The week's pick
Random Articles
Reseach Article
Power Aware Task Scheduling in Compute Cloud
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 180 - Number 24 |
| Year of Publication: 2018 |
| Authors: Biral Modi, Bela Shrimali, Hiren B. Patel |
10.5120/ijca2018916571
|
Biral Modi, Bela Shrimali, Hiren B. Patel . Power Aware Task Scheduling in Compute Cloud. International Journal of Computer Applications. 180, 24 ( Mar 2018), 22-28. DOI=10.5120/ijca2018916571
Abstract
Cloud computing has become an attractive computing paradigm in recent years to offer on demand computing resources for users worldwide. Computing resources are delivered in the form of virtual machines. In such a scenario, task scheduling algorithms play an important role to schedule the tasks effectively to achieve reduction in power consumption and makespan with improvement in resource utilization. Many task scheduling algorithms are introduced to improve energy efficiency of data center. In our work, we have proposed and discussed a power aware dependent task scheduling (PADTS) algorithm and compare it with existing ones.
References
- Ismail, L. and Fardoun, A.A., 2017, April. Towards energy- aware task scheduling (EATS) framework for divisible-load applications in Cloud computing infrastructure. In Systems Conference (SysCon), 2017 Annual IEEE International (pp. 1-6). IEEE.
- Beloglazov, A., Abawajy, J. and Buyya, R., 2012. Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computing. Future generation computer systems, 28(5), pp.755-768.
- Rimal, B.P. and Maier, M., 2017. Workflow scheduling in multi-tenant Cloud computing environments. IEEE Transactions on Parallel and Distributed Systems, 28(1), pp.290-304.
- Ali, H.G.E.D.H., Saroit, I.A. and Kotb, A.M., 2017. Grouped tasks scheduling algorithm based on QoS in Cloud computing network. Egyptian Informatics Journal, 18(1), pp.11-19.
- Sampaio, A.M., Barbosa, J.G. and Prodan, R., 2015. PIASA: A power and interference aware resource management strategy for heterogeneous workloads in Cloud data centers. Simulation Modelling Practice and Theory, 57, pp.142-160.
- Mishra, S.K., Puthal, D., Sahoo, B., Jena, S.K. and Obaidat, M.S., 2018. An adaptive task allocation technique for green Cloud computing. The Journal of Supercomputing, pp.1-16.
- Li, H., Li, J., Yao, W., Nazarian, S., Lin, X. and Wang, Y., 2017, March. Fast and energy-aware resource provisioning and task scheduling for Cloud systems. In Quality Electronic Design (ISQED), 2017 18th International Symposium on (pp. 174-179). IEEE.
- Sanjeevi, P. and Viswanathan, P., 2015, December. A green energy optimized scheduling algorithm for Cloud data centers.In Computing and Network Communications (CoCoNet), 2015 International Conference on (pp. 941-945). IEEE.
Index Terms
Keywords