Solving the Task Starvation and Resources Problem Using Optimized SMPIA in Cloud

In this study,a new feature is added to the smart message passing interface(SMPI)approach(SMPIA)based on the prioritization method,which cancompletely eliminate the task starvation and lack of sufficient resources problemsthrough prioritizing the tasks.The proposed approach is based on prioritizing thetasks and the urgency of implementation.Tasks are prioritized based on executiontime,workload,the task with a more sensitive priority is executed earlier by thefree source.The idea of demand-bound functions(DBFs)was extended to theSMPIA setting based on partitions and caps.For each task,two DBFs are constructed,DBFLO and DBFHI,for the LO and HI criticality modes,respectively.The simulation results returned by MATLAB showed that with the optimizedSMPIA(O-SMPIA),the parameters of maximum service execution time,response time,delay time,and throughput improved in this work.In addition,the results confirmed that the reduction of execution time,completion time,andresource consumption time did not affect the response time and throughput ofworkflow tasks and did not cause inefficient use of resources in virtual machines(VMs)and data centers(DCs).The evaluation of performance metrics showedthat the delay,response time of the Greedy algorithm was less than that ofMax-Min and Min-Min.At the same time,the execution time of Max-Min wasless than the others and the throughput of the Greedy was longer.The effectand throughput of O-SMPIA became more obvious as change to the job countand the number of cloud workloads increased.It is also worth mentioning thatone of the main advantages of the O-SMPIA to other methods is the efficientuse of time to execute all the defined tasks by CPU.