Research On Cloud Task Scheduling Strategy Based On Improved Symbiotic Organisms Search Algorithm

Cloud computing is the focus of information technology development and service model innovation,providing basic support for the development of big data,Internet of things,artificial intelligence and other emerging fields.However,it is an urgent problem to be solved during the development of cloud computing that the cloud platform must handle a large number of task requests,how to properly schedule tasks,and meet the task requirements.In this paper,the symbiotic organisms search algorithm is improved and applied to the field of cloud computing task scheduling,and some defects existing in the existing scheduling algorithm are improved,the main contents are as follows:(1)In order to make the performance of the SOS better when dealing with task scheduling problems,two improved algorithms are proposed: 1)The potential solution operation and the improved rotation learning operation will be introduced into the SOS algorithm,and the improvement of independent task scheduling will be proposed algorithm(GISOS);2)By designing the population difference degree calculation method,the algorithm is guided by feedback into tendency learning,cross learning and mutation operations,and an improved algorithm for workflow task scheduling(RQSOS)is proposed.The comparison of numerical tests shows that the performance of the improved algorithm is improved.(2)For the independent task scheduling problem in the cloud environment,aiming at improving the performance of cloud computing systems and user satisfaction,by rationalizing the coding of GISOS algorithms,clustering resources and tasks,and improving the driving model,etc.A cloud computing task scheduling strategy(FIDSOS)based on clustering and improved SOS algorithm is proposed,and the effectiveness of the algorithm is proved by comparative experiments.(3)For the workflow task scheduling problem in cloud environment,the scheduling algorithm is designed with the goal of reducing the completion time and reducing the resource usage cost.First of all,in order to make RQSOS algorithm suitable for discrete problems,improve its coding,assign priorities to workflow tasks,and redesign the fitness function,a workflow task scheduling problem suitable for cloud environment is presented.The experimental results show that the algorithm can reduce the completion time and the cost of use.In summary,this paper improves the ability of the SOS algorithm to handle complex problems.By analyzing the scheduling problems of different types of tasks and constructing a suitable driving model,the improved algorithm is applied to the task scheduling problem,and simulation experiments are conducted.The experimental results show that the proposed algorithm is effective.