情况下，通过应用程序传递策略来利用移动应用程序的呼叫图表示的消息传递策略来增强分析和算法框架。