Energy Efficient and VM Consolidation Framework using Improved Spider Monkey Optimization Algorithm

Cloud Computing is rapidly being utilized to operate informational technological services by outstanding technologies for a variety of benefits, including dynamically improved resources planning and a new service delivery method. The Cloud computing process is occurred by allowing the client devices for data access through the internet from a remote server, computers, and the databases. An internet connection is linked among the front end users such as client device, network, browser, and software application with the back end that constitutes of servers, computers, and database. For satisfying the demands of the Service Level Agreement (SLA), providers of cloud service should reduce the usage of energy. Capacity reservations oriented system is available by clouds’ providers to permit users for customizing Virtual Machines (VMs) having specified age and geographic resources, reduces the amount to be paid for cloud services. To overcome the aforementioned issue, an Improved Spider Monkey Optimization (ISMO) approach is proposed for cloud center optimization. The VM consolidation architecture based on the proposed ISMO algorithm decreases energy usage while attempting to prevent Service Level Agreement breaches. The accessibility of hosts or virtual machines (VMs) for task performance is measured by fitness. If the number of tasks to be handled increases the hosts of VMs available at right state. The proposed VM consolidation architecture decreases energy usage while also attempting to prevent Service Level Agreement breaches and also provide energy-efficient computing in data centers. The proposed approach may be utilized to provide energy-efficient computing in data centers. The energy efficiency of the proposed ISMO method is achieved 28266 whereas, the existing algorithm showed an energy efficiency of 6009 and 10001.

Download Full-text

Distance Aware VM allocation process to minimize energy consumption in cloud computing

Recent Patents on Computer Science ◽

10.2174/2213275912666191023143709 ◽

2019 ◽

Vol 12 ◽

Author(s):

Gurpreet Singh ◽

Manish Mahajan ◽

Rajni Mohana

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Energy Consumption ◽

Virtual Machine ◽

Virtual Machines ◽

Research Work ◽

Service Level Agreement ◽

Service Level ◽

Physical Machine ◽

Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Download Full-text

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

International Journal of Cloud Applications and Computing ◽

10.4018/ijcac.2012070104 ◽

2012 ◽

Vol 2 (3) ◽

pp. 86-97

Author(s):

Veena Goswami ◽

Sudhansu Shekhar Patra ◽

G. B. Mund

Keyword(s):

Cloud Computing ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Finite Buffer ◽

Web Browser ◽

Computing Paradigm ◽

Computing Services ◽

Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

Download Full-text

Virtual Machine Consolidation with Minimization of Migration Thrashing for Cloud Data Centers

Mathematical Problems in Engineering ◽

10.1155/2020/7848232 ◽

2020 ◽

Vol 2020 ◽

pp. 1-13

Author(s):

Xialin Liu ◽

Junsheng Wu ◽

Gang Sha ◽

Shuqin Liu

Keyword(s):

Virtual Machine ◽

Carbon Dioxide Emissions ◽

Data Centers ◽

Virtual Machines ◽

Service Level Agreement ◽

High Capacity ◽

Electrical Energy ◽

Cloud Data ◽

Cloud Data Centers ◽

Vm Consolidation

Cloud data centers consume huge amount of electrical energy bringing about in high operating costs and carbon dioxide emissions. Virtual machine (VM) consolidation utilizes live migration of virtual machines (VMs) to transfer a VM among physical servers in order to improve the utilization of resources and energy efficiency in cloud data centers. Most of the current VM consolidation approaches tend to aggressive-migrate for some types of applications such as large capacity application such as speech recognition, image processing, and decision support systems. These approaches generate a high migration thrashing because VMs are consolidated to servers according to VM’s instant resource usage without considering their overall and long-term utilization. The proposed approach, dynamic consolidation with minimization of migration thrashing (DCMMT) which prioritizes VM with high capacity, significantly reduces migration thrashing and the number of migrations to ensure service-level agreement (SLA) since it keeps VMs likely to suffer from migration thrashing in the same physical servers instead of migrating. We have performed experiments using real workload traces compared to existing aggressive-migration-based solutions; through simulations, we show that our approach improves migration thrashing metric by about 28%, number of migrations metric by about 21%, and SLAV metric by about 19%.

Download Full-text

Service Level Agreement Conformance in Virtual Machine Migration with an Improved Energy and Performance Management Method

Journal of Computational and Theoretical Nanoscience ◽

10.1166/jctn.2020.8984 ◽

2020 ◽

Vol 17 (9) ◽

pp. 3904-3906

Author(s):

Susmita J. A. Nair ◽

T. R. Gopalakrishnan Nair

Keyword(s):

Energy Consumption ◽

Performance Management ◽

Large Scale ◽

Data Centers ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Performance Degradation ◽

Virtual Machine Migration ◽

And Performance

Increasing demand of computing resources and the popularity of cloud computing have led the organizations to establish of large-scale data centers. To handle varying workloads, allocating resources to Virtual Machines, placing the VMs in the most suitable physical machine at data centers without violating the Service Level Agreement remains a big challenge for the cloud providers. The energy consumption and performance degradation are the prime focus for the data centers in providing services by strictly following the SLA. In this paper we are suggesting a model for minimizing the energy consumption and performance degradation without violating SLA. The experiments conducted have shown a reduction in SLA violation by nearly 10%.

Download Full-text

SLA and Performance Efficient Heuristics for Virtual Machines Placement in Cloud Data Centers

International Journal of Grid and High Performance Computing ◽

10.4018/ijghpc.2017070102 ◽

2017 ◽

Vol 9 (3) ◽

pp. 17-33 ◽

Cited By ~ 2

Author(s):

Oshin Sharma ◽

Hemraj Saini

Keyword(s):

Energy Consumption ◽

Data Centers ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Consolidation Process ◽

Cloud Data ◽

Trade Offs ◽

And Performance ◽

High Level

Cloud computing has revolutionized the working models of IT industry and increasing the demand of cloud resources which further leads to increase in energy consumption of data centers. Virtual machines (VMs) are consolidated dynamically to reduce the number of host machines inside data centers by satisfying the customer's requirements and quality of services (QoS). Moreover, for using the services of cloud environment every cloud user has a service level agreement (SLA) that deals with energy and performance trade-offs. As, the excess of consolidation and migration may degrade the performance of system, therefore, this paper focuses the overall performance of the system instead of energy consumption during the consolidation process to maintain a trust level between cloud's users and providers. In addition, the paper proposed three different heuristics for virtual machine (VM) placement based on current and previous usage of resources. The proposed heuristics ensure a high level of service level agreements (SLA) and better performance of ESM metric in comparison to previous research.

Download Full-text

An Energy-efficient Virtual Machine Placement Algorithm based Service Level Agreement in Cloud Computing Environments

Circulation in Computer Science ◽

10.22632/ccs-2017-252-25 ◽

2017 ◽

Vol 2 (6) ◽

pp. 1-6

Author(s):

Arash Mazidi ◽

Elham Damghanijazi ◽

Sajad Tofighy

Keyword(s):

Cloud Computing ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Model Management ◽

Time Data ◽

Computing Services ◽

Cloud Computing Services ◽

Placement Algorithm ◽

Leading Enterprises

The cloud computing has given services to the users throughout the world during recent years. The cloud computing services have been founded according to ‘As-Pay-You-Go’ model and some leading enterprises give these services. The giving these cloud-computing services has been developed every day and these requirements necessitate for more infrastructures and Internet providers (IPs). The nodes of data centers consume a lot of energy in cloud structure and disseminate noticeable amount of carbon dioxide into the environment. We define a framework and structure for cloud environment of efficient energy in the present paper. We examine the present problems and challenges based on this structure and then present and model management algorithms and source allocation in cloud computing environment in order to manage energy in addition to considering Service Level Agreement. The proposed algorithm has been implemented by cloudsim simulator where the obtained results from simulation of real-time data indicate that the proposed method is superior to previous techniques in terms of energy consumption and observance of Service Level Agreement. Similarly, number of live migration of virtual machines and quantity of transferred data has been improved.

Download Full-text

Quality of Services and Optimal Management of Cloud Centers with Different Arrival Modes

Advances in Wireless Technologies and Telecommunication - Multidisciplinary Perspectives on Telecommunications, Wireless Systems, and Mobile Computing ◽

10.4018/978-1-4666-4715-2.ch011 ◽

2014 ◽

pp. 185-198

Author(s):

V. Goswami ◽

S. S. Patra ◽

G. B. Mund

Keyword(s):

Cloud Computing ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Quality Of Services ◽

Finite Buffer ◽

Optimal Management ◽

It Industry ◽

Computing Paradigm

In Cloud Computing, the virtualization of IT infrastructure enables consolidation and pooling of IT resources so they are shared over diverse applications to offset the limitation of shrinking resources and growing business needs. Cloud Computing is a way to increase the capacity or add capabilities dynamically without investing in new infrastructure, training new personnel, or licensing new software. It extends Information Technology's existing capabilities. In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services is crucial. Based on the Service Level Agreement, the requests are processed in the cloud centers in different modes. This chapter deals with Quality of Services and optimal management of cloud centers with different arrival modes. For this purpose, the authors consider a finite-buffer multi-server queuing system where client requests have different arrival modes. It is assumed that each arrival mode is serviced by one or more virtual machines, and different modes have equal probabilities of receiving services. Various performance measures are obtained and optimal cost policy is presented with numerical results. A genetic algorithm is employed to search optimal values of various parameters for the system.

Download Full-text

Optimizing the Migration of Virtual Machines in Cloud Data Centers

International Journal of Embedded and Real-Time Communication Systems ◽

10.4018/ijertcs.289200 ◽

2022 ◽

Vol 13 (1) ◽

pp. 0-0

Keyword(s):

Data Centers ◽

Bin Packing ◽

Virtual Machines ◽

Service Level Agreement ◽

Service Level ◽

Virtual Machine Migration ◽

Cloud Data ◽

Time Simulation ◽

Cloud Data Centers ◽

Dynamic Resource

Dynamic resource allocation of cloud data centers is implemented with the use of virtual machine migration. Selected virtual machines (VM) should be migrated on appropriate destination servers. This is a critical step and should be performed according to several criteria. It is proposed to use the criteria of minimum resource wastage and service level agreement violation. The optimization problem of the VM placement according to two criteria is formulated, which is equivalent to the well-known main assignment problem in terms of the structure, necessary conditions, and the nature of variables. It is suggested to use the Hungarian method or to reduce the problem to a closed transport problem. This allows the exact solution to be obtained in real time. Simulation has shown that the proposed approach outperforms widely used bin-packing heuristics in both criteria.

Download Full-text