Next Article in Journal
The Use of Neural Networks in Combination with Evolutionary Algorithms to Optimise the Copper Flotation Enrichment Process
Next Article in Special Issue
A Cloud-Based UTOPIA Smart Video Surveillance System for Smart Cities
Previous Article in Journal
Optimization of a T-Shaped MIMO Antenna for Reduction of EMI
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing

Department of Computer Science and Engineering, Kyung Hee University, Global Campus, Yongin-si 17104, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(9), 3115; https://doi.org/10.3390/app10093115
Submission received: 19 March 2020 / Revised: 23 April 2020 / Accepted: 25 April 2020 / Published: 29 April 2020
(This article belongs to the Special Issue Cloud Computing Beyond)

Abstract

Accelerating the development of the 5G network and Internet of Things (IoT) application, multi-access edge computing (MEC) in a small-cell network (SCN) is designed to provide computation-intensive and latency-sensitive applications through task offloading. However, without collaboration, the resources of a single MEC server are wasted or sometimes overloaded for different service requests and applications; therefore, it increases the user’s task failure rate and task duration. Meanwhile, the distinct MEC server has faced some challenges to determine where the offloaded task will be processed because the system can hardly predict the demand of end-users in advance. As a result, the quality-of-service (QoS) will be deteriorated because of service interruptions, long execution, and waiting time. To improve the QoS, we propose a novel Fuzzy logic-based collaborative task offloading (FCTO) scheme in MEC-enabled densely deployed small-cell networks. In FCTO, the delay sensitivity of the QoS is considered as the Fuzzy input parameter to make a decision where to offload the task is beneficial. The key is to share computation resources with each other and among MEC servers by using fuzzy-logic approach to select a target MEC server for task offloading. As a result, it can accommodate more computation workload in the MEC system and reduce reliance on the remote cloud. The simulation result of the proposed scheme show that our proposed system provides the best performances in all scenarios with different criteria compared with other baseline algorithms in terms of the average task failure rate, task completion time, and server utilization.
Keywords: multi-access edge computing; fuzzy logic; collaborative task offloading; small-cell network multi-access edge computing; fuzzy logic; collaborative task offloading; small-cell network

Share and Cite

MDPI and ACS Style

Hossain, M.D.; Sultana, T.; Nguyen, V.; Rahman, W.u.; Nguyen, T.D.T.; Huynh, L.N.T.; Huh, E.-N. Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing. Appl. Sci. 2020, 10, 3115. https://doi.org/10.3390/app10093115

AMA Style

Hossain MD, Sultana T, Nguyen V, Rahman Wu, Nguyen TDT, Huynh LNT, Huh E-N. Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing. Applied Sciences. 2020; 10(9):3115. https://doi.org/10.3390/app10093115

Chicago/Turabian Style

Hossain, Md Delowar, Tangina Sultana, VanDung Nguyen, Waqas ur Rahman, Tri D. T. Nguyen, Luan N. T. Huynh, and Eui-Nam Huh. 2020. "Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing" Applied Sciences 10, no. 9: 3115. https://doi.org/10.3390/app10093115

APA Style

Hossain, M. D., Sultana, T., Nguyen, V., Rahman, W. u., Nguyen, T. D. T., Huynh, L. N. T., & Huh, E.-N. (2020). Fuzzy Based Collaborative Task Offloading Scheme in the Densely Deployed Small-Cell Networks with Multi-Access Edge Computing. Applied Sciences, 10(9), 3115. https://doi.org/10.3390/app10093115

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop