scholarly journals Load Balancing of Unbalanced Matrix Problem of Maximum Machines with Min Min Algorithm

2019 ◽  
Vol 8 (3) ◽  
pp. 627-629
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Execution Time ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Elastic Behavior ◽  
Computing Technology ◽  
Matrix Problem ◽  
Web Based ◽  
Stay Behind

Most eminent computing technology related to the cloud is an exclusively web-based approach where resources are hosted on a cloud; it prospers the resources. Cloud computing is the most promising technologies that offer a standard for bulky sized computing. That is a structure for enabling applications to execution on virtualized resources and accessed by a network protocol. It provides resource and services in a very elastic behavior that can be scaled according to the required of the clients. Limited numbers of devices execute less number of tasks at that time. So it is more complex to perform each task at once. Several devices execute each task, so it has required balancing total loads that reduce the completion time and executes each task in a definite way. We have said earlier that there are not feasible to stay behind an equal server to execute similar tasks. The tasks that are to be executed by machine in the cloud system must be less than the united VM for a time. Overloaded servers have to perform a less number of jobs. Here in our approach, we want to show a scheduling algorithm for balancing of loads and presentation with minimum execution time and makespan.

Efficient task scheduling on virtual machine in cloud computing environment

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mahfooz Alam ◽  
Mahak ◽  
Raza Abbas Haidri ◽  
Dileep Kumar Yadav
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Response Time ◽  
Virtual Machine ◽  
Task Allocation ◽  
Completion Time ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Content Type ◽  
Minimum Completion Time

Purpose Cloud users can access services at anytime from anywhere in the world. On average, Google now processes more than 40,000 searches every second, which is approximately 3.5 billion searches per day. The diverse and vast amounts of data are generated with the development of next-generation information technologies such as cryptocurrency, internet of things and big data. To execute such applications, it is needed to design an efficient scheduling algorithm that considers the quality of service parameters like utilization, makespan and response time. Therefore, this paper aims to propose a novel Efficient Static Task Allocation (ESTA) algorithm, which optimizes average utilization. Design/methodology/approach Cloud computing provides resources such as virtual machine, network, storage, etc. over the internet. Cloud computing follows the pay-per-use billing model. To achieve efficient task allocation, scheduling algorithm problems should be interacted and tackled through efficient task distribution on the resources. The methodology of ESTA algorithm is based on minimum completion time approach. ESTA intelligently maps the batch of independent tasks (cloudlets) on heterogeneous virtual machines and optimizes their utilization in infrastructure as a service cloud computing. Findings To evaluate the performance of ESTA, the simulation study is compared with Min-Min, load balancing strategy with migration cost, Longest job in the fastest resource-shortest job in the fastest resource, sufferage, minimum completion time (MCT), minimum execution time and opportunistic load balancing on account of makespan, utilization and response time. Originality/value The simulation result reveals that the ESTA algorithm consistently superior performs under varying of batch independent of cloudlets and the number of virtual machines’ test conditions.

scholarly journals Load Balancing Technique with an Efficient Method

2019 ◽  
Vol 8 (6) ◽  
pp. 1257-1262
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Efficient Method ◽  
Load Balance ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Quality Of Services ◽  
Huge Number ◽  
Task Scheduling Algorithm

There are a huge number of nodes connected to web computing to offer various types of web services to provide cloud clients. Limited numbers of nodes connected to cloud computing have to execute more than a thousand or a million tasks at the same time. So it is not so simple to execute all tasks at the same particular time. Some nodes execute all tasks, so there is a need to balance all the tasks or loads at a time. Load balance minimizes the completion time and executes all the tasks in a particular way.There is no possibility to keep an equal number of servers in cloud computing to execute an equal number of tasks. Tasks that are to be performed in cloud computing would be more than the connected servers. Limited servers have to perform a great number of tasks.We propose a task scheduling algorithm where few nodes perform the jobs, where jobs are more than the nodes and balance all loads to the available nodes to make the best use of the quality of services with load balancing.

An Adaptive Load Balancing Method of Adjustment Based on Cloud Computing Resources

2013 ◽  
Vol 385-386 ◽  
pp. 1708-1712
Author(s):  
Xiao Ping Jiang ◽  
Teng Jiang ◽  
Tao Zhang ◽  
Cheng Hua Li
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Large Scale ◽  
Scheduling Algorithm ◽  
Utilization Rate ◽  
Computing Technology ◽  
Service Platform ◽  
Technology System ◽  
Cluster Architecture ◽  
Cloud Computing Service

By combining LVS cluster architecture and could computing technology, system architecture of the cloud computing service platform is proposed. Cloud computing technology is suitable to support large-scale applications with flash crowds by support elastic amounts of bandwidth and storage resource etc. But traditional algorithms of load balancing provided by LVS are unsuitable for the proposed service platform, because these algorithms are designed for static server resource provided by traditional cluster technology. Taking both the overall utilization rate of server resources and the active connections of the server into counter, an adaptive adjustable load balancing algorithms (Least Comprehensive Utilization and Connection Scheduling algorithm, called LUCU) is proposed in this paper. According the utilization of cloud resource and the users demand, automatic switching between Round Robin (RR) algorithm and LUCU algorithm is achieved. When the cloud capacities are not able to meet the instantaneous demands, LUCU is chosen instead of RR. The proposed platform and algorithm are verified and evaluated using large-scare simulation experiments. The test results show that the equilibrium load is nearly achieved by adopting the proposed algorithms.

scholarly journals Rancang Bangun Server HAproxy Load Balancing Master to Master MySQL (Replication) Berbasis Cloud Computing

2020 ◽  
Vol 4 (1) ◽  
pp. 45
Author(s):  
Eka Pandu Cynthia ◽  
Iwan Iskandar ◽  
Anwar Alfaruqi Sipayung
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Database Management ◽  
Scheduling Algorithm ◽  
Rapid Development ◽  
Single Server ◽  
Computing Technology ◽  
High Increase ◽  
Network Load ◽  
Existing Data

<em>At present, the development of cloud computing technology is experiencing rapid development. Also in line with the increase in the need and use of cloud computing technology itself. This rapid and high increase can cause an increase in load for the existing server so that it can result in overload on the connection path traffic. To avoid and optimize management on the server, it is necessary to share network load using various solutions available in the load balancing method. One solution is to use HAProxy software. HAProxy bridges at least 2 servers to apply load balancing and use the Round Robin scheduling algorithm. In the database management of two servers, replication Master to Master can be used by using MySQL as an existing database management media. From the results of tests conducted in this study, the HAProxy server is considered capable of handling problems compared to a single server. A replication that was tested was also considered to be a solution to bridge changes in existing data on the HAProxy server.</em>

Cloud Computing in Three Phase Scheduling Algorithm Based on Service Quality

2014 ◽  
Vol 687-691 ◽  
pp. 2862-2866
Author(s):  
Yong Long Zhuang ◽  
Xiao Lan Weng ◽  
Xiang He Wei
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Service Quality ◽  
Network Topology ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Hierarchical Network ◽  
Three Phase ◽  
Simulation Results ◽  
Minimum Completion Time

Assurance issues for cloud computing’s service quality; propose a hierarchical network topology on the basis of the three-stage scheduling algorithm. The algorithm ensures that each work to be performed can be assigned to the appropriate resources, and can effectively improve the load of each node and reduce the waste of resources. FCFS, SJF, OLB and Min-Min (MM) scheduling algorithm’s simulation results show that the algorithm can not only make the work get the minimum completion time, but also the service node operation achieve the load balancing.

scholarly journals Cloud Computing based on the Load Balancing Algorithm

2018 ◽  
Vol 7 (4.7) ◽  
pp. 131
Author(s):  
NV Abhinav Chand ◽  
A Hemanth Kumar ◽  
Surya Teja Marella
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
User Satisfaction ◽  
Easy Access ◽  
Future Research ◽  
Computing Technology ◽  
Main Challenge ◽  
Load Balancing Algorithm ◽  
And Performance ◽  
Time Resource

Emerging cloud computing technology is a big step in virtual computing. Cloud computing provides services to clients through the internet. Cloud computing enables easy access to resources distributed all over the world. Increase in the number of the population has further increased the challenge. The main challenge of cloud computing technology is to achieve efficient load balancing. Load balancing is a process of assigning load to available resources in such a way that it avoids overloading of resources. If load balancing is performed efficiently, it improves QoS metric including cost, throughput, response time, resource utilization and performance. Efficient load balancing techniques also provide better user satisfaction. Various load balancing algorithms are used in different scenarios for ensuring the same. In the current research, we will study different algorithms for load balancing and benefits and limitations caused to the system due to the algorithms. In this paper, we will compare static and dynamic load balancing algorithms for various measures of efficiency. These will be useful for future research in the concerned field. 

scholarly journals Capacity Preserve Assignment Scheduling Algorithm in context of Determination System for Cloud Computing

2019 ◽  
Vol 8 (2S8) ◽  
pp. 647-650
Keyword(s):  
Cloud Computing ◽  
Information Systems ◽  
Load Balancing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Processing Condition ◽  
Feedback Mechanism ◽  
Determination System

Booking figuring is reliably a fervently issue in appropriated processing condition. Remembering the true objective to take out system bottleneck and modify stack logically. A stack changing endeavor booking count in light of weighted self-assertive and input frameworks was proposed in this paperFrom the outset the picked cloud masterminding host picked assets by necessities and made static estimation, and some time later coordinated them; other than the tally picked assets from which composed by weight self-confidently; by then it got standing out powerful data from effect burden to channel and sort the left. Finally it accomplished oneself adaptively to structure stack through information systems. The examination demonstrates that the calculation has stayed away from the framework bottleneck adequately and has accomplished adjusted burden and furthermore self-flexibility to it.keywords: Task Scheduling; Feedback Mechanism; Cloud Computing; Load Balancing

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