Article Details

QoS Based Scheduling Algorithms in Energy Aware Cloud Environment

[ Vol. 9 , Issue. 3 ]


Prakash Kumar, Krishna Gopal and Jai P. Gupta   Pages 222 - 230 ( 9 )


Background: Energy consumption is a major issue in Cloud Computing environments. Its efficient use can benefit in many ways such as cost saving, efficient utilization of resources and also saving the environment, as energy consumption, cost and time are important and decision making factors for both user as well as cloud service providers. QoS conscious scheduling of jobs along with energy awareness is very important, especially in cloud environment, where large datacenters are to be maintained and at the same time huge computations are involved. Optimal resource usage and price reduction are the direct and operational benefits for both users as well as the service providers. A substantial amount of energy is consumed by the underlying system resources. Hence, energy aware computations and scheduling is a big future concern that may heavily contribute to maintain the nature’s environmental systems, ecological balances and may avoid direct and indirect health hazards to all living beings. Omnidirectional benefits are the outcome of using energy aware scheduling techniques for Cloud environments and that too without compromising the Quality of Service.

Methods: Software based scheduling and testing is done with DVFS (Dynamic Voltage and Frequency Scaling) based experiments for minimizing the processing cost, makespan time in Energy Aware environment so that in addition to energy saving, the Quality of Service is not compromised. Simulations are done using CloudSim with combinations of various Quality of Service (QoS) parameters along with the combinations of energy aware VM allocation policies. A comparison of these algorithms is shown with the normally used existing algorithms based on the Processing Cost, MakespanTime and Energy Utilization parameters.

Results: A combination of Max-Min scheduling algorithm for cloudlet or task scheduling with Minimum Used Host scheduling algorithm for virtual machine allocation gives the most efficient environment in terms of Processing Cost, Makespan Time and Energy Consumption maintain the QoS.

Conclusion: It is observed that adoption of modified, conscious and logical scheduling policy in Cloud environments may drastically improve the QoS and save the energy usage as well, which is extremely important for huge Data Centers used in Cloud Environments, as described in various patents.


Cloud Computing, scheduling algorithms, energy aware computing, resource utilization, CloudSim.


Department of Computer Science Engineering & IT, JIIT, Noida

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