Mobile Application Placement in Multi-access Edge Computing Environments

Modern mobile applications require both a sufficient amount of infrastructure resources as well as a certain network Quality of Service (QoS) in order to process and respond to user requests efficiently and thus ensure the correct behavior of the applications. Multi-access Edge Computing (MEC) combined with new mobile communications technologies, such as 5G and 6G, provides the technological basis for fulfilling these requirements. In this context, a key challenge is the deployment of the microservices of the mobile applications within the environment. Since the microservices of an application interact with each other via the network, they must be placed within the MEC environment, taking into account the available resources on the MEC hosts, the network QoS and the location of the corresponding user device. In this paper, we describe an approach for the placement of mobile applications in MEC environments based on Reinforcement Learning, considering the architecture and functionalities of the MEC standard, with the aim of proposing an efficient placement methodology for future mobile networks. -MEC, Edge, Cloud, Application, Placement

Authors

Institutions

Publication Details

Published
2024-09-02
DOI
https://doi.org/10.1109/fmec62297.2024.10710198
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mobile Application Placement in Multi-access Edge Computing Environments

Marc Hesenius, Volker Gruhn, David Schuster
Cloud Computing and Resource Management
article

Mobile Application Placement in Multi-access Edge Computing Environments

Marc Hesenius, Volker Gruhn, David Schuster
article en

Abstract

Modern mobile applications require both a sufficient amount of infrastructure resources as well as a certain network Quality of Service (QoS) in order to process and respond to user requests efficiently and thus ensure the correct behavior of the applications. Multi-access Edge Computing (MEC) combined with new mobile communications technologies, such as 5G and 6G, provides the technological basis for fulfilling these requirements. In this context, a key challenge is the deployment of the microservices of the mobile applications within the environment. Since the microservices of an application interact with each other via the network, they must be placed within the MEC environment, taking into account the available resources on the MEC hosts, the network QoS and the location of the corresponding user device. In this paper, we describe an approach for the placement of mobile applications in MEC environments based on Reinforcement Learning, considering the architecture and functionalities of the MEC standard, with the aim of proposing an efficient placement methodology for future mobile networks. -MEC, Edge, Cloud, Application, Placement

Software (Germany) (DE), University of Duisburg-Essen (DE)
Openalex Percentile: Top 72%
Cloud Computing and Resource Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.