Energy-Efficient Resource Allocation for Industrial Cyber-Physical IoT Systems in 5G Era

Li, Song and Ni, Qiang and Sun, Yanjing and Min, Geyong and Al-rubaye, Saba (2018) Energy-Efficient Resource Allocation for Industrial Cyber-Physical IoT Systems in 5G Era. IEEE Transactions on Industrial Informatics, 14 (6). pp. 2618-2628. ISSN 1551-3203

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Abstract

Cyber-physical Internet of things system (CPIoTS), as an evolution of Internet of things (IoT), plays a significant role in industrial area to support the interoperability and interaction of various machines (e.g. sensors, actuators, and controllers) by providing seamless connectivity with low bandwidth requirement. The fifth generation (5G) is a key enabling technology to revolutionize the future of industrial CPIoTS. In this paper, a communication framework based on 5G is presented to support the deployment of CPIoTS with a central controller. Based on this framework, multiple sensors and actuators can exchange information with the central controller in full-duplex mode. To accommodate the signal data in the available channel band, a resource allocation problem is formulated as a mixed integer non-convex programming problem, aiming to maximize the sum energy efficiency of CPIoTS. By introducing the transformation, we decompose the resource allocation problem into power allocation and channel allocation. Moreover, we consider an energy-efficient power allocation algorithm based on game theory and Dinkelbach's algorithm. Finally, to reduce the computational complexity, the channel allocation is modeled as a 3-dimensional matching problem, and solved by iterative Hungarian method with virtual devices (IHM-VD). A comparison is completed with well-known existing algorithms to demonstrate the performance of the proposed one. Simulation results confirm the efficiency of the proposed model, which significantly outperforms other benchmark algorithms in terms of meeting the energy efficiency and the QoS requirements.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Transactions on Industrial Informatics
Additional Information:
©2018 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2200/2208
Subjects:
ID Code:
124452
Deposited By:
Deposited On:
09 Apr 2018 08:50
Refereed?:
Yes
Published?:
Published
Last Modified:
27 Sep 2020 04:27