Creating and sharing knowledge for telecommunications

Exploiting Virtual Machine Commonality for Improved Resource Allocation in Edge Networks

Abdah, H. ; Barraca, JPB ; Aguiar, R.

Journal of Sensor and Actuator Networks Vol. 9, Nº 4, pp. 58 - 58, December, 2020.

ISSN (print): 2224-2708
ISSN (online):

Journal Impact Factor: (in )

Digital Object Identifier: 10.3390/jsan9040058

Download Full text PDF ( 614 KBs)

Open AccessArticle
Exploiting Virtual Machine Commonality for Improved Resource Allocation in Edge Networks
by Hadeel Abdah
1,2,* [OrcID] , João Paulo Barraca
2 [OrcID] and Rui L. Aguiar
2 [OrcID]
Instituto de Telecomunicações, 3810-193 Aveiro, Portugal
Departamento de Eletrónica, Telecomunicações e Informática, Universidade de Aveiro, 3810-193 Aveiro, Portugal
Author to whom correspondence should be addressed.
J. Sens. Actuator Netw. 2020, 9(4), 58;
Received: 29 October 2020 / Revised: 4 December 2020 / Accepted: 7 December 2020 / Published: 13 December 2020
(This article belongs to the Special Issue From Edge Computing to Distributed Cloud—A Novel Paradigm toward 6G Networks)
Download PDF Browse Figures
Citation Export
5G systems are putting increasing pressure on Telecom operators to enhance users’ experience, leading to the development of more techniques with the aim of improving service quality. However, it is essential to take into consideration not only users’ demands but also service providers’ interests. In this work, we explore policies that satisfy both views. We first formulate a mathematical model to compute End-to-End (E2E) delay experienced by mobile users in Multi-access Edge Computing (MEC) environments. Then, dynamic Virtual Machine (VM) allocation policies are presented, with the objective of satisfying mobile users Quality of Service (QoS) requirements, while optimally using the cloud resources by exploiting VM resource reuse.Thus, maximizing the service providers’ profit should be ensured while providing the service required by users. We further demonstrate the benefits of these policies in comparison with previous works.