Abstract
Data Center energy usage has risen dramatically because of the rapid growth and demand for cloud computing. This excessive energy usage is a challenge from an economic and environmental point. Virtual Machine Placement (VMP) along with virtualization technologies is widely used to manage power utilization in data centers. The assignment of virtual machines to physical machines affects energy consumption. VMP is a process of mapping VMs onto a set of PMs in a data center to minimize total power consumption and maximize resource utilization. The VMP is an NP-hard problem due to its constraints and huge combinations. In this paper, we formulated the problem as a single objective optimization problem in which the objective is to minimize the energy consumption in cloud data centers. The main contribution of this paper is hybrid and adaptive harmony search algorithm for optimal placements of VMs to PMs. HSA with adaptive PAR settings, simulated annealing and local search strategy aims at minimizing energy consumption in cloud data centers with satisfying given constraints. Experiments are conducted to validate the performance of these variations. Results show that these hybrid HSA variations produce better results than basic HSA and adaptive HSA. Hybrid HS with simulated annealing, and local search strategy gives better results than other variants for 80 percent datasets.
Highlights
Cloud computing is the on-demand delivery of computing resources, such as software, data storage, computing power, networking, and database
The evaluation of our proposed algorithm is performed through different sets of experiments in a simulated environment
We developed a python program that can randomly generate a data set for the problems of different characteristics
Summary
Cloud computing is the on-demand delivery of computing resources, such as software, data storage, computing power, networking, and database. The different types of cloud services available such as infrastructure as a service (IaaS), software as a service (SaaS), and platform as a service (PaaS). There are many benefits for both data center providers and the enduser. A cloud provider is able to sell computer resources to a large number of consumers. Consumers are able to buy computing resources for lower costs, as compared to the costs of keeping each of these resources and private infrastructure (software, hardware). A cloud provider aims at maximizing profits and that implies reducing the deployed computer resources as much as possible
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