Abstract
The energy consumption of underlying cloud hardware has dramatically increased. The cloud service providers need to adopt some cost-effective and energy-aware job scheduler without compromising the quality of service QoS specified in the service level agreement SLA. Based on a rigorous mathematical model, we formulate an energy efficient problem to improve the resource utilisation for high system throughput. A multiple-procedure heuristic workflow scheduling and consolidation strategy is proposed with objectives to maximise the resource utilisation and minimise the power. Several techniques have been utilised including dynamic voltage and frequency scaling DVFS with task module migration for workload balance and task consolidation for virtual machine VM overhead reduction. The simulation results illustrate that our approach consistently achieves a lower power consumption and higher resource utilisation rate within the execution time bound compared with other similar scheduling algorithms as well as our previous algorithm without the task migration based on VM threshold.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Computational Science and Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
