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Power-constrained edge computing with maximum processing capacity for IoT networks
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Qin, Min, Chen, Li, Zhao, Nan, Chen, Yunfei, Yu, F. Richard and Wei, Guo (2019) Power-constrained edge computing with maximum processing capacity for IoT networks. IEEE Internet of Things Journal, 6 (3). pp. 4330-4343. doi:10.1109/JIOT.2018.2875218
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Official URL: https://doi.org/10.1109/JIOT.2018.2875218
Abstract
Mobile edge computing (MEC) plays an important role in next-generation networks. It aims to enhance processing capacity and offer low-latency computing services for Internet of Things (IoT). In this paper, we investigate a resource allocation policy to maximize the available processing capacity (APC) for MEC IoT networks with constrained power and unpredictable tasks. First, the APC which describes the computing ability and speed of a served IoT device is defined. Then its expression is derived by analyzing the relationship between task partitioning and resource allocation. Based on this expression, the power allocation solution for the single-user MEC system with a single subcarrier is studied and the factors that affect the APC improvement are considered. For the multiuser MEC system, an optimization problem of APC with a general utility function is formulated and several fundamental criteria for resource allocation are derived. By leveraging these criteria, a binarysearch water-filling algorithm is proposed to solve the power allocation between local CPU and multiple subcarriers, and a suboptimal algorithm is proposed to assign the subcarriers among users. Finally, the validity of the proposed algorithms is verified by Monte Carlo simulation.
| Item Type: | Journal Article | |||||||||||||||||||||
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| Subjects: | Q Science > QA Mathematics > QA75 (Please use QA76 Electronic Computers. Computer Science) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science > Engineering | |||||||||||||||||||||
| Library of Congress Subject Headings (LCSH): | Internet of things, Mobile computing, Computer capacity | |||||||||||||||||||||
| Journal or Publication Title: | IEEE Internet of Things Journal | |||||||||||||||||||||
| Publisher: | IEEE | |||||||||||||||||||||
| ISSN: | 2327-4662 | |||||||||||||||||||||
| Official Date: | June 2019 | |||||||||||||||||||||
| Dates: |
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| Volume: | 6 | |||||||||||||||||||||
| Number: | 3 | |||||||||||||||||||||
| Page Range: | pp. 4330-4343 | |||||||||||||||||||||
| DOI: | 10.1109/JIOT.2018.2875218 | |||||||||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||||||||
| Publication Status: | Published | |||||||||||||||||||||
| Publisher Statement: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||||||||
| RIOXX Funder/Project Grant: |
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