scholarly journals Analysis of Load Balancing Techniques in Cloud Computing

2005 ◽  
Vol 4 (2) ◽  
pp. 737-741 ◽  
Author(s):  
Amandeep Sidhu ◽  
Supriya Kinger
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Storage ◽  
Cloud Storage ◽  
Job Scheduling ◽  
Single Node ◽  
Computing Paradigm ◽  
System A ◽  
Share Data ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. So, the amount of data storage increases quickly. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. A few existing scheduling algorithms can maintain load balancing and provide better strategies through efficient job scheduling and resource allocation techniques as well. In order to gain maximum profits with optimized load balancing algorithms, it is necessary to utilize resources efficiently. This paper discusses some of the existing load balancing algorithms in cloud computing and also their challenges.

scholarly journals IMPROVED ANT COLONY LOAD BALANCING ALGORITHM IN CLOUD COMPUTING

2015 ◽  
Vol 14 (4) ◽  
pp. 5636-5644
Author(s):  
Jaspreet Singh ◽  
Susmita Mishra
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Computing Paradigm ◽  
Share Data ◽  
Load Balancing Algorithm ◽  
Scalable Network

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. Since, cloud has inherited characteristic of distributed computing and virtualization there is a possibility of machines getting unused. Hence, in this paper, a load balancing algorithm has been proposed to avoid deadlocks and to provide proper utilization of all the Virtual Machines (VMs) while processing the requests received from the users by VM migration. Further, this paper also provides the anticipated results with the implementation of the proposed algorithm. The main contributions of our work is to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved Ant Colony Optimization algorithm can outperform them according to the experimental results.

scholarly journals A REVIEW ON DYNAMIC RESOURCE ALLOCATION BASED ON LEASE TYPES IN CLOUD ENVIRONMENT

2017 ◽  
Vol 16 (1) ◽  
pp. 7581-7585
Author(s):  
Sumanpreet Kaur ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Cloud Service ◽  
Single Node ◽  
Cloud Service Provider ◽  
Computing Paradigm ◽  
Share Data ◽  
Dynamic Resource ◽  
Working Performance ◽  
Scalable Network

Load balancing is one of the essential factors to enhance the working performance of the cloud service provider. Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently over a scalable network of nodes. Since Cloud computing stores the data and disseminated resources in the open environment. Since, cloud has inherited characteristic of distributed computing and virtualization there is a possibility of machines getting unused. Hence, in this paper, different load balancing algorithms has been studied. Different kinds of job types have been discussed and their problems have been reviewed. In the cloud storage, load balancing is a key issue. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed.

scholarly journals AN IMPLEMENTATION OF LOAD BALANCING ALGORITHM IN CLOUD ENVIRONMENT

2016 ◽  
Vol 15 (9) ◽  
pp. 7124-7129
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Storage ◽  
Cloud Environment ◽  
Computing Paradigm ◽  
Share Data ◽  
Load Balancing Algorithm

Cloud Computing is an emerging computing paradigm. It aims to share data, calculations, and service transparently overascalable network of nodes. Since Cloud computing stores the data and disseminated resources in the openenvironment.So, the amount of data storage increases quickly. As we know that a cloud is the collection of many nodes,which can support various types of application that is used by the clients on a basis of pay per use. Therefore, the system,which is incurring a cost for the user should function smoothly and should have algorithms that can continue the propersystem functioning even at peak usage. In this paper, a load balancing algorithm has been discussed and implemented inCloudSim environment. Multiple number of experiments have been conducted to analyze the results.

scholarly journals Multi-objective Prediction based Task Scheduling Method in Cloud Computing

2019 ◽  
Vol 8 (4) ◽  
pp. 9388-9394 ◽  
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Task Scheduling ◽  
Job Scheduling ◽  
Sigmoid Function ◽  
Service Model ◽  
Multi Objective ◽  
Computing Paradigm ◽  
Optimal Node ◽  
Scheduling Method

Cloud Computing is Internet based computing where one can store and access their personal resources from any computer through Internet. Cloud Computing is a simple pay-per-utilize consumer-provider service model. Cloud is nothing but large pool of easily accessible and usable virtual resources. Task (Job) scheduling is always a noteworthy issue in any computing paradigm. Due to the availability of finite resources and time variant nature of incoming tasks it is very challenging to schedule a new task accurately and assign requested resources to cloud user. Traditional task scheduling techniques are improper for cloud computing as cloud computing is based on virtualization technology with disseminated nature. Cloud computing brings in new challenges for task scheduling due to heterogeneity in hardware capabilities, on-demand service model, pay-per-utilize model and guarantee to meet Quality of Service (QoS). This has motivated us to generate multi-objective methods for task scheduling. In this research paper we have presented multi-objective prediction based task scheduling method in cloud computing to improve load balancing in order to satisfy cloud consumers dynamically changing needs and also to benefit cloud providers for effective resource management. Basically our method gives low probability value for not capable and overloaded nodes. To achieve the same we have used sigmoid function and Euclidean distance. Our major goal is to predict optimal node for task scheduling which satisfies objectives like resource utilization and load balancing with accuracy.

scholarly journals A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING

2016 ◽  
Vol 15 (14) ◽  
pp. 7435-7443 ◽  
Author(s):  
Sheenam Kamboj ◽  
Mr. Navtej Singh Ghumman
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Job Scheduling ◽  
Virtual Machines ◽  
Turnaround Time ◽  
Cloud Environment ◽  
Single Node ◽  
Novel Approach ◽  
Load Balancing Algorithm

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results. 

scholarly journals Understanding Load Balancing Algorithms and Their Need in Cloud Computing

2021 ◽  
Vol 9 (VI) ◽  
pp. 5378-5385
Author(s):  
Mridul Sadhu
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Data Processing ◽  
Data Storage ◽  
Natural World ◽  
The Internet ◽  
Exponential Increase ◽  
The World ◽  
Share Data

With each passing day, the number of users on the internet increases and thus does the data associated with them. This implies an exponential increase in the data storage and data processing units of practically all the servers on the net. Considering that the underlying idea and original purpose of the internet was to share data and resources, it becomes an increasingly difficult task to manage gigantic amounts of data associated with the ever-increasing number of users. This is why Cloud Computing has been able to bring a revolution in the world of technology and become the indispensable part of the internet that it is today. In this paper, we review the topic of load balancing and the various load balancing algorithms upon different measures. We also try to understand the most challenging problems that the cloud faces and some new load balancing techniques inspired from the natural world.

scholarly journals ENHANCED DYNAMIC RESOURCE ALLOCATION SCHEME BASED ON PACKAGE LEVEL ACCESS IN CLOUD COMPUTING

2017 ◽  
Vol 16 (5) ◽  
pp. 6903-6912
Author(s):  
Manpreet Kaur ◽  
Dr. Rajinder Singh
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machine ◽  
Job Scheduling ◽  
Research Work ◽  
Cloud Service ◽  
Current Status ◽  
Cloud Environment ◽  
Single Node ◽  
Load Balancing Algorithm

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. This research work deals with the balancing of work load in cloud environment. Load balancing is one of the essential factors to enhance the working performance of the cloud service provider. It would consume a lot of cost to maintain load information, since the system is too huge to timely disperse load. Load balancing is one of the main challenges in cloud computing which is required to distribute the dynamic workload across multiple nodes to ensure that no single node is overwhelmed. It helps in optimal utilization of resources and hence in enhancing the performance of the system. We propose an improved load balancing algorithm for job scheduling in the cloud environment using load distribution table in which the current status, current package, VM Capacity and the number of cloudlets submitted to each and every virtual machine will be stored. Submit the job of the user to the datacenter broker. Data center broker will first find the suitable Vm according to the requirements of the cloudlet and will match and find the most suitable Vm according to its availability or the machine with least load in the distribution table. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. The main contributions of the research work is to balance the entire system load while trying to minimize the make span of a given set of jobs. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.

Efficient Share Generator for Slicing and Securely Retrieving the Cloud-Hosted Heterogeneous Multimedia Data

2021 ◽  
pp. 20-32
Author(s):  
admin admin ◽  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Cloud Storage ◽  
Implementation Strategies ◽  
Critical Issue ◽  
Multimedia Data ◽  
Storage And Retrieval ◽  
Remote Storage ◽  
Source Transformation ◽  
Cloud Servers

Recently, the security of heterogeneous multimedia data becomes a very critical issue, substantially with the proliferation of multimedia data and applications. Cloud computing is the hidden back-end for storing heterogeneous multimedia data. Notwithstanding that using cloud storage is indispensable, but the remote storage servers are untrusted. Therefore, one of the most critical challenges is securing multimedia data storage and retrieval from the untrusted cloud servers. This paper applies a Shamir Secrete-Sharing scheme and integrates with cloud computing to guarantee efficiency and security for sensitive multimedia data storage and retrieval. The proposed scheme can fully support the comprehensive and multilevel security control requirements for the cloud-hosted multimedia data and applications. In addition, our scheme is also based on a source transformation that provides powerful mutual interdependence in its encrypted representation—the Share Generator slices and encrypts the multimedia data before sending it to the cloud storage. The extensive experimental evaluation on various configurations confirmed the effectiveness and efficiency of our scheme, which showed excellent performance and compatibility with several implementation strategies.

Different Perspectives of Cloud Security

2015 ◽  
pp. 1432-1449
Author(s):  
M. Sundaresan ◽  
D. Boopathy
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Service Provider ◽  
Web Application ◽  
Cloud Storage ◽  
Minimum Cost ◽  
Maximum Level ◽  
Local Data ◽  
Legal Security ◽  
Processing And Storage

Cloud storage systems can be considered to be a network of distributed datacenters that typically use cloud computing technology like virtualization and offer some kind of interface for storing data. To increase the availability of the data, it may be redundantly stored at different locations. Basic cloud storage is generally not designed to be accessed directly by users but rather incorporated into custom software using API. Cloud computing involves other processes besides storage. In this chapter, the authors discuss different viewpoints for cloud computing from the user, legal, security, and service provider perspectives. From the user viewpoint, the stored data creates a mirror of currently available local data. The backup feature allows users to recover any version of a previously stored data. Synchronization is the process of establishing consistency among the stored data. From the legal viewpoint, provisions regulating the user processing and storage of the data must have to be constant from when the data is stored in the cloud. The security viewpoint requires interaction with the Web application, data storage, and transmission. The service provider viewpoint requires the maximum level of cloud storage service at the minimum cost.

scholarly journals SLA-aware resource scheduling algorithm for cloud storage

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Yong Wang ◽  
Xiaoling Tao ◽  
Feng Zhao ◽  
Bo Tian ◽  
Akshita Maradapu Vera Venkata Sai
Keyword(s):  
Cloud Computing ◽  
Cloud Storage ◽  
Scheduling Algorithm ◽  
The Public ◽  
Computing Paradigm ◽  
Self Service ◽  
End Node ◽  
Violation Rate ◽  
And Storage ◽  
Compare And Contrast

AbstractCloud computing is a novel computing paradigm, which connects plenty of computing resources and storage resources via Internet. Cloud computing provides a number of high-quality services, such as cloud storage, outsourcing computing, and on-demand self-service, which have been widely accepted by the public. In cloud computing, by submitting their tasks to cloud, plenty of applications share huge computation and storage resources. However, how to schedule resource efficiently is a big challenge in cloud computing.In this paper, we propose a SLA-aware resource algorithm to enable cloud storage more efficiently. In our scheme, we take advantage of the back-end node space utilization and I/O throughput comprehensively simultaneously. We compare and contrast the existing scheduling storage policies by implementing those algorithms. The extensive tests show that our algorithm achieves a considerable improvement in terms of violation rate and the number of used hosts.

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