A Hybrid Method for Reduction of Energy Consumption in Cloud Networks
Mehran Tarahomi, Mohammad Izadi Kish International Campus Sharif University of Technology Tehran, Iran, Department of Computer Engineering Sharif University of Technology Tehran, Iran
Abstract: Cloud computing is consisted of physical data centers each of which including hundreds or thousands of
computers. A key technology which has enabled cloud computing feasible, is virtualization. Virtualization allows us to
separate virtual machines in a way that each of these so-called virtualized machines can be configured on a number of hosts
according to the type of application of the user. It is also possible to dynamically alter the allocated resources of a virtual
machine. Different methods of energy saving in data centers can be divided to three general categories: 1) energy saving
methods based on balancing the loads of resources; 2) scheduling by the help of hardware facilities; 3) reducing the consumption
of energy through being aware of thermal characteristics of the environment.
One of the most important challenges in terms of cloud computing is to maintain an optimized load balance in cloud environment
on servers because this issue is critical for energy consumption. Since load balance algorithms depend on the current
behavior of the system, they act dynamically. Important factors which should be taken into account while developing such
types of algorithms include load estimation, load ratio, adaptability of different systems, performance of the system, interaction
between nods, scheduling, nature of the transferred service, selecting nodes and etc.
By taking a detailed look on previous methods and challenges of energy saving in cloud networks, we provide a hybrid method
which enables us to save energy through finding a suitable configuration for placement of virtual machines and through being
aware of special features of virtual environments for scheduling and balancing their dynamic loads by the help of live
migration method.
Keywords: Cloud Networks, Virtual Machines, Energy Saving, Scheduling, Load Balance, Live Migration, Cloudsim, DVFS A Hybrid Method for Reduction of Energy Consumption in Cloud Networks
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