Computer Science ›› 2018, Vol. 45 ›› Issue (4): 137-142.doi: 10.11896/j.issn.1002-137X.2018.04.022

Previous Articles     Next Articles

Fog Computing Task Scheduling Strategy Based on Improved Genetic Algorithm

HAN Kui-kui, XIE Zai-peng and LV Xin   

  • Online:2018-04-15 Published:2018-05-11

Abstract: Task scheduling and assignment has always been a key issue in the development of cloud computing.However,with the explosive growth of internet connection devices,cloud computing has been unable to meet some requirements such as health monitoring,emergency response and so on,which all require low latency.Thus fog computing appears.Fog computing extends the cloud services to the edge of network.Under the fog computing architecture,task scheduling and assignment is still a relatively new research hotspot.This paper introduced an improved genetic algorithm(IGA).The algorithm introduces the fitness judgment into the parental mutation operation which overcomes the blindness of simple genetic algorithm(SGA) in mutation operation.The response time restriction in the service level objective(SLO) is considered when the IGA is used to schedule tasks(FOG-SLO-IGA).The experimental results show that when scheduling user tasks are under the fog computing architecture,FOG-SLO-IGA is superior to the scheduling which uses IGA under cloud computing architecture in latency,SLO violation rate and service provider’s cost.Futhermore,IGA algorithm is superior to the traditional SGA algorithm and the round-robin scheduling algorithm(RRSA) in the execution of the tasks under the fog computing architecture.

Key words: Task scheduling,Cloud computing,Fog computing,Service level objective,Genetic algorithm

[1] LI Q,ZHENG X.A Review of the Present Situation aboutCloud Computing[J].Computer Science,2011,8(4):32-37.(in Chinese) 李乔,郑啸.云计算研究现状综述[J].计算机科学,2011,8(4):32-37.
[2] LAI C F,WANG H,CHAO H C,et al.A Network and Device Aware QoS Approach for Cloud-Based Mobile Streaming[J].IEEE Transactions on Multimedia,2013,5(4):747-757.
[3] RIMAL B P,CHOI E,LUMB I.A Taxonomy and Survey of Cloud Computing Systems[C]∥International Joint Conference on Inc,Ims and IDC.IEEE,2009:44-51.
[4] MarketWatch:‘Cisco delivers vision of fog computing to acce-lerate value from billions of connected devices’.http://www.the-iet.org/resources/journals/research/index.cfm.
[5] BONOMI F,MILITO R,ZHU J,et al.Fog computing and itsrole in the internet of things[C]∥Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing.ACM,2012:13-16.
[6] LUAN T H,GAO L,LI Z,et al.Fog computing:Focusing on mobile users at the edge[J].arXiv preprint arXiv:1502.01815,2015.
[7] AAZAM M,HUH E N.Fog computing and smart gatewaybased communication for cloud of things[C]∥2014 InternationalConference on Future Internet of Things and Cloud(FiCloud).IEEE,2014:464-470.
[8] AAZAM M,HUH E N.Fog Computing:The Cloud-IoT/IoE Middleware Paradigm[J].IEEE Potentials,2016,5(3):40-44.
[9] 北京物联远信息技术有限公司.一种面向物联网的雾计算架构:中国,201511019375.3[P/OL].(2016-05-25).http://www.soopat.com/patent/201511019375.
[10] GUPTA H,DASTJERDI A V,GHOSH S K,et al.i-FogSim:A Toolkit for Modeling and Simulation of Resource Management Techniques in Internet of Things,Edge and Fog Computing Environments[J].arXiv preprint arXiv:1606.02007,6.
[11] ZENG D,GU L,GUO S,et al.Joint Optimization of TaskScheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System[J].IEEE Transactions on Computers,2016,5(12):3702-3712.
[12] HE X L,REN Z Y,SHI C H,et al.Cloud and Fog network for Medical Big Data and its Distributed Computing Scheme[J].Journal of Xi’an Jiaotong University,2016,0(10):71-77.(in Chinese) 何秀丽,任智源,史晨华,等.面向医疗大数据的云雾网络及其分布式计算方案[J].西安交通大学学报,2016,50(10):71-77.
[13] CHENG D M,LI Z.Hospital Information Service System Based on Fog Computing[J].Computer Science,2015,2(7):170-190.(in Chinese) 程冬梅,李志.基于雾计算的医院信息服务系统[J].计算机科学,2015,42(7):170-190.
[14] SARKAR S,MISRA S.Theoretical modelling of fog computing:a green computing paradigm to support IoT applications[J].IET Journals,2016,5(2):23-29.
[15] WU L.SLA-based resource provisioning for management ofCloud-based Software-as-a-Service applications[D].The University of Melbourne,2014.
[16] LI J F,PENG J.Task Scheduling Algorithm Based on Improved Genetic Algorithm in Cloud Computing Environment[J].Journal of Computer Application,2011,1(1):184-186.(in Chinese) 李剑锋,彭舰.云环境下基于改进遗传算法的任务调度算法[J].计算机应用,2011,1(1):184-186.
[17] CHIANG M,ZHANG T.Fog and IoT:An Overvi-ew of Research Opportunities[J].IEEE Internet of Things Journal,2016,3(6):854-864.
[18] 周明,孙树栋.遗传算法原理及应用[M].北京:国防工业出版社,1996:18-32.
[19] HE X L.A Generalized Genetic Algorithm for Task Scheduling[J].Computer Engineering,2010,6(17):184-186.(in Chinese) 贺晓丽.一种用于任务调度的广义遗传算法[J].计算机工程,2010,36(17):184-186.
[20] CALHEIROS R N,RANJAN R,BELOGLAZOV A,et al.CloudSim:a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms[J].Software Practice & Experience,2011,41(1):23-50.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!