A Survey on Database Performance in Virtualized Cloud Environments

2012 ◽  
Vol 8 (3) ◽  
pp. 1-26 ◽  
Author(s):  
Todor Ivanov ◽  
Ilia Petrov ◽  
Alejandro Buchmann
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Database Systems ◽  
High Availability ◽  
Feed Processing ◽  
Computing Platform ◽  
Efficient Resource ◽  
Cloud Environments ◽  
Column Stores

Cloud Computing emerged as a major paradigm over the years. Major challenges it poses to computer science are related to latency, scale, and reliability issues. It leverages strong economical aspects and provides sound answers to questions like energy consumption, high availability, elasticity, or efficient computing resource utilization. Many Cloud Computing platform and solution providers resort to virtualization as key underlying technology. Properties like isolation, multi-virtual machine parallelism, load balancing, efficient resource utilization, and dynamic pre-allocation besides economic factors make it attractive. It not only legitimates the spread of several types of data stores supporting a variety of data modes, but also inherently requires different types of load: (i) analytical; (ii) Transactional/Update-intensive; and (iii) mixed real-time feed processing. The authors survey how database systems can best leverage virtualization properties in cloud scenarios. The authors show that read mostly database systems and especially column stores profit from virtualization in analytical and search scenarios. Secondly, cloud analytics virtualized database systems are efficient in transactional scenarios such as Cloud CRM virtualized database systems lag. The authors also explore how the nature of mixed cloud loads can be best reflected by virtualization properties like load balancing, migration, and high availability.

scholarly journals ENERGY EFFICIENT LOAD BALANCING FOR CLOUD DATA CENTER

2017 ◽  
Vol 10 (13) ◽  
pp. 162
Author(s):  
Amey Rivankar ◽  
Anusooya G
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Energy Efficient ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Efficient Resource ◽  
Cloud Data Centers ◽  
Near Future

Cloud computing is the latest trend in large-scale distributed computing. It provides diverse services on demand to distributive resources such asservers, software, and databases. One of the challenging problems in cloud data centers is to manage the load of different reconfigurable virtual machines over one another. Thus, in the near future of cloud computing field, providing a mechanism for efficient resource management will be very significant. Many load balancing algorithms have been already implemented and executed to manage the resources efficiently and adequately. The objective of this paper is to analyze shortcomings of existing algorithms and implement a new algorithm which will give optimized load balancingresult.

A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue

2020 ◽  
Vol 11 (1) ◽  
pp. 12-36
Author(s):  
Minakshi Sharma ◽  
Rajneesh Kumar ◽  
Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Cloud Service ◽  
Cloud Environment ◽  
Cloud Service Provider ◽  
Qos Parameters ◽  
Load Balancing Algorithm

Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

A Survey on Load Balancing Algorithms for Cloud Environment

2019 ◽  
Vol 16 (2) ◽  
pp. 764-767
Author(s):  
P. Chitra ◽  
Karthika D. Renuka ◽  
K. Senathipathi ◽  
S. Deepika ◽  
R. Geethamani
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Comparative Analysis ◽  
Load Balancing ◽  
Resource Utilization ◽  
The Internet ◽  
Cloud Environment ◽  
Web Based ◽  
Qos Metrics

Cloud computing is the cutting edge technology in the information field to provide services to the users over the internet through web–based tools and applications. One of the major aspects of cloud computing is load balancing. Challenges like Quality of service (QoS) metrics and resource utilization can be improved by balancing the load in cloud environment. Specific scheduling criteria can be applied using load balancing for users prioritization. This paper surveys different load balancing algorithms. The approaches that are existing are discussed and analyzed to provide fair load balancing and also a comparative analysis was presented for the performance of the existing different load balancing schemes.

Efficient on Demand Dynamic Availability-Distribution-Span Scheduling and Load Balancing Scheme for Cloud Computing

2016 ◽  
Vol 13 (10) ◽  
pp. 7655-7660 ◽  
Author(s):  
V Jeyakrishnan ◽  
P Sengottuvelan
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Scheduling Algorithms ◽  
Time Factor ◽  
Cloud Environment ◽  
On Demand ◽  
Availability Factor ◽  
Scheduling Method

The problem of load balancing in cloud environment has been approached by different scheduling algorithms. Still the performance of cloud environment has not been met to the point and to overcome these issues, we propose a naval ADS (Availability-Distribution-Span) Scheduling method to perform load balancing as well as scheduling the resources of cloud environment. The method performs scheduling and load balancing in on demand nature and takes dynamic actions to fulfill the request of users. At the time of request, the method identifies set of resources required by the process and computes Availability Factor, Distributional Factor and Span Time factor for each of the resource available. Based on all these factors computed, the method schedules the requests to be processed in least span time. The proposed method produces efficient result on scheduling as well as load balancing to improve the performance of resource utilization in the cloud environment.

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.

Elastic Optical Network Service-Oriented Architecture (SOA) Used for Cloud Computing and Its Resource Mapping Optimization Scheme

2020 ◽  
Vol 15 (4) ◽  
pp. 442-449
Author(s):  
Xun Xia ◽  
Ling Chen
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Service Oriented Architecture ◽  
Optical Network ◽  
Spectrum Utilization ◽  
Mapping Algorithm ◽  
Resource Mapping ◽  
Elastic Optical Network ◽  
Service Oriented

In this study, starting from the elastic optical network, the layered and function isolated service-oriented architecture (SOA) is introduced, so as to propose an elastic optical network SOA for cloud computing, and further study the resource mapping of optical network. Linear mapping model, random routing mapping algorithm, load balancing mapping algorithm and link separation mapping algorithm are introduced respectively, and the resource utilization effect of different mapping algorithms for the proposed optical network is compared. During the experiment, firstly, the elastic optical network is tested. It is found that the node utilization and spectrum utilization of the underlying optical fiber level network are significantly improved. Within the average service time of 0.312 s∼0.416 s, the corresponding node utilization and spectrum utilization are 90% and 80% respectively. In the resource mapping experiment, load balancing algorithm and link separation algorithm can effectively improve the mapping success rate of services. Among them, the link separation mapping algorithm can improve the spectrum resource utilization of optical network by 15.6%. The elastic optical network SOA proposed in this study is helpful to improve the use of network resources.

The Research of Energy Consumption Control of Tobacco Information Based on Cloud Computing

2014 ◽  
Vol 915-916 ◽  
pp. 1393-1396
Author(s):  
Xue Feng Jiang ◽  
Zheng Min Wang ◽  
Hui Liang Dong ◽  
Wei Li
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Resource Utilization ◽  
Effective Control ◽  
Enterprise Information ◽  
Computing Platform ◽  
Management Platform ◽  
Platform Architecture ◽  
Cloud Computing Platform ◽  
Consumption Control

With the development of technology and enterprise information resources utilization improving system reliability requirements, cloud computing is becoming more and more widely used. To improve the tobacco resource utilization of a lot of information and increase reliability of resource platform, this article is based on cloud computing technology, to research the use of virtualization technology on tobacco cloud computing platform architecture carried on the system design, and studies the tobacco cloud management platform, based on effective control of tobacco information resource utilization and energy consumption, to improve the reliability of the resource platform, having the vital significance to the development of the tobacco industry.

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