• Juhi Mondal Department of CSE, VIT University, Chennai, Tamil Nadu, India.
  • Pradeep Kv Department of CSE, VIT University, Chennai, Tamil Nadu, India.
  • Vijayakumar V Department of CSE, VIT University, Chennai, Tamil Nadu, Indi


Cloud computing is the hottest topic in today’s world and is being used by most of the information technology companies due to its benefits in
cost saving and ease of use. It is a dynamic, scalable, and pay-per-use distributed computing model. The cloud computing is aims to give access
to remote and geographically distributed resources. Scheduling the job from one data center to other data center or from one region of cloud to
other region is truly a testing in cloud environment. However, when data are shifted from one data center to other data center, huge amount of
carbon dioxide (CO2) gases emits and also consumes more power. Since energy is an important issue, that is, why green cloud computing comes
into the picture. Green cloud computing can be obtained by applying various techniques and algorithms, which use less power and emits less
CO2 gas, that is, damaging the environment. Cloud provides many facilities to its tenants such as sharing of resources for different purposes. In
cloud domain, job scheduling is one of the biggest and hypothetical problems. Numerous investigations for scheduling a job and efforts carried
out in this regard because it is one of the main jobs to get the most profit. Scheduling can decrease the power consumption. So many algorithms
had been proposed for this purpose, and a lot more had to be done. In the paper, intends to present a variety of energy-efficient job scheduling
algorithms along with performance comparison analysis of various preexisting algorithms for scheduling jobs to provide energy efficiency in
green cloud computing.

Keywords: Cloud computing, Job scheduling, Resource allocation, Efficiency, Performance, Cost.


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How to Cite
Mondal, J., P. Kv, and V. V. “A REVIEW ON ENERGY EFFICIENT JOB SCHEDULING ALGORITHMS IN GREEN CLOUD COMPUTING”. Asian Journal of Pharmaceutical and Clinical Research, Vol. 10, no. 13, Apr. 2017, pp. 453-6, doi:10.22159/ajpcr.2017.v10s1.20509.
Original Article(s)