International Journal of Cloud-Computing and Super-Computing Vol.2, No.1 (2015), pp.21-34 http://dx.doi.org/10.14257/ijcs.2015.2.1.03 ISSN: 2287-8491 IJCS Copyright ⓒ 2015 SERSC Energy Efficient Load Balancing of Virtual Machines in Cloud Environments Abdulhussein Abdulmohson 1 , Sudha Pelluri 2 and Ramachandram Sirandas 3 University of Kufa - Alnajaf-Iraq 1 Osmania university-Hyderabad-India 2,3 abdulhussein.fadhel@uokufa.edu.iq 1 , sudhapv23@gmail.com 2 , schandram@gmail.com Abstract Today Cloud computing is used in a wide range of domains. By using cloud computing a user can utilize services and pool of resources through internet. The cloud computing platform guarantees subscribers that it will live up to the service level agreement (SLA) in providing resources as service and as per needs. However, it is essential that the provider be able to effectively manage the resources. One of the important roles of the cloud computing platform is to balance the load amongst different servers in order to avoid overloading in any host and improve resource utilization. The concept of Genetic algorithm is specifically useful in load balancing for best virtual machines distribution across servers. In this paper, we focus on load balancing and also on efficient use of resources to reduce the energy consumption without degrading cloud performance. Keywords: Cloud computing, load balancing, genetic algorithm, energy efficient management 1. Introduction With the explosive growth of the use of cloud computing ,the workload on servers is increasing rapidly and servers may easily be overloaded. The effective use of resources is important to serve a large number of customers, maximizing productivity and reducing the response times in cloud. Effective management of resources also enables minimize resource starvation, avoid possible overloads and ensure fairness amongst the parties utilizing the resources. Load balancing has great impact on performance in a cloud computing environment, it makes the cloud more efficient and improve user satisfaction. Energy efficient Load balancing is an effective way to reduce resource consumption and serve a large number of users and hence improve performance. Energy efficient Load balancing using genetic algorithm uses the memory, CPU, bandwidth as a parameters for calculating the load of each host and migration cost for each virtual machine (Migration parameters should not increase load and reduce the benefit of transfer of virtual machine to another server). During low-workload hours, the CPU utilization is less than we’d like. As a result, overall memory and CPU utilization is not as efficient as we’d like. For example, one specific type of Facebook server consumes about 60 watts when the server is IDLE, while the consumption jumps to 130 watts when it runs low-level CPU task [16]. But surprisingly, at high load the power consumption is only 150 watts. The difference between the power consumption in low load and high load is only marginal. Hence, it would be highly beneficial to run high load on most servers. To do that, we try to decrease the number of servers running by combining the total load and accommodating it in less numbers of servers without overloading on any servers. We can hibernate some servers by efficiently managing the load on servers. The main gain is obtained by reducing the number of servers that are switched- on.