A bandit algorithm for multi-path routing in the emergency convergence network

Fullerton Wu, Lin Zheng, Xiaoji Li
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Abstract

In the convergence network which consists of cognitive self-organization network and mobile cellular network (MCN), the emergency service requires the network with higher reliability and quality of service (QoS). However, the time-variant factors such as spectrum, channel, network topology, node energy, as well as the gateway performance make the stochastic optimization problem of emergency service complex. In this paper, we create an optimum model which is based on the restless bandit theory[1], and propose an optimum algorithm for multi-path routing selection by considering the routing cross and overlap. In our algorithm, the multi-mode gateways are regarded as the key nodes to construct the routes between cognitive self-organization network and mobile cellular network. The cross and overlapped routes are taken into consideration to loosen and expand the routes set for selection. The communication process is divided into a few path decision stages, and some paths for multicast[2][3] communication are activated according to their real-time status in each stage. The trade-off between delay and energy efficiency is made for multi-path selection. Simulation results verify that our algorithm owns outstanding performance on decreasing delay and improving energy efficiency.
紧急收敛网络中多路径路由的强盗算法
在由认知自组织网络和移动蜂窝网络(MCN)组成的融合网络中,应急服务对网络可靠性和服务质量(QoS)的要求更高。然而,频谱、信道、网络拓扑、节点能量以及网关性能等时变因素使得应急服务的随机优化问题变得复杂。本文基于不宁土匪理论[1]建立了最优模型,提出了一种考虑路由交叉和重叠的多路径路由选择最优算法。该算法将多模式网关作为构建认知自组织网络与移动蜂窝网络之间路由的关键节点。考虑交叉和重叠的路线,使可供选择的路线集更加松散和扩展。将通信过程划分为若干个路径决策阶段,并根据各阶段的实时状态激活部分多播[2][3]通信路径。在多路径选择中,对时延和能效进行了权衡。仿真结果表明,该算法在降低时延和提高能效方面具有优异的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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