Decentralised workflow scheduling in volunteer computing systems

Volunteer computing systems exploiting large amounts of geographically dispersed resources on the Internet for solving complex scientific problems. However, scheduling scientific workflows in a fully decentralised way and low overhead is a challenging task in these environments. To counter this challenge, this paper presents a fully decentralised proximity-aware workflow-scheduling policy for these environments. The proposed scheduling consists of three phases. In the first phase, each workflow application is partitioned into sub-workflows in order to minimise data dependencies among them. The second phase of the workflow-scheduling algorithm finds some resources to execute each sub-workflow. These resources are selected based on Quality of Service (QoS) constraints of the workflow, load balancing and proximity of resources. Each workflow can have QoS constraints in terms of minimum CPU speed and minimum RAM or hard disk requirements. In the third phase, sub-workflows will be executed on each resource based on local scheduling algorithm to minimise the partial makespan. The proposed scheduling policy focuses on the reduction of communication overhead to improve the performance of I/O-intensive and data-intensive workflows. Simulation results show that the proposed workflow-scheduling policy improves the average response time of scientific workflows up to 53.6% under a moderate load.