Ad hoc Networking with Swarm Intelligence

具有群体智能的自组织网络

• 批准号: 0240398
• 负责人: Chien-Chung Shen
• 金额: $ 35万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-06-01 至 2006-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0240398&HistoricalAwards=false
• 关键词: Ad; hoc; Networking; Swarm; Intelligence

This research project aims at applying the swarm intelligence framework to design a new class of networking protocols for mobile wireless ad hoc networks, facilitated attractive features such as scalability, autonomy, robustness, and fault-tolerance for routing, topology control and energy conservation. The basic idea is inspired by the collective activities of social insects, and utilizes small packets equivalent to ants in the real world. These packets, traveling like ants, deposit some information at nodes they visit similar to the way ants lay pheromone trails. This information, in turn, affects the behavior of other ant packets. With this form of indirect communication, the deployment of ant-like packets resembles a distributed reinforcement learning system that evolves itself to an optimal state, based on the current condition of the environment. This project will characterize the behavior and study the performance of swarm intelligence for ad hoc networking protocols based on probability, reinforcement learning, and stochastic control theories, in addition to large-scale simulation studies. To cope with network dynamics and mobility efficiently, the ad-hoc networks based on swarm intelligence are expected to learn and inherently adapt to changes in network states.

本研究项目旨在应用群体智能框架为移动无线自组网设计一类新的组网协议，具有良好的可扩展性、自主性、健壮性、路由容错性、拓扑控制和节能等特点。基本想法的灵感来自于群居昆虫的集体活动，并利用相当于现实世界中蚂蚁的小包裹。这些信息包像蚂蚁一样行进，在它们访问的节点存储一些信息，类似于蚂蚁放置信息素踪迹的方式。这些信息反过来会影响其他ANT数据包的行为。通过这种形式的间接通信，蚂蚁类分组的部署类似于分布式强化学习系统，该系统基于环境的当前条件将自身进化到最佳状态。该项目将基于概率、强化学习和随机控制理论来描述自组织网络协议的行为，并研究群体智能的性能，此外还将进行大规模的仿真研究。为了有效地应对网络的动态和移动性，基于群体智能的自组织网络被期望学习并内在地适应网络状态的变化。