A Budget-constrained Time and Reliability Optimization BAT Algorithm for Scheduling Workflow Applications in Clouds

AbstractEffective scheduling is one of the key concerns while executing workflows in the cloud environment. Workflow scheduling in clouds refers to the mapping of workflow tasks to the cloud resources to optimize some objective function. In this paper, we apply a recently developed meta-heuristic method called the BAT algorithm to solve the multi-objective problem of workflow scheduling in clouds that minimizes the execution time and maximizes the reliability by keeping the budget within user specified limit. Comparison of the results is made with basic, randomized, evolutionary algorithm (BREA) that uses greedy approach to allocate resources to the workflow tasks on the basis of low cost, high reliability and improved execution time machines. It is clear from the experimental results that the BAT algorithm performs better than the basic randomized evolutionary algorithm

Autonomous resource-aware scheduling of large-scale media workflows

The media processing and distribution industry generally requires considerable resources to be able to execute the various tasks and workflows that constitute their business processes. The latter processes are often tied to critical constraints such as strict deadlines. A key issue herein is how to efficiently use the available computational, storage and network resources to be able to cope with the high work load. Optimizing resource usage is not only vital to scalability, but also to the level of QoS (e.g. responsiveness or prioritization) that can be provided. We designed an autonomous platform for scheduling and workflow-to-resource assignment, taking into account the different requirements and constraints. This paper presents the workflow scheduling algorithms, which consider the state and characteristics of the resources (computational, network and storage). The performance of these algorithms is presented in detail in the context of a European media processing and distribution use-case