Virtual Machine Placement Techniques Based on Biological Models: Comprehensive Research and Study

Abstract

Cloud computing is a recent trend of managing virtual spaces for holding information, accessing them through different devices. With green computing as a predominant design approach, managing energy efficiently is the proven solution to reduce emission of greenhouse gases. Count of physical machines can be optimized into a considerable number of data centers through which dynamic migration of information can be regulated. Consolidation process, followed by effective placement of VMs, can further improve the quality of services offered by cloud service providers. In the same context, placing the virtual machines within a specific region in considerable proximity of physical machines, is a renowned strategy for achieving energy efficiency in virtual environments. Optimization algorithms are, at times, inspired from biological models to deliver quality of service parameters and refining cost of communications, energy utilizations, managing resources and hence meeting the user expectations in terms of deadlines. A detailed review of biological models for constructing the taxonomy of virtual machine placement techniques is presented in this literature survey. The fundamental ideologies of placing virtual machines, their pros and cons, achievement of tangible and intangible factors, meeting the requirements and expectations of end users, issues and challenges in the design and implementation are discussed in detail. Different strategies, their approaches and optimization algorithms, comparisons of performance in real time and simulated platforms are presented for better understanding of the models. The common list of parameters which have to be satisfied for efficient functioning and energy management are listed. Finally, the article concludes with future prospects of biological models.