Authors: Daniel Carvalho; Laécio Rodrigues; Patricia Takako Endo; Sokol Kosta; Francisco Airton Silva
Addresses: Universidade Federal do Piauí, R. Cícero Duarte, No. 905 – Junco, Picos – PI, 64607-670, Brazil ' Universidade Federal do Piauí, R. Cícero Duarte, No. 905 – Junco, Picos – PI, 64607-670, Brazil ' Universidade de Pernambuco, Avenida Agamenon Magalhães, S/N – Santo Amaro, Recife – PE, 50100-010, Brazil ' Aalborg University, A.C. Meyers Vænge 15, 2450 København, Copenhagen, Denmark ' Universidade Federal do Piauí, R. Cícero Duarte, No. 905 – Junco, Picos – PI, 64607-670, Brazil
Abstract: Mobile edge computing (MEC) is a network architecture that takes advantage of cloud computing features (such as high availability and elasticity) and makes use of computational resources available at the edge of the network in order to enhance the mobile user experience by decreasing the service latency. MEC solutions need to dynamically allocate the requests as close as possible to their users. However, the request placement depends not only on the geographical location of the servers, but also on their requirements. Based on this fact, this paper proposes a stochastic Petri net (SPN) model to represent an MEC scenario and analyse its performance, focusing on the parameters that can directly impact the service mean response time (MRT) and resource utilisation level. In order to present the applicability of our work, we propose three case studies with numerical analysis using real-world values. The main objective is to provide a practical guide to help infrastructure administrators to adapt their architectures, finding a trade-off between MRT and level of resource usage.
Keywords: mobile edge computing; MEC; internet of things; IoT; stochastic models; server placement.
International Journal of Computational Science and Engineering, 2020 Vol.23 No.4, pp.352 - 366
Received: 04 Apr 2020
Accepted: 08 Jul 2020
Published online: 10 Feb 2021 *