NeTS: Small: Principles and Protocols for Traffic-Insensitive Performance in Wireless Networks

智能手机和其他智能无线设备的快速增长产生了大量多样化的流量，从发送警告消息到通过蜂窝网络、物联网和网络物理系统等无线网络观看在线视频。如此广泛的通信量要求开发具有通信量不敏感性能的无线算法，在某种意义上，网络性能(如吞吐量和延迟)不依赖于除平均通信量负载之外的网络通信量的分布。在高度异质的无线应用中，这是非常有价值的。本项目的目标是使无线算法设计能够对多样化的服务需求具有健壮性，并满足未来无线系统严格的性能需求。该研究项目还将与PI的本科和研究生课程紧密结合，为本科生和高中生提供无线网络技术的实践经验。该项目旨在建立高效、可适应和可扩展的算法，对渗透到几乎每个无线系统的不同无线流量具有健壮性。这就需要新的动态算法和分析框架来处理延迟和短期公平性不敏感度，这对于实时应用来说是非常重要的。为此，该项目将回答以下八个问题，这些问题解决了流行无线系统的关键要素和挑战：(1)对于流到达和离开的现实模型，是否有实现良好吞吐量的算法，时延和短期公平性不敏感？(2)如何在多通道基站中实现这样的算法？(3)如何在基站协调有限的上行链路中实现这样的算法？(4)是否可以以纯分布式的方式实现这样的算法？(5)有什么好的数学模型来研究这种算法对流量大小分布的时延不敏感度？(6)算法是否具有良好的短期公平性性能？(7)对于流的到达和离开，有什么好的模型它们如何影响算法的性能？(8)如何通过实验室实验来验证算法？该研究的创新之处在于开发了适用于各种无线系统的高效、健壮和易于实现的调度算法，以及分析延迟和短期公平性不敏感性的方法。

The rapid growth of smart phones as well as other intelligent wireless devices generates significant amount of diversified traffic ranging from sending warning messages to watching online videos over wireless networks such as cellular networks, Internet of Things, and cyber-physical systems. Such wide range of traffic calls for the development of wireless algorithms with traffic-insensitive performance in the sense that the network performance (such as throughput and latency) does not depend on the distribution of network traffic except the mean traffic load. This is tremendously valuable in the presence of highly heterogeneous wireless applications. The goal of this project is to enable the wireless algorithm design to be robust to the diversified service demands and meet the stringent performance needs of future wireless systems. This research project will also be closely integrated with PI's undergraduate and graduate courses, and will provide hand-on experiences for undergraduate and high school students in wireless networking technology.This project aims to establish efficient, adaptable and scalable algorithms that are robust to the diverse wireless traffic penetrating almost every wireless system. This calls for new dynamic algorithms and analytical framework for both delay and short-term fairness insensitivity, which are extremely important for real-time applications. Towards this end, the project will answer the following eight questions that address key elements and challenges of popular wireless systems: (1) For a realistic model of flow arrivals and departures, is there an algorithm that achieves good throughput, delay and short-term fairness insensitivity? (2) How can such an algorithm be implemented in a multi-channel base station? (3) How can such an algorithm be implemented in the uplink with limited coordination by the base station? (4) Is it possible to implement such an algorithm in a purely distributed way? (5) What are good mathematical models to study the delay insensitivity of such algorithms to flow-size distributions? (6) Does the algorithm have good short-term fairness performance? (7) What are good models for arrivals and departures of flows and how do they affect the performance of the algorithm? (8) How does one validate the algorithms using laboratory experiments? The novelty in the proposed research lies in the development of efficient, robust and easily implementable scheduling algorithms in various wireless systems as well as the methodology for analyzing both delay and short-term fairness insensitivity.