Enhanced Active Monitoring Load Balancing algorithm for Virtual Machines in cloud computing

2016 ◽  
Author(s):  
Shikha Garg ◽  
Dr. D.V. Gupta ◽  
Rakesh Kumar Dwivedi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Active Monitoring ◽  
Load Balancing Algorithm

scholarly journals Simulation and performance assessment of a modified throttled load balancing algorithm in cloud computing environment

2022 ◽  
Vol 12 (2) ◽  
pp. 2087
Author(s):  
Noha G. Elnagar ◽  
Ghada F. Elkabbany ◽  
Amr A. Al-Awamry ◽  
Mohamed B. Abdelhalim
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Processing Time ◽  
Virtual Machines ◽  
Active Monitoring ◽  
Load Fluctuation ◽  
Load Balancing Algorithm ◽  
And Performance ◽  
Load Balancer

<span lang="EN-US">Load balancing is crucial to ensure scalability, reliability, minimize response time, and processing time and maximize resource utilization in cloud computing. However, the load fluctuation accompanied with the distribution of a huge number of requests among a set of virtual machines (VMs) is challenging and needs effective and practical load balancers. In this work, a two listed throttled load balancer (TLT-LB) algorithm is proposed and further simulated using the CloudAnalyst simulator. The TLT-LB algorithm is based on the modification of the conventional TLB algorithm to improve the distribution of the tasks between different VMs. The performance of the TLT-LB algorithm compared to the TLB, round robin (RR), and active monitoring load balancer (AMLB) algorithms has been evaluated using two different configurations. Interestingly, the TLT-LB significantly balances the load between the VMs by reducing the loading gap between the heaviest loaded and the lightest loaded VMs to be 6.45% compared to 68.55% for the TLB and AMLB algorithms. Furthermore, the TLT-LB algorithm considerably reduces the average response time and processing time compared to the TLB, RR, and AMLB algorithms.</span>

scholarly journals An Optimal Solution in cloud computing for Load Balancing using Genetic Algorithm

2019 ◽  
Vol 8 (6) ◽  
pp. 2490-2494
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Load Balancing ◽  
Virtual Machines ◽  
Optimal Solution ◽  
Cloud Services ◽  
Research Trend ◽  
Schedule Length ◽  
Research Gap ◽  
Load Balancing Algorithm

Cloud computing is a research trend which bring various cloud services to the users. Cloud environment face various challenges and issues to provide efficient services. In this paper, a novel Genetic Algorithm based load balancing algorithm has been implemented to balance the load in the network. The literature review has been studied to understand the research gap. More specifically, load balancing technique authenticate the network by enabling Virtual Machines (VM). The proposed technique has been further evaluated using the Schedule Length Runtime (SLR) and Energy consumption (EC) parameters. Overall, the effective results has been obtained such as 46% improvement in consuming the energy and 12 % accuracy for the SLR measurement. In addition, results has been compared with the conventional approaches to validate the outcomes.

scholarly journals Measuring the Performance on Load Balancing Algorithms

2019 ◽  
pp. 41-49 ◽  
Author(s):  
Saumendu Roy ◽  
Dr. Md. Alam Hossain ◽  
Sujit Kumar Sen ◽  
Nazmul Hossain ◽  
Md. Rashid Al Asif
Keyword(s):  
Cloud Computing ◽  
Reaction Time ◽  
Load Balancing ◽  
Virtual Machines ◽  
Huge Amount ◽  
Heavy Load ◽  
Cloud Server ◽  
Load Balancing Algorithm ◽  
Day By Day ◽  
Better Than

Load balancing is an integrated aspect of the environment in cloud computing. Cloud computing has lately outgoing technology. It has getting exoteric day by day residence widespread chance in close to posterior. Cloud computing is defined as a massively distributed computing example that is moved by an economic scale in which a repertory of abstracted virtualized energetically. The number of clients in cloud computing is increasing exponentially. The huge amount of user requests attempt to entitle the collection for numerous applications. Which alongside with heavy load not far afield off from cloud server. Whenever particular (Virtual Machine) VMs are overloaded then there are no more duties should be addressed to overloaded VM if under loaded VMs are receivable. For optimizing accomplishment and better response or reaction time the load has to be balanced between overloaded VMs (virtual machines). This Paper describes briefly about the load balancing accession and identifies which is better than others (load balancing algorithm).

scholarly journals Resource Allocation in Cloud Computing using Heuristic Load Balancing Algorithm

2020 ◽  
Author(s):  
Anup Shrestha ◽  
Suriayati Chuprat ◽  
Nandini Mukherjee
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Completion Time ◽  
Virtual Machines ◽  
It Services ◽  
Computing Environment ◽  
Load Balancing Algorithm ◽  
Better Than

Cloud computing is becoming more popular, unlike conventional computing, due to its added advantages. This is because it offers utility-based services to its subscribers upon their demand. Furthermore, this computing environment provides IT services to its users where they pay for every use. However, the increasing number of tasks requires virtual machines for them to be accomplished quickly. Load balancing a critical concern in cloud computing due to the massive increase in users' numbers. This paper proposes the best heuristic load balancing algorithm that will schedule a strategy for resource allocation that will minimize make span (completion time) in any technology that involves use cloud computing. The proposed algorithm performs better than other load balancing algorithms.

scholarly journals ENHANCING JOB ALLOCATION USING NBST IN CLOUD ENVIRONMENT: A REVIEW

2017 ◽  
Vol 16 (3) ◽  
pp. 6247-6253
Author(s):  
Ashima Ashima ◽  
Mrs Navjot Jyoti
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
User Satisfaction ◽  
Data Centers ◽  
Virtual Machines ◽  
Efficient Manner ◽  
Equal Distribution ◽  
Cloud Data ◽  
Cloud Data Centers ◽  
Load Balancing Algorithm

Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. Load balancing is a critical aspect that ensures that all the resources and entities are well balanced such that no resource or entity neither is under loaded nor overloaded. The load balancing algorithms can be static or dynamic.  Load balancing in this environment means equal distribution of workload across all the nodes. Load balancing provides a way of achieving the proper utilization of resources and better user satisfaction. Hence, use of an appropriate load balancing algorithm is necessary for selecting the virtual machines or servers. This paper focuses on the load balancing algorithm which distributes the incoming jobs among VMs optimally in cloud data centers. In this paper, we have reviewed several existing load balancing mechanisms and we have tried to address the problems associated with them.

scholarly journals Hybrid Heuristic Load Balancing Algorithm For Resource Allocation In Cloud Computing

2020 ◽  
Author(s):  
Anup Shrestha ◽  
Suriayati Chuprat ◽  
Nandini Mukherjee
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Completion Time ◽  
Virtual Machines ◽  
It Services ◽  
Computing Environment ◽  
Hybrid Heuristic ◽  
Load Balancing Algorithm ◽  
Better Than

<div> <div> <div> <p>Cloud computing is becoming more popular, unlike conventional computing, due to its added advantages. This is because it offers utility-based services to its subscribers upon their demand. Furthermore, this computing environment provides IT services to its users where they pay for every use. However, the increasing number of tasks requires virtual machines for them to be accomplished quickly. Load balancing a critical concern in cloud computing due to the massive increase in users' numbers. This paper proposes the best heuristic load balancing algorithm that will schedule a strategy for resource allocation that will minimize make span (completion time) in any technology that involves use cloud computing. The proposed algorithm performs better than other load balancing algorithms.</p> </div> </div> </div>

scholarly journals Hybrid Heuristic Load Balancing Algorithm For Resource Allocation In Cloud Computing

2020 ◽  
Author(s):  
Anup Shrestha ◽  
Suriayati Chuprat ◽  
Nandini Mukherjee
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Load Balancing ◽  
Completion Time ◽  
Virtual Machines ◽  
It Services ◽  
Computing Environment ◽  
Hybrid Heuristic ◽  
Load Balancing Algorithm ◽  
Better Than

<div> <div> <div> <p>Cloud computing is becoming more popular, unlike conventional computing, due to its added advantages. This is because it offers utility-based services to its subscribers upon their demand. Furthermore, this computing environment provides IT services to its users where they pay for every use. However, the increasing number of tasks requires virtual machines for them to be accomplished quickly. Load balancing a critical concern in cloud computing due to the massive increase in users' numbers. This paper proposes the best heuristic load balancing algorithm that will schedule a strategy for resource allocation that will minimize make span (completion time) in any technology that involves use cloud computing. The proposed algorithm performs better than other load balancing algorithms.</p> </div> </div> </div>

scholarly journals Load Balancing Mechanisms in Amazon Web Services using Meta Heuristic Rules

2019 ◽  
Vol 8 (2S11) ◽  
pp. 4071-4075
Keyword(s):  
Machine Learning ◽  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Resource Utilization ◽  
Waiting Time ◽  
Virtual Machines ◽  
Machine Learning Techniques ◽  
System Response ◽  
Load Balancing Algorithm

Cloud computing is defined as the resource that can be delivered or accessed by the local host from the remote server via the internet. Cloud providers typically use a "pay-as-you-go" model. The evolution of cloud computing has led to the evolution of modern environment due to abundance and advancement of computing and communication infrastructure. During user request, and system response generation, an amount load will be assigned in the cloud computing, where it may be over or under load. Due to heavy load, power consumption and energy management problems are created, and it makes system failure and lead data loss. Though, an efficient load balancing method is compulsory to overcome all mentioned problems. The objective of this work is to develop a metaheuristic load balancing algorithm to migrate multi-server for load balancing and machine learning techniques is used to increase the cloud resource utilization and minimize the make-span time of the task. Using an unsupervised machine learning technique, it is possible to predict the correct response time and waiting time of the servers by getting the prior knowledge about the virtual machines and its clusters. And this work involves to calculate the accuracy rate of the Round-Robin load balancing algorithm and then compared it with a proposed algorithm. By this work, the response time and waiting time can be minimized and also it increases the resource utilization and minimize the make- span time of the task.

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. 

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