This manuscript proposed and explored a novel strategy for optimizing the composition of tasks from distributed workflows to achieve parallel execution, optimality toward resource utilization. The critical objective of the proposal is to optimize the task sequences from the distributed workflows initiated to execute parallel in Cloud Networks, which is unique in regard to the earlier contributions related to optimal utilization of the resources under diversified quality factors of cloud network domain, which are found in contemporary literature. The contemporary models aimed to optimize the resources utilization under 1 or two quality factors, and the sequence of tasks is not considering as the factor to optimize the resource utilization. In order to this, the Optimum Resource Utilization by ComposingDistributed Task Sequences (CDTS) from set of tasks delivered by distributed workflows is proposed. The CDTS optimizes the execution of tasks from multiple workflows initiated in parallel. A novel scale called “Task Sequence Reliability Weight” defined, which uses the order of other metrics referred as “task sequence coverage”, “dependency scope”, and roundtrip-time as input. The experiments conducted on the proposed model and other benchmark models found in contemporary literature. The results obtained from the experimental study evincing that the CDTS is significant and robust to optimize the task sequences in order to execute distribute workflows in parallel. The comparative analysis of the results obtained from CDTS and other contemporary models performed using ANOVA standards like t-test, Wilcoxon signed rank test.
Volume 11 | Issue 6