A Calculus Approach for Stochastic Networks: From Communication Networks to Smart Grids to Internet Water Army

随机网络的微积分方法：从通信网络到智能电网再到互联网水军

• 批准号: 261409-2013
• 负责人: Wu, Kui
• 金额: $ 1.82万
• 依托单位: University of Victoria
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634969
• 关键词: Calculus; Approach; Stochastic; Networks; Communication

Uncertainty is ubiquitous in real-world network systems. For example, in computer and communication networks, data traffic is highly coupled with end users' behavior and popular social events, both of which are not always deterministic; in modern power grids, distributed renewable energy sources (e.g., wind and solar energy) are important to reduce carbon dioxide emission, but renewable energy sources are normally uncertain, and their availability is hard to predict; in online social networks, people often interact with each other or follow social events in a probabilistic fashion. In all these network systems, it is fundamental to understand the uncertainty for better system control. In particular, it is critical to answer the following questions: How to model the uncertainty? What is the impact of uncertainty on the network performance? How to control the system in the presence of uncertain input? This research proposal addresses the above fundamental questions with Stochastic Network Calculus (SNC), an active yet still-nascent research field. Due to its short history and the lack of fast algorithms to handle the intensive computation involved in SNC, current SNC theory is still immature and has not seen many successes in practical applications. The objective of this research is to push the boundary of SNC and make it easily accessible and broadly applicable to a large range of practical problems. With mathematical analysis, simulation, and real-world experiments, the project will address three interweaving research themes in the development of SNC: performance modeling and evaluation, optimal stochastic control, and efficient numerical calculation. The research will enrich the toolset of stochastic modeling and stochastic control and will benefit many scientific and engineering areas, such as computer and communication networks, online social networks, and electric power networks. By applying the theoretical results into our existing industrial projects in Canada, such as power reliability of micro smart grids and distributed intelligent lighting control, we expect more effective control on stochastic network systems and high cost saving in Canadian IT and energy industries.

不确定性在现实世界的网络系统中无处不在。例如，在计算机和通信网络中，数据业务与终端用户的行为和流行的社会事件高度耦合，这两者并不总是确定的;在现代电网中，分布式可再生能源（例如，风能和太阳能）对于减少二氧化碳排放是重要的，但是可再生能源通常是不确定的，并且它们的可用性很难预测;在在线社交网络中，人们经常以概率的方式彼此交互或者关注社交事件。在所有这些网络系统中，了解不确定性对于更好的系统控制是至关重要的。特别是，它是至关重要的，以回答以下问题：如何建模的不确定性？不确定性对网络性能有什么影响？在输入不确定的情况下，如何控制系统？本研究计划通过随机网络演算（SNC）解决上述基本问题，SNC是一个活跃但仍处于萌芽状态的研究领域。由于SNC的发展历史较短，缺乏快速算法来处理SNC涉及的密集计算，目前SNC理论还不成熟，在实际应用中还没有看到很多成功。本研究的目的是推动SNC的边界，使其易于访问和广泛适用于大范围的实际问题。通过数学分析，模拟和真实世界的实验，该项目将解决SNC开发中三个交织的研究主题：性能建模和评估，最优随机控制和有效的数值计算。该研究将丰富随机建模和随机控制的工具集，并将有利于许多科学和工程领域，如计算机和通信网络，在线社交网络，电力网络。通过将理论结果应用到我们在加拿大现有的工业项目中，例如微型智能电网的电力可靠性和分布式智能照明控制，我们期望对随机网络系统进行更有效的控制，并在加拿大IT和能源行业节省大量成本。