چکیده (انگلیسی):

Cloud computing is an interesting and beneficial area in modern
distributed computing. It enables millions of users to use the offered
services through their own devices or terminals. Cloud computing offers an
environment with low cost, ease of use and low power consumption by
utilizing server virtualization in its offered services (e.g., Infrastructure as a
Service). The pool of Virtual Machines (VMs) in a cloud computing Data
Center (DC) needs to be managed through an efficient task scheduling
algorithm to maintain quality of service and resource utilization and thus
ensure the positive impact of energy consumption in the cloud computing
environment. In this study, an experimental comparative study is carried
out among three task scheduling algorithms in cloud computing, namely,
random resource selection, round robin and green scheduler. Based on the
analysis of the simulation result, we can conclude which algorithm is the
best for scheduling in terms of energy and performance of VMs. The
evaluation of these algorithms is based on three metrics: Total power
consumption, DC load and VM load. A number of experiments with
various aims are completed in this empirical comparative study. The results
showed that there is no algorithm that is superior to the others. Each has its
own pros and cons. Based on the simulation performed, the green scheduler
gives the best performance with respect to energy consumption. On the
other hand, the random scheduler showed the best performance with respect
to both VM and DC load. The round robin scheduler gives better VM and
DC load than the green scheduler but have more energy consumption than
both random and green schedulers. However, since the RR scheduler
distributes the tasks fairly, the network traffic is balanced and neither the
server nor the network node will get overloaded or congested.