An implementation of task processing on 4G-based mobile-edge computing systems

Document typeMaster thesis
Date2019-06
Rights accessOpen Access
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Abstract
Mobile Edge Computing (MEC) is a new technology that facilitates low-latency cloud services to mobile devices (MDs) by pushing mobile computing, storage and network control to the network edge, thereby prolonging the battery lifetime of MDs. Besides, MEC aims to reduce latency and permit delay-sensitive applications in 4G communications. There is, therefore, a push to test MEC performance on existing cellular systems. With the recently available mobile platform for academia SINET, NII can now connect MDs to ESs through 4G. This project focuses on the implementation of a physical 4G-based MEC System for task offloading, in which with the goal of achieving face detection, MD partially offload tasks to the ES under the instructions dictated by the offloading algorithms. Accordingly, the objectives of this thesis are to prove the efficiency of LTE based MEC systems in the real world focusing on its performance in terms of latency and battery consumption.
Description
Mobile Edge Computing (MEC) is a new technology that facilitates low-latency cloud services to mobile devices (MDs) by pushing mobile computing, storage and network control to the network edge (closer to MDs), thereby prolonging the battery lifetime of MDs. One of the main objectives of MEC is to reduce latency and permit delay-sensitive applications in 4G and in the future, 5G communications. To achieve this feat, MEC aims to build up a computing platform by deploying edge servers (ESs) on the network edge. There is, therefore, a push to test the MEC performance on existin
SubjectsMobile communication systems, Cloud computing, Comunicacions mòbils, Sistemes de, Computació en núvol
DegreeMÀSTER UNIVERSITARI EN ENGINYERIA DE TELECOMUNICACIÓ (Pla 2013)
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Circe Romero Thesis 2019 CODE.zip | 28,69Mb | application/zip | View/Open | |
Circe Romero TFM 2019.pdf | 2,824Mb | View/Open |