research-article

A Local-Ratio-Based Power Control Approach for Capacitated Access Points in Mobile Edge Computing

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Xuejie ZhangAuthors Info & Claims

HP3C '22: Proceedings of the 6th International Conference on High Performance Compilation, Computing and Communications

Pages 175 - 182

https://doi.org/10.1145/3546000.3546027

Published: 19 August 2022 Publication History

Abstract

Terminal devices (TDs) connect to networks through access points (APs) integrated into the edge server. This provides a prerequisite for TDs to upload tasks to cloud data centers or offload them to edge servers for execution. In this process, signal coverage, data transmission, and task execution consume energy, and the energy consumption of signal coverage increases sharply as the radius increases. Lower power leads to less energy consumption in a given time segment. Thus, power control for APs is essential for reducing energy consumption. Our objective is to determine the power assignment for each AP with same capacity constraints such that all TDs are covered, and the total power is minimized. We define this problem as a minimum power capacitated cover (MPCC) problem and present a minimum local ratio (MLR) power control approach for this problem to obtain accurate results in polynomial time. Power assignments are chosen in a sequence of rounds. In each round, we choose the power assignment that minimizes the ratio of its power to the number of currently uncovered TDs it contains. In the event of a tie, we pick an arbitrary power assignment that achieves the minimum ratio. We continue choosing power assignments until all TDs are covered. Finally, various experiments verify that this method can outperform another greedy-based way.

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Cited By

Xu MLi WZhang XSu Q(2024)A discrete dwarf mongoose optimization algorithm to solve task assignment problems on smart farmsCluster Computing10.1007/s10586-024-04271-327:5(6185-6204)Online publication date: 24-Feb-2024
https://doi.org/10.1007/s10586-024-04271-3
Cao M(2023)An Approximation Algorithm for Stochastic Power Cover ProblemTheoretical Computer Science10.1007/978-981-99-7743-7_6(96-106)Online publication date: 26-Nov-2023
https://doi.org/10.1007/978-981-99-7743-7_6
Zhang QLi WSu QZhang X(2022)A Primal–Dual-Based Power Control Approach for Capacitated Edge ServersSensors10.3390/s2219758222:19(7582)Online publication date: 6-Oct-2022
https://doi.org/10.3390/s22197582
Show More Cited By

Index Terms

A Local-Ratio-Based Power Control Approach for Capacitated Access Points in Mobile Edge Computing
1. Networks
  1. Network types
    1. Wireless access networks
2. Theory of computation
  1. Design and analysis of algorithms

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Abstract
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HP3C '22: Proceedings of the 6th International Conference on High Performance Compilation, Computing and Communications

June 2022

221 pages

ISBN:9781450396295

DOI:10.1145/3546000

Copyright © 2022 ACM.

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Publication History

Published: 19 August 2022

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the National Natural Science Foundation of China
the 13th Postgraduate Innovation Project of Yunnan University

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HP3C'22

HP3C'22: 2022 6th International Conference on High Performance Compilation, Computing and Communications

June 23 - 25, 2022

Jilin, China

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Cited By

Xu MLi WZhang XSu Q(2024)A discrete dwarf mongoose optimization algorithm to solve task assignment problems on smart farmsCluster Computing10.1007/s10586-024-04271-327:5(6185-6204)Online publication date: 24-Feb-2024
https://doi.org/10.1007/s10586-024-04271-3
Cao M(2023)An Approximation Algorithm for Stochastic Power Cover ProblemTheoretical Computer Science10.1007/978-981-99-7743-7_6(96-106)Online publication date: 26-Nov-2023
https://doi.org/10.1007/978-981-99-7743-7_6
Zhang QLi WSu QZhang X(2022)A Primal–Dual-Based Power Control Approach for Capacitated Edge ServersSensors10.3390/s2219758222:19(7582)Online publication date: 6-Oct-2022
https://doi.org/10.3390/s22197582
Dai H(2022)An Improved Approximation Algorithm for the Minimum Power Cover Problem with Submodular PenaltyComputation10.3390/computation1010018910:10(189)Online publication date: 19-Oct-2022
https://doi.org/10.3390/computation10100189
Xu MLi WZhang X(2022)Using a Compositional Function Hybridization of GCDPSO and GA to Solve Task Allocation Problems in Smart Farms2022 5th International Conference on Computing and Big Data (ICCBD)10.1109/ICCBD56965.2022.10080815(123-130)Online publication date: 16-Dec-2022
https://doi.org/10.1109/ICCBD56965.2022.10080815
Li HLi WZhang X(2022)A Genetic Algorithm for Task Offloading problem in Vehicular Edge Computing2022 China Automation Congress (CAC)10.1109/CAC57257.2022.10054675(6242-6247)Online publication date: 25-Nov-2022
https://doi.org/10.1109/CAC57257.2022.10054675
Lan H(2022)A 1/2 Approximation Algorithm for Energy-Constrained Geometric Coverage ProblemTheoretical Computer Science10.1007/978-981-19-8152-4_7(105-114)Online publication date: 10-Dec-2022
https://doi.org/10.1007/978-981-19-8152-4_7

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