物联网中信息新鲜度和能耗的权衡揭示及优化  

Revealing and Optimizing Trade-Offs Between Information Freshness and Energy Consumption in Internet of Things

作　　者：朱鹏 王海 秦蓁 景璐璐 王乐萍 ZHU Peng;WANG Hai;QING Zhen;JING Lulu;WANG Leping(College of Communications Engineering,Army Engineering University,Nanjing 210000,China;Department of Cyber Security and Informatization,Nanjing Forestry University,Nanjing 210000,China)

机构地区：[1]陆军工程大学通信工程学院,南京210000 [2]南京林业大学网络安全和信息化办公室,南京210000

出　　处：《计算机工程与应用》2024年第21期254-263,共10页Computer Engineering and Applications

基　　金：国家自然科学基金(62171465)。

摘　　要：无人机辅助物联网传感器节点(sensor nodes,SN)数据采集场景中,信息新鲜度和无人机能耗本质上是相互竞争的指标。为揭示两个指标之间的权衡,引入Pareto边界的概念,将该问题公式化为多目标混合整数线性规划问题,并应用Bender分解算法求解该问题。而后通过节点唤醒与睡眠机制与无人机轨迹的联合设计,共同优化两个指标,并最大限度地减少SN的最大能耗,将该联合设计公式化为混合整数非凸优化问题,通过应用逐次凸优化技术,提出了一种迭代算法来求解。仿真结果表明,所提出的方法能在两个竞争度量之间得出Pareto最优解。与悬停方案相比,所提设计中无人机能耗和信息新鲜度得到优化,同时显著节省了SN的能耗。In the context of unmanned aerial vehicle(UAV)assisted data collection for Internet of things sensor node,the freshness of information and UAV energy consumption are fundamentally competing metrics.To elucidate the trade-off between these two metrics,this paper introduces the concept of the Pareto boundary,formulating the problem as a multiobjective mixed integer linear programming problem,the Bender decomposition algorithm is applied to solve this problem.Subsequently,through the joint design of node wake-up/sleep mechanisms and UAV trajectories,the two metrics are collectively optimized,maximizing the reduction of the maximum energy consumption of SN,formulating the design as a mixed-integer non-convex optimization problem,and an iterative algorithm is proposed using sequential convex optimization techniques to find a suboptimal solution for design.Simulation results demonstrate that the proposed method can achieve Pareto optimal solutions between two metrics.Compared to the hover solution,the proposed design optimizes UAV energy consumption and information freshness while significantly saving energy consumption of SN.

关 键 词：无人机能耗 信息新鲜度 PARETO最优 SN能耗 唤醒与睡眠机制 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]