scholarly journals NetAP: Adaptive Polling Technique for Network Packet Processing in Virtualized Environments

2020 ◽  
Vol 10 (15) ◽  
pp. 5219
Author(s):  
Hyunchan Park ◽  
Juyong Seong ◽  
Munkyu Lee ◽  
Kyungwoon Lee ◽  
Cheol-Ho Hong
Keyword(s):  
Virtual Machine ◽  
Network Performance ◽  
Virtual Machines ◽  
Search Algorithm ◽  
Golden Section ◽  
Processing Technique ◽  
Packet Processing ◽  
Host System ◽  
Storage Devices ◽  
Adaptive Polling

In cloud systems, computing resources, such as the CPU, memory, network, and storage devices, are virtualized and shared by multiple users. In recent decades, methods to virtualize these resources efficiently have been intensively studied. Nevertheless, the current virtualization techniques cannot achieve effective I/O virtualization when packets are transferred between a virtual machine and a host system. For example, VirtIO, which is a network device driver for KVM-based virtualization, adopts an interrupt-based packet-delivery mechanism, and incurs frequent switch overheads between the virtual machine and the host system. Therefore, VirtIO wastes valuable CPU resources and decreases network performance. To address this limitation, this paper proposes an adaptive polling-based network I/O processing technique, called NetAP, for virtualized environments. NetAP processes network requests via a periodical polling-based mechanism. For this purpose, NetAP adopts the golden-section search algorithm to determine the near-optimal polling interval for various workloads with different characteristics. We implement NetAP in a Linux kernel and evaluated it with up to six virtual machines. The evaluation results show that NetAP can improve the network performance of virtual machines by up to 31.16%, while only using 32.92% of the host CPU time used by VirtIO for packet processing.

scholarly journals Energy Efficient Resource Allocation in Cloud Computing

2019 ◽  
Vol 8 (6S3) ◽  
pp. 2071-2074
Keyword(s):  
Virtual Machine ◽  
Service Provider ◽  
Physical System ◽  
Virtual Machines ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Host System ◽  
Physical Systems ◽  
Single Host

Cloud service provider in cloud environment will provide or provision resource based on demand from the user. The cloud service provider (CSP) will provide resources as and when required or demanded by the user for execution of the job on the cloud environment. The CSP will perform this in a static and dynamic manner. The CSP should also consider various other factors in order to provide the resources to the user, the prime among that will be the Service Level Agreement (SLA), which is normally signed by the user and cloud service provider during the inception phase of service. There are many algorithm which are used in order to allocate resources to the user in cloud environment. The algorithm which is proposed will be used to reduce the amount of energy utilized in performing various job execution in cloud environment. Here the energy utilized for execution of various jobs are taken into account by increasing the number of virtual machines that are used on a single physical host system. There is no thumb rule to calculate the number of virtual machines to be executed on a single host. The same can be derived by calculating the amount of space, speed required along with the time to execute the job on a virtual machine. Based up on this we can derive the number of Virtual machine on a single host system. There can be 10 virtual machines on a single system or even 20 number of virtual machines on single physical system. But if the same is calculated by the equation then the result will be exactly matching with the threshold capacity of the physical system[1]. If more number of physical systems are used to execute fewer virtual machines on each then the amount of energy consumed will be very high. So in order to reduce the energy consumption , the algorithm can be used will not only will help to calculate the number of virtual machines on single physical system , but also will help to reduce the energy as less number of physical systems will be in need[2].

scholarly journals Energy-Efficient Resource Provisioning Using Adaptive Harmony Search Algorithm for Compute-Intensive Workloads with Load Balancing in Datacenters

2020 ◽  
Vol 10 (7) ◽  
pp. 2323
Author(s):  
T. Renugadevi ◽  
K. Geetha ◽  
K. Muthukumar ◽  
Zong Woo Geem
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Power Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Resource Provisioning ◽  
Total Power

Drastic variations in high-performance computing workloads lead to the commencement of large number of datacenters. To revolutionize themselves as green datacenters, these data centers are assured to reduce their energy consumption without compromising the performance. The energy consumption of the processor is considered as an important metric for power reduction in servers as it accounts to 60% of the total power consumption. In this research work, a power-aware algorithm (PA) and an adaptive harmony search algorithm (AHSA) are proposed for the placement of reserved virtual machines in the datacenters to reduce the power consumption of servers. Modification of the standard harmony search algorithm is inevitable to suit this specific problem with varying global search space in each allocation interval. A task distribution algorithm is also proposed to distribute and balance the workload among the servers to evade over-utilization of servers which is unique of its kind against traditional virtual machine consolidation approaches that intend to restrain the number of powered on servers to the minimum as possible. Different policies for overload host selection and virtual machine selection are discussed for load balancing. The observations endorse that the AHSA outperforms, and yields better results towards the objective than, the PA algorithm and the existing counterparts.

scholarly journals Low Power Consumption on Cloud Data Centers Using HSA Algorithm

2020 ◽  
pp. 78-84
Author(s):  
Louay Al Nuaimy ◽  
Tadele Debisa Deressa ◽  
Mohammad Mastan ◽  
Syed Umar
Keyword(s):  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Search Algorithm ◽  
Rapid Development ◽  
Electricity Consumption ◽  
Cloud Infrastructure ◽  
Virtual Machine Migration ◽  
Cloud Data ◽  
The Right

The rapid development of knowledge and communication has created a new processing style called cloud computing. One of the key issues facing cloud infrastructure providers is minimizing costs and maximizing profitability. Power management in cloud centres is very important to achieve this. Energy consumption can be reduced by releasing inactive nodes or by reducing the migration of virtual machines. The second is one of the challenges of choosing the virtual machine deployment method to migrate to the right node. This article proposes an approach to reduce electricity consumption in cloud centres. This approach adapts Harmony's search algorithm to move virtual machines. Positioning is done by sorting nodes and virtual machines according to their priorities in descending order. Priority is calculated based on the workload. The proposed procedure is envisaged. The evaluation results show less virtual machine migration, greater efficiency and lower energy consumption.

Container-based virtualization technologies

2016 ◽  
Vol 39 (3-4) ◽  
Author(s):  
Sebastian Wüst ◽  
Dennis Schwerdel ◽  
Paul Müller
Keyword(s):  
Virtual Machine ◽  
System Integration ◽  
Virtual Machines ◽  
Host System ◽  
Client Software

AbstractAs a newer concept, in comparison to hypervisor technologies, container-based virtualization is a rather lightweight virtualization concept. By not emulating any hardware it has a much lower overhead with good isolation. The basic idea is to generate isolated containers which use the same kernel as the host system, instead of individual ones per virtual machine. Hence the virtualized applications or systems have to be compatible to the same kernel. Networking testbeds like ToMaTo can benefit from such technology, since it allows to run many virtual machines in parallel. In this paper, three representatives of Linux container-based virtualization technologies will be presented: OpenVZ, Linux-VServer and LXC. The main features and concepts of each technology will be discussed, followed by a comparison about performance, security, virtualization system integration and client software. At the end their value for ToMaTo will be rated.

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

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.

A Defense Mechanism Based on Improved Allocation Strategy of VMs Co-Resident Attack in Power Cloud Platform

2020 ◽  
Vol 13 ◽  
Author(s):  
Yuancheng Li ◽  
Pan Zhang ◽  
Daoxing Li ◽  
Jing Zeng
Keyword(s):  
Virtual Machine ◽  
Simulation Experiment ◽  
Virtual Machines ◽  
Defense Mechanism ◽  
Security Threats ◽  
Allocation Strategy ◽  
Cloud Platform ◽  
Deployment Strategy ◽  
Dbscan Algorithm ◽  
Maximum Minimum

Background: Cloud platform is widely used in electric power field. Virtual machine co-resident attack is one of the major security threats to the existing power cloud platform. Objective: This paper proposes a mechanism to defend virtual machine co-resident attack on power cloud platform. Method: Our defense mechanism uses the DBSCAN algorithm to classify and output the classification results through the random forest and uses improved virtual machine deployment strategy which combines the advantages of random round robin strategy and maximum/minimum resource strategy to deploy virtual machines. Results: we made a simulation experiment on power cloud platform of State Grid and verified the effectiveness of proposed defense deployment strategy. Conclusion: After the virtual machine deployment strategy is improved, the coverage of the virtual machine is remarkably reduced which proves that our defense mechanism achieves some effect of defending the virtual machine from virtual machine co-resident attack.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

scholarly journals A Unified Analysis for the Free Vibration of the Sandwich Piezoelectric Laminated Beam with General Boundary Conditions under the Thermal Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Guohua Gao ◽  
Ningze Sun ◽  
Dong Shao ◽  
Yongqiang Tao ◽  
Wei Wu
Keyword(s):  
Free Vibration ◽  
Boundary Conditions ◽  
Thermal Environment ◽  
Search Algorithm ◽  
Golden Section ◽  
Shear Deformation Theory ◽  
Simulation Software ◽  
Elastic Boundary ◽  
Piezoelectric Beam ◽  
Elastic Boundary Conditions

This article mainly analyzes the free vibration characteristic of the sandwich piezoelectric beam under elastic boundary conditions and thermal environment. According to the first-order shear deformation theory and Hamilton’s principle, the thermo-electro-elastic coupling equations of the sandwich piezoelectric beam are obtained. Meanwhile, elastic boundary conditions composed of an array of springs are introduced, and the displacement variables and external potential energy of the beam are expressed as wave functions. By using the method of reverberation-ray matrix to integrate and solve the governing equations, a search algorithm based on golden-section search is introduced to calculate the required frequency parameters. A series of numerical results are compared with those reported in literature studies and obtained by simulation software to verify the correctness and versatility of the search algorithm. In addition, three parametric research cases are proposed to investigate the frequency parameters of sandwich piezoelectric beams with elastic restraint conditions, material parameters, thickness ratio, different temperature rises, and external electric potential.

scholarly journals Virtual Disks Performance Analysis Using Flexible I/O and Powerstat

2021 ◽  
Vol 9 (10) ◽  
pp. 267-296
Author(s):  
Pritam Patange
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Disk File ◽  
Virtual Machine Monitor ◽  
Image File ◽  
File Formats ◽  
Physical Infrastructure ◽  
Disk Image ◽  
The Impact

Abstract: Cloud computing has experienced significant growth in the recent years owing to the various advantages it provides such as 24/7 availability, quick provisioning of resources, easy scalability to name a few. Virtualization is the backbone of cloud computing. Virtual Machines (VMs) are created and executed by a software called Virtual Machine Monitor (VMM) or the hypervisor. It separates compute environments from the actual physical infrastructure. A disk image file representing a single virtual machine is created on the hypervisor’s file system. In this paper, we analysed the runtime performance of multiple different disk image file formats. The analysis comprises of four different parameters of performance namely- bandwidth, latency, input-output operations performed per second (IOPS) and power consumption. The impact of the hypervisor’s block and file sizes is also analysed for the different file formats. The paper aims to act as a reference for the reader in choosing the most appropriate disk file image format for their use case based on the performance comparisons made between different disk image file formats on two different hypervisors – KVM and VirtualBox. Keywords: Virtualization, Virtual disk formats, Cloud computing, fio, KVM, virt-manager, powerstat, VirtualBox.

scholarly journals Virtual Machine Selection Algorithm Based on User Requirements in Mobile Cloud Computing Environment

2018 ◽  
Vol 17 (2) ◽  
pp. 7335-7349
Author(s):  
Rashid Alakbarov
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Mobile Cloud Computing ◽  
Virtual Machines ◽  
Mobile User ◽  
Base Stations ◽  
Mobile Cloud ◽  
Software Applications ◽  
Wireless Metropolitan Area Networks ◽  
Cloud Technologies

The article analyzes the advantages of mobile cloud technologies and problems emerging during the use of those. The network infrastructure created based on cloudlets at the second level of mobile cloud computing with hierarchical structure is analyzed. At the same time, the article explores the issues of satisfaction of demand of mobile equipment for computing and memory resources by using these technologies. The article presents one solution for the allocation of mobile user requests in virtual machines created in cloudlets located near base stations of wireless metropolitan area networks (WMAN) in a balanced way by considering the technical capacity of those. Alongside, the article considers the solution of user problem during designated time and the issue of determining virtual machines satisfying other requirements. For this purpose, different characteristics of the stated problem, virtual machines, as well as communication channels between a user and virtual machines are considered. By using possible values determining the importance of cloudlets, conditions for loading software applications of a user to a virtual machine are explored and an appropriate method is proposed.

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