RECORD
Computing Resource Allocation of Mobile Edge Computing Networks Based on Potential Game Theory
Networking and Internet Architecture · Submitted 2 Jan 2019
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Compared with traditional solutions, simulation results indicate the computing resource utilization and energy efficiency of the proposed computing resource allocation solution are significantly improved.
The compiled record
The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
Open the compiled record
The abstract, sentence by sentence
Mobile edge computing (MEC) networks are one of the key technologies for ultra-reliability and low-latency communications. The computing resource allocation solution needs to be carefully designed to guarantee the computing resource efficiency of MEC networks. Based on the potential game theory, a computing resource allocation solution is proposed to reduce energy consumption and improve computing resource efficiency in MEC networks. The computing resource allocation solution includes two parts: the first part is the power control scheme based on the potential game theory and the second part is the computing resource allocation scheme based on linear programming. The power control scheme is to find a set of the transmission powers of base stations (BSs) that maximizes the potential function of MEC networks. The computing resource allocation scheme is to maximize the average computing resource allocation coefficient of the MEC networks based on the results of the power control scheme. Compared with traditional solutions, simulation results indicate the computing resource utilization and energy efficiency of the proposed computing resource allocation solution are significantly improved.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Mobile edge computing (MEC) networks are one of the key technologies for ultra-reliability and low-latency communications. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | The computing resource allocation solution needs to be carefully designed to guarantee the computing resource efficiency of MEC networks. | background 0.92 | 0.05 | 0.03 | asserted 0.98 |
| s2 | Based on the potential game theory, a computing resource allocation solution is proposed to reduce energy consumption and improve computing resource efficiency in MEC networks. | contribution 0.97 | 0.91 | 0.25 | asserted 0.99 |
| s3 | The computing resource allocation solution includes two parts: the first part is the power control scheme based on the potential game theory and the second part is the computing resource allocation scheme based on linear programming. | method 0.96 | 0.81 | 0.04 | asserted 1.00 |
| s4 | The power control scheme is to find a set of the transmission powers of base stations (BSs) that maximizes the potential function of MEC networks. | method 0.99 | 0.65 | 0.03 | asserted 1.00 |
| s5 | The computing resource allocation scheme is to maximize the average computing resource allocation coefficient of the MEC networks based on the results of the power control scheme. | method 0.99 | 0.74 | 0.06 | asserted 0.99 |
| s6 | Compared with traditional solutions, simulation results indicate the computing resource utilization and energy efficiency of the proposed computing resource allocation solution are significantly improved. | result 0.99 | 0.94 | 0.90 | hedged possibility 0.77 |
What was examined, and what was not
- arXiv listing abstract v1
- full text
- figures and tables
- references and citing sentences
- relations to other papers
- P abstract
- S sections
- T body sentences
- C citations
- R cross-paper relations
The paper
Original abstract
Mobile edge computing (MEC) networks are one of the key technologies for ultra-reliability and low-latency communications. The computing resource allocation solution needs to be carefully designed to guarantee the computing resource efficiency of MEC networks. Based on the potential game theory, a computing resource allocation solution is proposed to reduce energy consumption and improve computing resource efficiency in MEC networks. The computing resource allocation solution includes two parts: the first part is the power control scheme based on the potential game theory and the second part is the computing resource allocation scheme based on linear programming. The power control scheme is to find a set of the transmission powers of base stations (BSs) that maximizes the potential function of MEC networks. The computing resource allocation scheme is to maximize the average computing resource allocation coefficient of the MEC networks based on the results of the power control scheme. Compared with traditional solutions, simulation results indicate the computing resource utilization and energy efficiency of the proposed computing resource allocation solution are significantly improved.
Human review
Discussion
Know something about this paper? Leave a comment, or highlight any passage above to comment on it.