Master data

Title: CoPaM: Cost-aware VM Placement and Migration for Mobile services in Multi-Cloudlet environment: An SDN-based approach
Subtitle:
Abstract:

Edge Cloud Computing (ECC) is a new approach for bringing Mobile Cloud Computing (MCC) services closer to mobile users in order to facilitate the complicated application execution on resource-constrained mobile devices. The main objective of the ECC solution with the cloudlet approach is mitigating the latency and augmenting the available bandwidth. This is basically done by deploying servers (a.k.a. “Cloudlets”) close to the user’s device on the edge of the cellular network. When considering the users’ mobility along with the limited resource of the cloudlets serving them, the user-cloudlet communication may need to go through multiple hops, which may seriously affect the communication delay between them and the quality of services (QoS). To reduce as much as possible the negative effects of such a QoS degradation, service execution must be dynamically migrated to a better placement. This study proposes a novel Cost-aware Virtual Machine (VM) placement and migration (CoPaM) framework for mobile services in a network of cloudlets. A Mixed Integer Linear Programming (MILP) model is proposed to select the least cost cloudlets for serving mobile users to a given trajectory in advance based on path prediction methods. Since the proposed model is NP-hard, it is not applicable within large-scale environments with a centralized approach and the use of Software Defined Networking (SDN) technology. Therefore, a heuristic algorithm is presented. Experiments are conducted by emulating the proposed framework in Mininet-WiFi with the Floodlight usage as the SDN controller. The simulation results show the superiority of the performance of the proposed architecture in terms of the service rate and the costs imposed on the operator in comparison to existing approaches.

Keywords: SDN, Mobile Edge Computing (MEC), Cloudlet, Virtual Machine (VM), Placement and migration
Publication type: Article in journal (Authorship)
Publication date: 01.07.2022 (Online)
Published by: Computer Communications
Computer Communications
to publication
 ( Elsevier B.V.; )
Title of the series: -
Volume number: 191
Issue: -
First publication: Yes
Version: -
Page: pp. 257 - 273

Versionen

Keine Version vorhanden
Publication date: 07.2022
ISBN: -
ISSN: 0140-3664
Homepage: https://www.sciencedirect.com/science/article/pii/S0140366422001578?via%3Dihub
Publication date: 01.07.2022
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1016/j.comcom.2022.05.005
Homepage: https://www.sciencedirect.com/science/article/pii/S0140366422001578?via%3Dihub
Open access
  • Available online (not open access)

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Citation index
  • Science Citation Index Expanded (SCI Expanded)
Information about the citation index: Master Journal List
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

Organisation Address
Ferdowsi University of Mashhad (FUM)
Azadi Square
Mashhad, Razavi Khorasan Province
Iran, Islamic Rep. of
Azadi Square
IR  Mashhad, Razavi Khorasan Province

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