Collaborative Research: Resource Allocation for Time-Critical Communications in Wireless Networks

合作研究：无线网络中时间关键型通信的资源分配

• 批准号: 1609202
• 负责人: Lei Ying
• 金额: $ 20万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1609202&HistoricalAwards=false
• 关键词: Collaborative; Research; Resource; Allocation; Time

Time-critical instantiations of wireless networks such as vehicular networks, robotic systems, real-time surveillance, and networked control require stringent deadline requirements on packet transmissions. These emerging networks demand reliable and predictable transmissions over an unreliable, time-varying wireless medium to support applications such as warning messages, voice calls and video streaming. Despite remarkable progress in the design of wireless networks with maximum throughput and low delays over the last two decades, communications with hard deadlines in wireless networks remains a challenging open problem. Most existing works on delay performance in wireless networks focus on reducing average delays rather than guaranteeing hard deadlines. The goal of this project is to develop fundamental theories and distributed algorithms for transmitting packets with hard deadlines in wireless networks for time-critical applications. Technical advances in this project will contribute to the improvement of wireless systems for time-critical communications, including the so-called internet of things, cyber-physical systems, emergency response wireless networks, and sensor networks.The problem of supporting communications with hard deadlines in ad hoc wireless networks is very challenging because the capacity region of the network is arrival-dependent, and packet deadlines induce special types of spatial and temporal correlation. This project focuses on a comprehensive resource allocation solution for time-critical communications in wireless networks by utilizing the following four novel techniques: (1) a virtual link approach to achieve spatial-temporal resource allocation to guarantee end-to-end hard deadlines, (2) a deadline-aware random access algorithm, (3) a virtual frame approach to deal with the infinite temporal correlation among packets, and (4) deadline-aware PHY/MAC resource allocation. By exploiting these transformative technical approaches, the project will (1) design distributed algorithms for mission-critical wireless networks, (2) design resource allocation algorithms for supporting hard end-to-end deadlines for physical layer models beyond the collision model and (3) design joint routing/scheduling algorithms for multihop traffic flows with end-to-end deadline constraints. Education is a core component of this project. During the course of this project, research and education will be integrated by including new theories and algorithms developed in this project into graduate-level courses. Every effort will be made to involve undergraduates and students from under-represented students in this project.

时间关键的无线网络，如车辆网络，机器人系统，实时监控和网络控制的实例需要严格的数据包传输的最后期限要求。这些新兴的网络需要在不可靠的、时变的无线介质上进行可靠和可预测的传输，以支持警告消息、语音呼叫和视频流等应用。尽管在过去的二十年中，在具有最大吞吐量和低延迟的无线网络设计方面取得了显着进展，但无线网络中具有硬截止期限的通信仍然是一个具有挑战性的开放问题。现有的大多数工作在无线网络中的延迟性能集中在减少平均延迟，而不是保证硬的最后期限。本项目的目标是为时间要求严格的应用开发无线网络中具有硬截止期限的数据包传输的基础理论和分布式算法。 该项目的技术进步将有助于改善时间关键通信的无线系统，包括所谓的物联网，网络物理系统，应急响应无线网络和传感器网络。在自组织无线网络中支持具有硬截止期限的通信的问题非常具有挑战性，因为网络的容量区域是依赖于到达的，并且分组截止时间导致特殊类型的空间和时间相关性。本项目的重点是利用以下四种新技术为无线网络中的时间关键通信提供全面的资源分配解决方案：（1）虚拟链路方法，用于实现时空资源分配以保证端到端硬截止期限，（2）截止期限感知随机接入算法，（3）虚拟帧方法，用于处理分组之间的无限时间相关性，以及（4）最后期限感知的PHY/MAC资源分配。通过利用这些变革性的技术方法，该项目将（1）为关键任务无线网络设计分布式算法，（2）设计资源分配算法，以支持超出冲突模型的物理层模型的硬端到端截止期限，（3）为具有端到端截止期限约束的多跳流量设计联合路由/调度算法。教育是该项目的核心组成部分。在这个项目的过程中，研究和教育将通过包括在这个项目中开发的新理论和算法纳入研究生课程。将尽一切努力让本科生和代表性不足的学生参与这个项目。

项目成果

On Achieving Zero Delay with Power-of-d-Choices Load Balancing

通过 D 选择功率负载均衡实现零延迟

• 发表时间: 2018
• 期刊: IEEE International Conference on Computer Communications
• 作者: Liu, Xin;Ying, Lei
• 通讯作者: Ying, Lei

Learning Parallel Markov Chains over Unreliable Wireless Channels

通过不可靠的无线信道学习并行马尔可夫链

• DOI: 10.1109/ciss48834.2020.1570614323
• 发表时间: 2020
• 期刊: CISS
• 作者: Wang, Weichang;Ying, Lei
• 通讯作者: Ying, Lei