Time-Varying Mobile Edge Computing for Capacity Maximization

Capacity is a fundamental metric for mobile edge computing scenarios, where the system state plays an important role. Previous studies have mostly been based on the premise that the system state is stable. In reality, the network is dynamic and the system state changes with time. In this paper, we s...

Full description

Bibliographic Details
Main Authors: Yunyun Cai, Peiyan Yuan
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9157891/
id doaj-1fc5b3cbd0f14772b7c0825df500930b
record_format Article
spelling doaj-1fc5b3cbd0f14772b7c0825df500930b2021-03-30T04:51:52ZengIEEEIEEE Access2169-35362020-01-01814283214284210.1109/ACCESS.2020.30142759157891Time-Varying Mobile Edge Computing for Capacity MaximizationYunyun Cai0https://orcid.org/0000-0001-9143-2850Peiyan Yuan1https://orcid.org/0000-0003-0023-1194School of Computer and Information Engineering, Henan Normal University, Xinxiang, ChinaSchool of Computer and Information Engineering, Henan Normal University, Xinxiang, ChinaCapacity is a fundamental metric for mobile edge computing scenarios, where the system state plays an important role. Previous studies have mostly been based on the premise that the system state is stable. In reality, the network is dynamic and the system state changes with time. In this paper, we study the capacity of a mobile edge system in which users continuously join or leave the coverage of base station. We first change the problem of maximum network capacity into a minimum transmission distance problem. We observe that both the probability of the files being requested and the distance of the files transmission are related to the degree of files, i.e., the number of users who are interested in a file and request it with a certain probability. Then, we evaluate the degree of files in a time-varying situation, and calculate the probability of the files being requested and the transmission distance according to the degree of files. Finally, we calculate the capacity of the network under time-varying conditions. In the experimental section, we analyze the degree of files, the optimal copies number, and the change in network capacity over time. In addition, we compare the capacity in our system with classic studies. The experimental results verify the superiority of the proposed method.https://ieeexplore.ieee.org/document/9157891/Mobile edge computingcapacitytime-varyingdegree of filestransmission distance
collection DOAJ
language English
format Article
sources DOAJ
author Yunyun Cai
Peiyan Yuan
spellingShingle Yunyun Cai
Peiyan Yuan
Time-Varying Mobile Edge Computing for Capacity Maximization
IEEE Access
Mobile edge computing
capacity
time-varying
degree of files
transmission distance
author_facet Yunyun Cai
Peiyan Yuan
author_sort Yunyun Cai
title Time-Varying Mobile Edge Computing for Capacity Maximization
title_short Time-Varying Mobile Edge Computing for Capacity Maximization
title_full Time-Varying Mobile Edge Computing for Capacity Maximization
title_fullStr Time-Varying Mobile Edge Computing for Capacity Maximization
title_full_unstemmed Time-Varying Mobile Edge Computing for Capacity Maximization
title_sort time-varying mobile edge computing for capacity maximization
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Capacity is a fundamental metric for mobile edge computing scenarios, where the system state plays an important role. Previous studies have mostly been based on the premise that the system state is stable. In reality, the network is dynamic and the system state changes with time. In this paper, we study the capacity of a mobile edge system in which users continuously join or leave the coverage of base station. We first change the problem of maximum network capacity into a minimum transmission distance problem. We observe that both the probability of the files being requested and the distance of the files transmission are related to the degree of files, i.e., the number of users who are interested in a file and request it with a certain probability. Then, we evaluate the degree of files in a time-varying situation, and calculate the probability of the files being requested and the transmission distance according to the degree of files. Finally, we calculate the capacity of the network under time-varying conditions. In the experimental section, we analyze the degree of files, the optimal copies number, and the change in network capacity over time. In addition, we compare the capacity in our system with classic studies. The experimental results verify the superiority of the proposed method.
topic Mobile edge computing
capacity
time-varying
degree of files
transmission distance
url https://ieeexplore.ieee.org/document/9157891/
work_keys_str_mv AT yunyuncai timevaryingmobileedgecomputingforcapacitymaximization
AT peiyanyuan timevaryingmobileedgecomputingforcapacitymaximization
_version_ 1724181069756891136