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Efficient microservices offloading for cost optimization in diverse MEC cloud networks.

Authors :
Mahesar, Abdul Rasheed
Li, Xiaoping
Sajnani, Dileep Kumar
Source :
Journal of Big Data; 9/4/2024, Vol. 11 Issue 1, p1-27, 27p
Publication Year :
2024

Abstract

In recent years, mobile applications have proliferated across domains such as E-banking, Augmented Reality, E-Transportation, and E-Healthcare. These applications are often built using microservices, an architectural style where the application is composed of independently deployable services focusing on specific functionalities. Mobile devices cannot process these microservices locally, so traditionally, cloud-based frameworks using cost-efficient Virtual Machines (VMs) and edge servers have been used to offload these tasks. However, cloud frameworks suffer from extended boot times and high transmission overhead, while edge servers have limited computational resources. To overcome these challenges, this study introduces a Microservices Container-Based Mobile Edge Cloud Computing (MCBMEC) environment and proposes an innovative framework, Optimization Task Scheduling and Computational Offloading with Cost Awareness (OTSCOCA). This framework addresses Resource Matching, Task Sequencing, and Task Scheduling to enhance server utilization, reduce service latency, and improve service bootup times. Empirical results validate the efficacy of MCBMEC and OTSCOCA, demonstrating significant improvements in server efficiency, reduced service latency, faster service bootup times, and notable cost savings. These outcomes underscore the pivotal role of these methodologies in advancing mobile edge computing applications amidst the challenges of edge server limitations and traditional cloud-based approaches. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21961115
Volume :
11
Issue :
1
Database :
Complementary Index
Journal :
Journal of Big Data
Publication Type :
Academic Journal
Accession number :
179438709
Full Text :
https://doi.org/10.1186/s40537-024-00975-w