Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach

dc.contributor.author Adhikari, Mainak
dc.contributor.author Amgoth, Tarachand
dc.contributor.author Srirama, Satish Narayana
dc.date.accessioned 2022-03-27T06:03:40Z
dc.date.available 2022-03-27T06:03:40Z
dc.date.issued 2020-08-01
dc.description.abstract Cloud computing is a distributed computing paradigm, that provides infrastructure and services to the users using the pay-as-you-use billing model. With the increasing demands and diversity of the scientific workflows, the cloud providers face a fundamental issue of resource provisioning and load balancing. Although, the workflow scheduling in the cloud environment is extensively studied, however, most of the strategies ignore to consider the multiple conflicting objectives of the workflows for scheduling and resource provisioning. To address the above-mentioned issues, in the paper, we introduce a new workflow scheduling strategy using the Firefly algorithm (FA) by considering multiple conflicting objectives including workload of cloud servers, makespan, resource utilization, and reliability. The main purpose of the FA is to find a suitable cloud server for each workflow that can meet its requirements while balancing the loads and resource utilization of the cloud servers. In addition, a rule-based approach is designed to assign the tasks on the suitable VM instances for minimizing the makespan of the workflow while meeting the deadline. The proposed scheduling strategy is evaluated over Google cluster traces using various simulation runs. The control parameters of the FA are also thoroughly investigated for better performance. Through the experimental analysis, we prove that the proposed strategy performs better than the state-of-the-art-algorithms in terms of different Quality-of-Service (QoS) parameters including makespan, reliability, resource utilization and loads of the cloud servers.
dc.identifier.citation Applied Soft Computing Journal. v.93
dc.identifier.issn 15684946
dc.identifier.uri 10.1016/j.asoc.2020.106411
dc.identifier.uri https://www.sciencedirect.com/science/article/abs/pii/S1568494620303513
dc.identifier.uri https://dspace.uohyd.ac.in/handle/1/9231
dc.subject Cloud computing
dc.subject Firefly algorithm
dc.subject Multi-objective optimization
dc.subject QoS
dc.subject Resource utilization
dc.subject Workflow scheduling
dc.title Multi-objective scheduling strategy for scientific workflows in cloud environment: A Firefly-based approach
dc.type Journal. Article
dspace.entity.type
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