scholarly journals Performance of Communication- and Computation-Intensive SaaS on the OpenStack Cloud

2021 ◽  
Vol 11 (16) ◽  
pp. 7379
Author(s):  
Oleg Bystrov ◽  
Ruslan Pacevič ◽  
Arnas Kačeniauskas
Keyword(s):  
Cloud Computing ◽  
Performance Analysis ◽  
Virtual Machines ◽  
Cloud Infrastructure ◽  
Parallel Processes ◽  
Load Imbalance ◽  
Software Execution ◽  
Performance Challenges ◽  
Infrastructure Services ◽  
The Impact

The pervasive use of cloud computing has led to many concerns, such as performance challenges in communication- and computation-intensive services on virtual cloud resources. Most evaluations of the infrastructural overhead are based on standard benchmarks. Therefore, the impact of communication issues and infrastructure services on the performance of parallel MPI-based computations remains unclear. This paper presents the performance analysis of communication- and computation-intensive software based on the discrete element method, which is deployed as a service (SaaS) on the OpenStack cloud. The performance measured on KVM-based virtual machines and Docker containers of the OpenStack cloud is compared with that obtained by using native hardware. The improved mapping of computations to multicore resources reduced the internode MPI communication by 34.4% and increased the parallel efficiency from 0.67 to 0.78, which shows the importance of communication issues. Increasing the number of parallel processes, the overhead of the cloud infrastructure increased to 13.7% and 11.2% of the software execution time on native hardware in the case of the Docker containers and KVM-based virtual machines of the OpenStack cloud, respectively. The observed overhead was mainly caused by OpenStack service processes that increased the load imbalance of parallel MPI-based SaaS.

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 An analysis of software aging in cloud environment

2020 ◽  
Vol 10 (6) ◽  
pp. 5985
Author(s):  
Shruthi P. ◽  
Nagaraj G. Cholli
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Service ◽  
Software Systems ◽  
System Failure ◽  
Dynamic Nature ◽  
Software Aging ◽  
Software Rejuvenation ◽  
The Impact

Cloud Computing is the environment in which several virtual machines (VM) run concurrently on physical machines. The cloud computing infrastructure hosts multiple cloud service segments that communicate with each other using the interfaces. This creates distributed computing environment. During operation, the software systems accumulate errors or garbage that leads to system failure and other hazardous consequences. This status is called software aging. Software aging happens because of memory fragmentation, resource consumption in large scale and accumulation of numerical error. Software aging degrads the performance that may result in system failure. This happens because of premature resource exhaustion. This issue cannot be determined during software testing phase because of the dynamic nature of operation. The errors that cause software aging are of special types. These errors do not disturb the software functionality but target the response time and its environment. This issue is to be resolved only during run time as it occurs because of the dynamic nature of the problem. To alleviate the impact of software aging, software rejuvenation technique is being used. Rejuvenation process reboots the system or re-initiates the softwares. This avoids faults or failure. Software rejuvenation removes accumulated error conditions, frees up deadlocks and defragments operating system resources like memory. Hence, it avoids future failures of system that may happen due to software aging. As service availability is crucial, software rejuvenation is to be carried out at defined schedules without disrupting the service. The presence of Software rejuvenation techniques can make software systems more trustworthy. Software designers are using this concept to improve the quality and reliability of the software. Software aging and rejuvenation has generated a lot of research interest in recent years. This work reviews some of the research works related to detection of software aging and identifies research gaps.

Does cloud computing improve team performance and employees' creativity?

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Zou ◽  
Cheng Jian
Keyword(s):  
Cloud Computing ◽  
Team Performance ◽  
Supporting Evidence ◽  
Cloud Infrastructure ◽  
Employee Creativity ◽  
Content Type ◽  
Cloud Management ◽  
Cloud Application ◽  
The Impact ◽  
Cloud Resources

Purpose The present investigation goals to empirically test the role of expert cloud on team performance and employee creativity. Here, the expert cloud comprises cloud application, cloud management, cloud infrastructure and cloud resources. The present study aims to identify important and key criteria and examine the relationships among them. In other words, the purpose of this study to find out the impact and relationship between cloud application, cloud management, cloud infrastructure and cloud resources and team performance and employee creativity. Design/methodology/approach Today, human societies’ rapid growth and the environmental changes that surround us every day are clearly visible. They highly affect our activities. In today’s highly complex organizations, people alone cannot handle all the issues that have arisen. As organizational managers are faced with diverse cultures in the governance of organizations, the need to use work teams with different abilities and specializations to achieve the goals of organizations leads managers to use teamwork and focus on employee creativity. On the other hand, the expert cloud makes it possible for human societies like universities, firms, industries, institutes, businesses and colleges to pool and share their human resources’ skills, knowledge and experiences to meet the competitive era’s demands. Therefore, the current investigation examines the impact of expert cloud on team performance and employee creativity. The research information is collected using an online questionnaire. The data collected is analyzed using AMOS and SMART PLS software. Findings All of the formulated hypotheses are supported. The results have shown that cloud application, cloud management, cloud infrastructure and cloud resources positively and significantly affect team performance and employee creativity. Practical implications Managers must be conscious of the vital role that the professional cloud plays in team performance and the innovation of workers. This paper would also make executives more conscious of the powerful tools in the field of cloud computing. Firms can use the outcomes of this paper investigation to improve team performance and employee creativity. Originality/value It is considered one of the initial efforts to demonstrate the impacts of expert cloud on team performance and employee creativity. This study’s value relies on that practitioners and academics may have supporting evidence on the role played by novel technology such as an expert cloud.

scholarly journals A Study of Impact of Cloud Computing and Artificial Intelligence on Banking Services, Profitability and Operational Benefits

2021 ◽  
Vol 12 (6) ◽  
pp. 1617-1627
Author(s):  
Sadhana Tiwari, Shashank Bharadwaj, Dr. Sunil Joshi
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Business Models ◽  
Mobile Banking ◽  
Cloud Infrastructure ◽  
Regulatory Requirements ◽  
Banking Services ◽  
Virtual Tools ◽  
Confirmatory Factor ◽  
The Impact

Banks have seen a convergence in end-customer banking interactions over the last decade, owing to IT-enabled solutions and services such as Core Banking, Online Banking, Mobile Banking, Wallet, Wallets Kiosk Banking. The evolution of IT in the banking industry supports both banks and their clients. Banks' business models are now centered on delivering consumer joy via IT-enabled solutions and services. Cloud technology allows banks to follow a digital paradigm for providing novel channels, reducing TAT to market new offerings, fulfilling consumer expectations, and adhering to regulatory requirements at a lower cost. In constantly evolving technical paradigms, cloud-based solutions offer a higher value proposition to IT solutions and services. Device administrators can remotely assemble, upload, customize, and execute virtual tools to manage a business solution using cloud infrastructure. Furthermore, cloud IT technology can be scaled up or down at any time based on planned use and specifications without incurring high costs. To assess the impact of cloud computing and artificial intelligence in operational and service advantage Confirmatory factor analysis (CFA) technique is used. The thesis demonstrates how well the measured variables reflect the number of constructs and whether the estimation hypothesis is confirmed or rejected.

Impact of cloud computing on network management

2020 ◽  
Vol 26 (1) ◽  
Author(s):  
Oluwatosin O.P. Ogunbodede ◽  
Yinka S.O Adelanwa ◽  
Oyinkansola Adewumi
Keyword(s):  
Cloud Computing ◽  
Network Management ◽  
Virtual Machines ◽  
International Standard Organization ◽  
Internet Service ◽  
Application Performance ◽  
Standard Organization ◽  
Cloud Infrastructures ◽  
Functional Areas ◽  
The Impact

Cloud computing solution is now being adopted for reasons of economic and technical benefits by organizations to deliver array of services over the internet. Service provisioning has increased, so has the subscribers that access these services, as well as increased complexity in cloud infrastructures. However, cloud benefits to providers and clients may erode if there are no adequate cloud managing/monitoring frameworks built on the peculiar characteristics of the mission-critical environment. Plethora of literatures have been written on cloud architecture, implementation, services, virtual machines, energy efficiency, security, privacy, data loss etc. but not much on how cloud has changed our perception of network management with respect to five functional areas: Fault Configuration, Application, Performance and Security (FCAPS) of International Standard Organization (ISO). Noting that not much work has been done in this direction, this paper presents detailed analysis of the cloud, cloud network management with emphasis to the ISO functional areas. It uses key cloud-centric issues of concern to discuss and critically analyse the impact of cloud computing to network management and proffer significant ways forward within the possible capabilities of existing technology.Keywords Cloud-based virtual network (CVN), Cloud computing, Data Centre, Fault Configuration, Application, Performance and Security (FCAPS), Virtual Machine (VM)Vol. 26, No. 1, June 2019

Cloud Computing Virtual Machine Workload Prediction Method Based on Variational Autoencoder

2021 ◽  
Vol 12 (2) ◽  
pp. 33-45
Author(s):  
Fargana J. Abdullayeva
Keyword(s):  
Neural Networks ◽  
Cloud Computing ◽  
Deep Neural Networks ◽  
Virtual Machines ◽  
Prediction Method ◽  
Data Reconstruction ◽  
Cloud Infrastructure ◽  
Workload Prediction ◽  
Variational Autoencoder ◽  
Probability Criterion

The paper proposes a method for predicting the workload of virtual machines in the cloud infrastructure. Reconstruction probabilities of variational autoencoders were used to provide the prediction. Reconstruction probability is a probability criterion that considers the variability in the distribution of variables. In the proposed approach, the values of the reconstruction probabilities of the variational autoencoder show the workload level of the virtual machines. The results of the experiments showed that variational autoencoders gave better results in predicting the workload of virtual machines compared to simple deep neural networks. The generative characteristics of the variational autoencoders determine the workload level by the data reconstruction.

scholarly journals Optimized Scheduling Approach for Scientific Applications Based on Clustering in Cloud Computing Environment

2019 ◽  
Vol 20 (3) ◽  
pp. 527-540
Author(s):  
Walid Kadri ◽  
Belabbas Yagoubi
Keyword(s):  
Cloud Computing ◽  
Resource Management ◽  
Clustering Algorithm ◽  
Virtual Machines ◽  
Directed Acyclic Graphs ◽  
Resource Provisioning ◽  
Scientific Applications ◽  
Scheduling Policies ◽  
Use Of Resources ◽  
The Impact

Cloud Computing refers to the use of the computing capabilities of remote computers, where the user has considerable computing power without having powerful units. Scientific applications, usually represented as Directed Acyclic Graphs (DAGs), are an important class of applications that lead to challenging problems for resource management in distributed computing. With the advent of Cloud Computing, particularly the IaaS offers for on demand virtual machines leasing, multiple jobs execution, consisting of a large number of DAGs, needs an elaborated scheduling and resource provisioning policies, for efficient use of resources. Only few works exists that consider this problem in the context of clouds environment. In goal of optimization and fault tolerance, DAGs applications are generally partitioned into multiple parallel DAGs using clustering algorithm and assigned to VM (Virtual Machine) resources independently. In this work, we investigate through simulation, the impact of clustering for both provisioning and scheduling policies in the total makespan and financial costs for execution of user's application. We implemented four scheduling policies well-known in grid computing systems, and adapted clustering algorithm to our resource management policy that leases and destroys dynamically VMs. We show that dynamic policies can achieve equal or even better performance than static management policies.

scholarly journals The Hybrid Optimization Algorithm for Load Balancing in Cloud

2019 ◽  
Vol 8 (5S3) ◽  
pp. 67-71 ◽  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Fitness Function ◽  
Research Direction ◽  
Grey Wolf Optimizer ◽  
Grey Wolf ◽  
Network Access ◽  
Cloud Infrastructure ◽  
Shared Resources

The advancements in the cloud computing has gained the attention of several researchers to provide on-demand network access to users with shared resources. Cloud computing is important a research direction that can provide platforms and softwares to clients using internet. But, handling huge number of tasks in cloud infrastructure is a complicated task. Thus, it needs a load balancing method for allocating tasks to Virtual Machines (VMs) without influencing system performance. This paper proposes a load balancing technique, named Elephant Herd Grey Wolf Optimization (EHGWO) for balancing the loads. The proposed EHGWO is designed by integrating Elephant Herding Optimization (EHO) in Grey Wolf Optimizer (GWO) for selecting the optimal VMs for reallocation based on newly devised fitness function. The proposed load balancing technique considers different parameters of VMs and PMs for selecting the tasks to initiate the reallocation for load balancing. Here, two pick factors, named Task Pick Factor (TPF) and VM Pick Factor (VPF), are considered for allocating the tasks to balance the loads.

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