A framework for decentralized, dynamic discrete-event systems

分散的动态离散事件系统的框架

• 批准号: 138887-2010
• 负责人: Rudie, Karen
• 金额: $ 3.13万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=475899
• 关键词: framework; decentralized; dynamic; discrete; event

My research focuses on systems whose behaviour can be thought of as sequences of events or actions, which occur with various probabilities under timing constraints. I develop mathematical models to represent such discrete-event systems in which control involves multiple agents in order to automate problem-solving and testing of solutions. I will use my models to develop public emergency response procedures and to improve software development for distributed systems. In emergency response protocols, such as those needed for an epidemic, we need to model systems with many agents (e.g., patients, care workers, health units), where events occur with probabilities (e.g., if exposed to a disease, a patient may have a 40% chance of contracting the disease), where actions sometimes need to occur at specific times (e.g., patients in a hospital must eat at specific hours), and the group of agents changes over time (as patients recover or die and new patients become ill). My research will aid in determining protocols, procedures and policies for public emergencies. Improved emergency response protocols will benefit Canada by optimizing resource allocation and minimizing the harm done to people by crises such as disease outbreaks, water contamination, and massive electrical outages.

我的研究重点是系统的行为可以被认为是一系列的事件或行动，发生在不同的概率下的时间约束。我开发数学模型来表示这种离散事件系统，其中控制涉及多个代理，以自动解决问题和测试的解决方案。我将使用我的模型来开发公共应急响应程序，并改进分布式系统的软件开发。在紧急响应协议中，例如流行病所需的协议，我们需要对具有许多代理的系统进行建模（例如，患者、护理人员、卫生单位），其中事件以概率发生（例如，如果暴露于疾病，患者可能有40%的机会感染疾病），其中有时需要在特定时间采取行动（例如，医院里的病人必须在特定的时间进食），并且药剂组随着时间的推移而变化（随着病人康复或死亡以及新病人生病）。我的研究将有助于确定公共紧急情况的协议，程序和政策。改进后的应急响应协议将使加拿大受益，优化资源分配，最大限度地减少疾病爆发、水污染和大规模停电等危机对人民造成的伤害。