Ad hoc Networking with Swarm Intelligence

本研究计划旨在应用群智能架构设计一种新的移动的无线自组织网络的网络协议，促进有吸引力的功能，如可扩展性，自治性，鲁棒性和容错路由，拓扑控制和节能。其基本思想受到社会性昆虫集体活动的启发，并利用了相当于真实的世界中蚂蚁的小包。这些数据包像蚂蚁一样移动，在它们访问的节点上存放存款一些信息，类似于蚂蚁放置信息素的方式。这些信息反过来会影响其他蚂蚁数据包的行为。通过这种形式的间接通信，类似蚂蚁的数据包的部署类似于一个分布式强化学习系统，该系统根据环境的当前条件将自身进化到最佳状态。本项目将基于概率、强化学习和随机控制理论，以及大规模的仿真研究，描述行为特征并研究群体智能在ad hoc网络协议中的性能。为了有效地科普网络的动态性和移动性，基于群体智能的ad-hoc网络被期望能够学习并内在地适应网络状态的变化。

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.