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SMDP-Based Radio Resource Allocation Scheme in Software-Defined Internet of Things Networks

机译:软件定义的物联网网络中基于SMDP的无线电资源分配方案

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摘要

With rapid development of the Internet of Things (IoT), various machine-to-machine communications technologies have emerged in recent years to provide ubiquitous wireless connections for a massive number of IoT devices. This poses significant challenges to network control and management of large-scale IoT networks. Software-defined networking (SDN) is considered a promising technology to streamline network management due to dynamic reconfigurable network elements. Thus, the integration of SDN and IoT provides a potentially feasible solution to strengthening management and control capabilities of the IoT network. Benefit from the SDN technology, resource utilization in the IoT network can be further enhanced. In this paper, we first propose a software-defined network architecture for IoT. Then, the resource allocation problem in the proposed SDN-based IoT network is investigated. The optimal problem of maximizing the expected average rewards of the network is formulated as a semi-Markov decision process (SMDP). The optimal solution is obtained through solving the SMDP problem using a relative value iteration algorithm. Simulation results demonstrate that the proposed resource allocation scheme is able to improve the system rewards compared with other comparative resource allocation schemes.
机译:随着物联网(IoT)的快速发展,近年来出现了各种机器对机器通信技术,以为大量的IoT设备提供无所不在的无线连接。这对大规模物联网网络的网络控制和管理提出了重大挑战。由于动态可重新配置的网络元素,软件定义网络(SDN)被认为是简化网络管理的有前途的技术。因此,SDN和IoT的集成为增强IoT网络的管理和控制能力提供了潜在可行的解决方案。受益于SDN技术,可以进一步提高IoT网络中的资源利用率。在本文中,我们首先提出了一种用于物联网的软件定义网络架构。然后,研究了所提出的基于SDN的物联网网络中的资源分配问题。最大化网络的预期平均回报的最佳问题被表述为半马尔可夫决策过程(SMDP)。通过使用相对值迭代算法解决SMDP问题,可以获得最优解。仿真结果表明,与其他比较资源分配方案相比,本文提出的资源分配方案能够提高系统的报酬。

著录项

  • 来源
    《IEEE sensors journal》 |2016年第20期|7304-7314|共11页
  • 作者单位

    Intelligent Computing and Communication Laboratory, Wireless Signal Processing and Networks Laboratory, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China;

    Intelligent Computing and Communication Laboratory, Wireless Signal Processing and Networks Laboratory, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China;

    Intelligent Computing and Communication Laboratory, Wireless Signal Processing and Networks Laboratory, Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China;

    College of Science and Engineering, James Cook University, Cairns, QLD, Australia;

    Software Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;

    Information Systems Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Internet of things; Resource management; Wireless sensor networks; Wireless communication; Network architecture; Signal to noise ratio; Sensors;

    机译:物联网;资源管理;无线传感器网络;无线通信;网络体系结构;信噪比;传感器;

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