Task Pattern Identification and Scheduling Using Equal Opportunity Model for Minimization of Makespan and Task Diversity in Cloud Computing

A Multi-queue Round Robin Algorithm for Task Scheduling in Enterprise Application Integration Platforms in the Cloud

“…The authors performed a systematic analysis of heuristic techniques using Principal Component Analysis (PCA) and proposed a Prediction of Tasks Computation Time (PTCT) algorithm. Gade et al [36] implemented an hierarchical clustering to identify task patterns focused on execution performance. This method was compared with K-means and FCM clustering models by using CloudSim platform.…”

“…Goal Research field Method Guo et al [9] Minimise makespan Cloud Fuzzy Rimal and Maier [23] Minimise makespan, cost, and tardiness Cloud -Zhou et al [24] Maximise completion ratio and minimise bandwidth consumption Broadcast EDS Zaourar et al [25] Minimise makespan and energy consumption Manufacturing PSO Manasrah and Ali [26] Minimise makespan, cost and balancing load Cloud GA & PSO Rodriguez and Buyya [27] Minimise makespan, cost, deadline, and VM Cloud -Anwar and Deng [28] Minimise makespan and cost Cloud BoTs & MIP Sun et al [29] Minimise makespan and resource utilisation rate E-Stream EFT & max-min fairness Ghafouri et al [30] Minimise makespan and cost Cloud back-tracking Xie et al [31] Minimise makespan and cost Cloud & Edge PSO Eldesokey et al [32] Minimise makespan, execution time and cost Cloud PSO & SSO Attiya et al [33] Minimise makespan Cloud & IoT MRFO & SSO Kumar et al [34] Minimise makespan Cloud B&B Al-Maytami et al [35] Minimise makespan and cost Cloud DAG Gade et al [36] Minimise makespan Cloud NALCA Tarafdar et al [37] Minimise makespan and energy consumption Cloud Greedy & ACO Zhang et al [38] Minimise makespan and execution time Cloud ACO Xia et al [39] Minimise makespan Cloud TOPSIS & MT Tian et al [40] Minimise which go through a segment of «tasks» uncoupled and connected by «communication channels», and then, the data is delivered to one or more data sink. Sources and sinks of data can be applications, databases, sensors, etc.…”