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

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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

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