Nimisha Patel

Energy Efficient Resource Allocation During Initial Mapping of Virtual Machines to Servers in Cloud Datacenters

Library; Bacon’s Media Directory; Cabell’s Directories; Compendex (Elsevier Engineering Index); DBLP; Google Scholar; INSPEC; JournalTOCs; Library & Information Science Abstracts (LISA); Linguistics & Language Behavior Abstracts (LLBA); MediaFinder; SCOPUS; The Standard Periodical Directory; Ulrich’s Periodicals Directory; Web of Science; Web of Science Emerging Sources Citation Index (ESCI) Research Articles

Achieving Energy Aware Mechanism in Cloud Computing Environment

Cloud Computing is an emerging technology and it provides pay-per-use computing model over the Internet without giving hassle of resource management to the users. With the increasing demand and usage of Cloud applications worldwide, the issues of energy consumption, carbon emission and operational cost require special attention. Many researchers have tried to address these issues in different facets. In this paper, we first explore few research carried out in the direction of energy efficiency. We further propose (a) architecture for energy-aware mechanism in Cloud and (b) pre-processing approach by considering Virtual Machine (VM) allocation and consolidation techniques as key factors to achieving energy efficiency in Cloud Computing.

An Efficient VM Selection Strategy for Minimization of Migration in Cloud Environment

Cloud Computing has been one of the most emphasized paradigms over the last few years. Increased usage of Cloud Computing has resulted into the augmentation of energy consumption and emission of carbon footprints in the environment. Many researchers have been working in the different directions to address these issues. Out of various facets, efficient allocation of Virtual Machines (VMs) on hosts could be one of the good paths to save energy of data center. Optimized VM allocation process is divided into two phases viz. (i) selection of VMs to be migrated and (ii) placement of VMs on the new host. During the selection phase, minimizing the number of VMs to be migrated would result into improvement in performance and reduction in SLA violation. In this research, we have proposed a modification in an existing Minimization of Migration algorithm. The existing algorithm works for two scenarios viz. (a) single VM selection and (b) multiple VM selections. We find the scope of enhancement in the existing algorithm, especially in the case of multiple VM selection. In such scenario, the existing algorithm selects a combination of VMs which is not the optimum. We propose our algorithm to optimally select the combination of VMs such that number of VMs to be migrated remains minimal and utilization of host, after migration, reaches nearer (and below) to an upper threshold value. The prospect of this research would to enhance utilization of hosts which would result in a reduction in a number of live hosts resulting in saving in energy consumption.

Efficient Resource Allocation Strategy to Improve Energy Consumption in Cloud Data Centers

The Cloud provider offers computing resources such as processing capabilities, storage, network bandwidth etc. to the consumers on pay-as-go model. Due to its wide adaptability and ease of use, Cloud has emerged drastically over the last few years. However, increase in Cloud usage has lead to increase in number of computing resources and hence, increase in energy consumption. Recently, the issue of effective energy consumption has been addressed by a good number of researchers. In our work, we intend to study various energy efficient techniques for Cloud which uses resource allocation and consolidation to achieve the same. Further, we try to modify the existing technique by adding an extra parameter viz. time which assists in maximizing resource utilization and minimizing number of running servers.

Usage of Hybrid Mechanisms to Reduce Energy Consumption while Preserving Green SLA in Cloud Environment

Cloud computing provides utility oriented services and pay-as-you-go computing model for its users. Massive adoption of Cloud services leads to build a sustainable environment and also demands for green Cloud services. With the advancement in Cloud services, the issue of carbon dioxide emission becomes significant. There is also a challenge for Cloud provider to satisfy the customer by guaranteeing the services with performance and availability in Service Level Agreement (SLA). Hence, energy consumption and SLA violation become important issues for Cloud providers. These issues can be addressed in many facets viz. efficient provisioning of resources, reducing energy consumption in datacenters, server consolidation, virtual machine (VM) migration, minimizing SLA violation or also by providing SLA with green requirements. In this paper, we survey various techniques which address green SLA with Quality of Service (QoS) requirements by using different resource management and consolidation procedures. Further, we propose our work by considering the multi-criteria method for resource management which selects the host as probable migration destination having highest predicted utilization after allocating a VM on the host. Hence, we aim to address the issue of maintaining the trade-off between energy consumption and SLA violation.