卫星物联网中基于能量感知的自适应节能路由策略

Adaptive energy-efficient routing strategy based on energy aware in satellite Internet of Things

随着5G技术的发展和6G技术的研究,低轨卫星网络在卫星物联网中的地位越发重要,而作为网络核心技术的路由策略仍面临一些挑战。本文针对低轨卫星网络拓扑结构动态变化、链路的不连续性、卫星能量供应受限等问题,为了及时感知星间链路状态和卫星的能量并选择正确的路由,将卫星物联网中的路由选择问题转化为马尔可夫决策过程下的最优策略问题,提出一种基于Dueling DQN(Dueling Deep Q Network)的自适应节能路由算法。该算法通过改进DQN中神经网络的架构,大幅度地提升了学习的效果。仿真结果表明,与传统的DQN算法相比,该算法能有效降低系统能耗,均衡网络负载,提高网络吞吐量。

With the development of 5G technology and the research of 6G technology,LEO satellite networks have become increasingly important in the satellite Internet of Things.However,as the core technology of the network,routing strategies still face some challenges.In this paper,an intelligent sensing routing algorithm based on Dueling DQN(Dueling Deep Q Network)is proposed to address issues such as dynamic changes in the topology of low earth orbit satellite networks,link discontinuity,and limited satellite energy supply,which could sense the status of the inter-satellite link and the energy of the satellite in time and select the correct route,and the routing problem in the satellite Internet of Things is transformed into the optimal strategy problem in the Markov decision-making process.This algorithm greatly improves the learning effect by improving the architecture of neural networks in DQN.Simulation results show that compared with traditional DQN algorithm,this algorithm can effectively reduce system energy consumption,balance network load,and improve network throughput.