scholarly journals Comparing load balancing algorithms for web application in cloud environment

2020 ◽  
Vol 17 (2) ◽  
pp. 1104
Author(s):  
Zakaria Benlalia ◽  
Karim Abouelmehdi ◽  
Abderrahim Beni-hssane ◽  
Abdellah Ezzati
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Web Application ◽  
Cloud Environment ◽  
Computing Environment ◽  
New Paradigm ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Software And Hardware

<p>Cloud computing has emerged as a new paradigm for providing on-demand computing resources and outsourcing software and hardware infrastructures. Load balancing is one of the major concerns in cloud computing environment means how to distribute load efficiently among all the nodes. For solving such a problem, we need some load balancing algorithms, so in this paper we will compare the existing algorithms for web application.and based on results obtained we choose the best among them.</p>

scholarly journals A Reliable Friedman Hypothesis-Based Detection and Adaptive Load Balancing Scheme for Mitigating Reduction of Quality DDoS Attacks in Cloud Computing

2019 ◽  
Vol 9 (1) ◽  
pp. 360-366
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Denial Of Service ◽  
Distributed Denial Of Service ◽  
Cloud Environment ◽  
Cloud Infrastructure ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Demand Service

The computing resource availability in a cloud computing environment is considered as the vital attribute among the security essentialities due to the consequence of on its on demand service. The class of adversaries related to the Distributed Denial of Service (DDoS) attack is prevalent in the cloud infrastructure for exploiting the vulnerabilities during the implementation of their attack that still make the process of providing security and availability at the same time as a challenging objective. In specific, The in cloud computing is the major threat during the process of balancing security and availability at the same time. In this paper, A Reliable Friedman Hypothesis-based Detection and Adaptive Load Balancing Scheme (RFALBS-RoQ-DDOS) is contributed for effective detection of RoQDDoS attacks through Friedman hypothesis testing. It also inherited an adaptive load balancing approach that prevents the degree of imbalance in the cloud environment. The simulation results of the proposed RFALBS-RoQ-DDoS technique confirmed a superior detection rate and a adaptive load balancing rate of nearly 23% and 28% predominant to the baseline DDoS mitigation schemes considered for investigation.

Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment

2020 ◽  
Vol 17 (6) ◽  
pp. 2430-2434
Author(s):  
R. S. Rajput ◽  
Dinesh Goyal ◽  
Rashid Hussain ◽  
Pratham Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Virtual Machines ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Auto Scaling ◽  
Adequate Resource ◽  
Cloud Resources

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment, but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling controller for the optimal use of cloud resources.

scholarly journals Data Service Trust Measurement in Cloud Environment

2019 ◽  
Author(s):  
Lin Shi ◽  
Zilong Wang ◽  
Ning Chen ◽  
Jie Chen
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Virtual Machines ◽  
Management Service ◽  
Cloud Environment ◽  
Computing Environment ◽  
Optimization Scheme ◽  
Processing Scheme ◽  
Cloud Computing Environment ◽  
Cloud Data

Abstract Highly trusted issues will be one of the main obstacles to a new era of highly trusted cloud computing. In the cloud computing environment, because sensitive applications and user data are put into the cloud, they run in virtual machines in the data center. Among them, due to the existence of access vulnerability, virtualization vulnerability, web application vulnerability, etc., high trust issues arise from data control, identity authentication, lack of information and other related issues. The introduction of trust mechanisms can be very facilitate the solution of related issues, achieve highly trusted quantification, analysis, and modeling of cloud data centers, meet high trust requirements, and provide users with a highly trusted cloud computing environment. This article mainly studies the trust measure of data services in cloud environment. In this paper, the optimization scheme is verified through experiments, and the traditional big data processing scheme, the original Sahara and the optimization scheme are compared in six cases. Overall, the optimization scheme has a significant performance improvement. Compared with the default configuration of Sahara, the configuration of the new interface has increased the throughput in DFSIO by 120%. Using the design of the unified cache management service, Tachyon can reach 13 in specific situations. In the execution time of Sort workloads, the optimization scheme generally decreased by about 50% compared to the original Sahara, and the memory utilization increased from 80% to 96% in our experiments, but in the cache isolation and other areas need to be improved. The results are basically in line with expectations, which also confirms the rational thinking and value of this article on BDAaS performance research.

scholarly journals Exploiting GPUs in Virtual Machine for BioCloud

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Heeseung Jo ◽  
Jinkyu Jeong ◽  
Myoungho Lee ◽  
Dong Hoon Choi
Keyword(s):  
Cloud Computing ◽  
System Architecture ◽  
Biological Applications ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Pci Express ◽  
On Demand ◽  
Time Share ◽  
Pass Through

Recently, biological applications start to be reimplemented into the applications which exploit many cores of GPUs for better computation performance. Therefore, by providing virtualized GPUs to VMs in cloud computing environment, many biological applications will willingly move into cloud environment to enhance their computation performance and utilize infinite cloud computing resource while reducing expenses for computations. In this paper, we propose a BioCloud system architecture that enables VMs to use GPUs in cloud environment. Because much of the previous research has focused on the sharing mechanism of GPUs among VMs, they cannot achieve enough performance for biological applications of which computation throughput is more crucial rather than sharing. The proposed system exploits the pass-through mode of PCI express (PCI-E) channel. By making each VM be able to access underlying GPUs directly, applications can show almost the same performance as when those are in native environment. In addition, our scheme multiplexes GPUs by using hot plug-in/out device features of PCI-E channel. By adding or removing GPUs in each VM in on-demand manner, VMs in the same physical host can time-share their GPUs. We implemented the proposed system using the Xen VMM and NVIDIA GPUs and showed that our prototype is highly effective for biological GPU applications in cloud environment.

Workflow Scheduling for Scientific Application in Homogeneous Cloud Environment

2017 ◽  
Vol 7 (7) ◽  
pp. 137
Author(s):  
. Monika ◽  
Pardeep Kumar ◽  
Sanjay Tyagi
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Large Data ◽  
Workflow Scheduling ◽  
Cloud Environment ◽  
Computing Environment ◽  
Scientific Application ◽  
Cloud Computing Environment ◽  
Flow Of Information

In Cloud computing environment QoS i.e. Quality-of-Service and cost is the key element that to be take care of. As, today in the era of big data, the data must be handled properly while satisfying the request. In such case, while handling request of large data or for scientific applications request, flow of information must be sustained. In this paper, a brief introduction of workflow scheduling is given and also a detailed survey of various scheduling algorithms is performed using various parameter.

Impact of Cloud of Clouds in Enterprises Applications

2019 ◽  
pp. 21-33
Author(s):  
Lavanya S. ◽  
Susila N. ◽  
Venkatachalam K.
Keyword(s):  
Cloud Computing ◽  
Scheduling Algorithm ◽  
Business Environment ◽  
Cloud Environment ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
Network Bandwidth ◽  
Enterprise Application ◽  
Major Disruption ◽  
Utmost Care

In recent times, the cloud has become a leading technology demanding its functionality in every business. According to research firm IDC and Gartner study, nearly one-third of the worldwide enterprise application market will be SaaS-based by 2018, driving annual SaaS revenue to $50.8 billion, from $22.6 billion in 2013. Downtime is treated as the primary drawback which may affect great deals in businesses. The service unavailability leads to a major disruption affecting the business environment. Hence, utmost care should be taken to scale the availability of services. As cloud computing has plenty of uncertainty with respect to network bandwidth and resources accessibility, delegating the computing resources as services should be scheduled accordingly. This chapter proposes a study on cloud of clouds and its impact on a business enterprise. It is also decided to propose a suitable scheduling algorithm to the cloud of cloud environment so as to trim the downtime problem faced by the cloud computing environment.

Sign in / Sign up

Export Citation Format

Share Document