Mobility, Search and Communication

移动、搜索和通信

• 批准号: RGPIN-2016-06213
• 负责人: Kranakis, Evangelos
• 金额: $ 2.26万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=655968
• 关键词: Mobility; Search; Communication

Some of the most striking developments in mobile agent computing today are occurring due to the synergy between communication, search and mobility. Equipped with locomotion mechanisms and outfitted with hardware and software for perception, mobile robots can move and perceive the world. A mobile robot is required to navigate through a well-defined domain by controlling its motion and applying its perception capabilities in the most effective and efficient manner, while at the same time communicating its findings to the rest of the robots so as to facilitate the solution of well-defined network tasks. Current research on cooperative mobile agent (robot, sensor) systems suffers from a lack of understanding of the impact of mobility in performing fundamental communication and search tasks. More specifically, we are interested in understanding the following questions. How can a swarm of mobile agents navigate efficiently through a distributed interconnected environment to complete its computing tasks? Which agent capabilities and what knowledge can be leveraged? What is special about a particular problem that makes it solvable efficiently as opposed to alternatives?****This proposal will pursue three complementary research themes within the context of mobile agent computing. 1) How do critical regimes arise when agent mobility is employed to optimize various network tasks? 2) What is the cost of optimal co-operative search in graphs and geometric domains when all tasks are finished by all agents? 3) How do interactive graphs affect the stability and convergence of population protocols in networks? This project aims to advance our knowledge by pursuing these three research directions. Topics proposed are expected to play a significant role in the development of theoretical computer science and distributed computing. Our approach will employ algorithmic design methodologies as well as probabilistic and deterministic techniques in the context of distributed computing.****The general guiding principles of our approach are the following. 1) Provide a deeper understanding of the behavior of interacting communicating entities within a dynamic network based on the methodologies of algorithmic distributed computing. 2) Develop research techniques using rigorous mathematical models that satisfy strict and well-defined requirements and are motivated from practical considerations in the established research space of wireless ad hoc & sensor networks, robot search & mobility, biological distributed computing, and social networks. 3) Train Highly Qualifies Personnel at the PDF, PhD and Master's level as well as gifted undergraduates in these emerging research fields.** **

由于通信、搜索和移动性之间的协同作用，今天移动代理计算中一些最引人注目的发展正在发生。移动机器人配备了运动机构和感知硬件和软件，可以移动和感知世界。移动机器人需要通过控制其运动和以最有效和高效的方式应用其感知能力在一个定义良好的领域中导航，同时将其发现传达给其他机器人，以促进解决定义良好的网络任务。目前对协作移动代理（机器人、传感器）系统的研究缺乏对移动性在执行基本通信和搜索任务中的影响的理解。更具体地说，我们有兴趣了解以下问题。一群移动代理如何在分布式互联环境中高效导航以完成其计算任务？可以利用哪些代理功能和哪些知识？一个特定的问题有什么特别之处，使得它可以有效地解决，而不是替代方案？****本提案将在移动代理计算的背景下追求三个互补的研究主题。1)当使用代理移动性来优化各种网络任务时，如何产生关键制度？2)当所有智能体完成所有任务时，图域和几何域中最优合作搜索的成本是多少？3)交互图如何影响网络中群体协议的稳定性和收敛性？这个项目旨在通过这三个研究方向来推进我们的知识。所提出的主题有望在理论计算机科学和分布式计算的发展中发挥重要作用。我们的方法将在分布式计算的背景下采用算法设计方法以及概率和确定性技术。****我们方法的一般指导原则如下。1)基于算法分布式计算的方法，对动态网络中交互通信实体的行为有更深的理解。2)开发研究技术，使用严格的数学模型，满足严格和定义明确的要求，并从无线自组织和传感器网络，机器人搜索和移动，生物分布式计算和社交网络等已建立的研究空间的实际考虑出发。3)在新兴研究领域培养PDF、博士、硕士水平的高素质人才和有天赋的本科生。* * * *