两跳无线网络中最小化信息年龄的拓扑结构优化算法

    A Topology Optimization Algorithm for Minimizing Information Age in Two-Hop Wireless Networks

    • 摘要: 信息年龄是一种最近提出的作为从目的节点的角度衡量数据新鲜度的度量。本文围绕正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)无线网络中的信息年龄(Age of Information, AoI)最小化问题展开研究。现有工作均假设网络的拓扑结构是给定的,并在此基础上设计优化信息年龄的数据调度算法。为了进一步优化两跳网络模型中的信息年龄,本文研究了两跳无线网络中最小化信息年龄的拓扑结构优化算法。首先,在共享信道和泊松到达/指数服务模型下,推导了源节点至中继节点及中继节点至目的地节点的AoI数学表达式,揭示了AoI与网络负载率之间的非线性关系。给出了两跳无线网络中的信息年龄下界,并证明中继节点的最优负载率为0.457。进一步地,在OFDM场景中综合考虑数据包大小、传输距离和信道速率等关键参数,设计了一种两阶段中继节点选择算法,通过中继节点负载率与理论最优阈值选出最优中继节点。仿真结果表明,该算法在多种网络密度、负载和数据规模条件下均显著优于基准方法,平均AoI降低幅度达32个百分点。

       

      Abstract: Age of Information (AoI) has been proposed as a new metric to quantify data freshness from the point of destination. In this research, the problem of minimizing AoI in orthogonal frequency division multiplexing (OFDM) wireless networks is focused on. Since all existing works assume that the network topology is given and then propose the efficient scheduling algorithms on the basis of given topology, a study is focused on the work for AoI optimization with topology control in a two-hop OFDM-based wireless networks. Firstly, under the Poisson arrival service model, the mathematical expressions of AoI from the source node to the relay node and from the relay node to the aggregation node are derived, revealing the nonlinear relationship between AoI and network load rate. The lower bound of the average AoI of whole network is theoretically analyzed, and the optimal load rate is proved to be 0.457. Furthermore, a two-stage relay node selection algorithm is designed in the OFDM scenario, taking into account key parameters such as packet size, transmission distance, and channel rate, in which the optimal relay node is selected based on the load rate and theoretical optimal threshold. The simulation results show that the algorithm is significantly better than the baseline strategies under various network density, load, and data size conditions, with an average AoI reduction of up to 32%.

       

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