VNF Scheduling and Sampling Rate Maximization in Energy Harvesting IoT Networks

IF 7.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS IEEE Transactions on Mobile Computing Pub Date : 2024-08-13 DOI:10.1109/TMC.2024.3442809
Longji Zhang;Kwan-Wu Chin
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Abstract

This paper studies virtual network function (VNF) scheduling in energy harvesting virtualized Internet of Things (IoT) networks. Unlike prior works, sensor devices leverage imprecise computation to vary their computational workload to conserve energy at the expense of computation quality. In this respect, an optimization problem of interest is to maximize the minimum VNF computation/execution quality. To this end, this paper presents the first mixed integer linear program (MILP) that optimizes i) the VNFs executed by each sensor device, ii) the computational resources allocated to VNFs, iii) sampling rate or amount of data supplied by sensor devices to VNFs, iv) the routing of samples to VNFs and forwarding of computation results, and v) link scheduling. In addition, this paper also proposes a heuristic, called sampling control and computation scheduling (SCACS), for large-scale networks. The simulation results show that SCACS reaches 81.66% of the optimal quality. In addition, the application completion rate when using SCACS is at most 39% higher than a benchmark that randomly selects nodes to sample targets and execute VNFs.
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能量收集物联网网络中的 VNF 调度和采样率最大化
本文研究了能量收集虚拟化物联网(IoT)网络中的虚拟网络功能(VNF)调度。与之前的研究不同,传感器设备利用不精确计算来改变其计算工作量,从而以牺牲计算质量为代价来节约能源。在这方面,一个值得关注的优化问题是最大限度地降低 VNF 的计算/执行质量。为此,本文首次提出了混合整数线性程序 (MILP),可优化 i) 每个传感器设备执行的 VNF;ii) 分配给 VNF 的计算资源;iii) 传感器设备向 VNF 提供的采样率或数据量;iv) 向 VNF 发送采样的路由和计算结果的转发;v) 链路调度。此外,本文还为大规模网络提出了一种启发式方法,称为采样控制和计算调度(SCACS)。仿真结果表明,SCACS 达到了最佳质量的 81.66%。此外,使用 SCACS 时的应用完成率比随机选择节点采样目标和执行 VNF 的基准最多高出 39%。
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来源期刊
IEEE Transactions on Mobile Computing
IEEE Transactions on Mobile Computing 工程技术-电信学
CiteScore
12.90
自引率
2.50%
发文量
403
审稿时长
6.6 months
期刊介绍: IEEE Transactions on Mobile Computing addresses key technical issues related to various aspects of mobile computing. This includes (a) architectures, (b) support services, (c) algorithm/protocol design and analysis, (d) mobile environments, (e) mobile communication systems, (f) applications, and (g) emerging technologies. Topics of interest span a wide range, covering aspects like mobile networks and hosts, mobility management, multimedia, operating system support, power management, online and mobile environments, security, scalability, reliability, and emerging technologies such as wearable computers, body area networks, and wireless sensor networks. The journal serves as a comprehensive platform for advancements in mobile computing research.
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