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>

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 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.

scholarly journals ANALISIS PENINGKATAN KINERJA FTP SERVER MENGGUNAKAN LOAD BALANCING PADA CONTAINER

2019 ◽  
Vol 9 (3) ◽  
pp. 8-18
Author(s):  
Januar Al Amien ◽  
Doni Winarso
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Round Robin ◽  
Single Server ◽  
Test Results ◽  
File Transfer Protocol ◽  
Computing Technology ◽  
File Transfer ◽  
Use Of Resources ◽  
Transfer Protocol

Abstract Cloud computing is a technology that answers the challenge of the need for efficient computing technology. There are many things that can be implemented using cloud computing technologies such as web services, storage services, applications and others. Use of cloud computing using container technology can help in the management of applications and optimize the use of resources in the form of memory and processor usage on the server. In this research docker containers implemented by service of FTP (File Transfer Protocol). The FTP service is made into 3 containers within a single server computer. To handle load problems performance on the FTP server against overload requests, load balancing is used. Load balancing is a method to improve performance while reducing the performance load on FTP servers. Based on the test results, the use of multi container and load balancing in the FTP server in load with two algorithm least connection and raound robin handling has result of smaller memory usage and utilization of processor usage evenly. Both algorithms are recommended for handling loads for FTP servers and will be more efficient when applied to servers with the same specifications and loads Keywords: Cloud Computing, Docker, FTP, Load Balancing, HAProxy, Least Connection, Round Robin. Abstrak Cloud computing merupakan teknologi yang menjawab tantangan akan kebutuhan teknologi komputasi yang efisien. Terdapat banyak hal yang dapat diimplementasikan menggunakan teknologi cloud computing seperti web service, layanan penyimpanan, aplikasi dan lain-lain. Penerapan cloud computing dengan menggunakan teknologi container dapat membantu dalam pengelolaan aplikasi serta mengoptimalkan penggunaan sumber daya berupa penggunaan memory dan prosesor pada server. Dalam penelitian ini penerapan docker container diimplementasikan menggunakan layanan aplikasi FTP (File Transfer Protocol). Layanan  FTP dibuat menjadi 3 container didalam satu computer server. Untuk menangani permasalahan beban kinerja pada FTP server terhadap permintaan yang terlalu berat (overload) digunakan load balancing. Load balancing merupakan metode untuk meningkatkan kinerja sekaligus mengurangi beban kinerja pada FTP server. Berdasarkan hasil pengujian, penerapan multi container serta load balancing didalam FTP server dalam penanganan beban dengan dua algortima least connection dan round robin memiliki hasil penggunaan memory yang lebih kecil dan pemanfaatan penggunaan prosesor yang merata kedua algoritma tersebut direkomendasikan untuk penanganan beban untuk ftp server dan akan lebih efisien apabila diterapkan pada server dengan spesifikasi dan beban yang sama. Kata Kunci: Cloud Computing, Docker, FTP, Load Balancing, HAProxy, Least Connection, Round Robin .

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

scholarly journals Design and Implementation of A New-type Cloud Computing Examination System

2015 ◽  
Vol 10 (4) ◽  
pp. 28
Author(s):  
Xuedong Zhang ◽  
Shuqin Kang ◽  
Miaole Hou ◽  
Xianglei Liu
Keyword(s):  
Cloud Computing ◽  
Lower Cost ◽  
Rapid Development ◽  
Support Service ◽  
Design Development ◽  
Examination System ◽  
Computing Technology ◽  
New Type ◽  
Analysis System ◽  
Shared Network

With the rapid development of network technology, large enterprises have established their own online learning and examination system respectively. However, as those network examination systems are dispersive, closed and disconnected, so various resources are unable to be utilized in a balanced way, which may cause substantial waste of enterprise resources. To solve such a problem, the emerging cloud computing technology with the characteristics of service on demand and dynamic expansion capability, provides a possibility of a shared network examination system with lower cost, named as cloud exam support service. A feasible solution for the application of the cloud computing technology in the network examination, which combines the theoretical analysis, system design and technical implementation, is put forward in this paper. The design, development, and pilot application of the cloud examination system described in this paper show that this study is highly practical, operable, and worthy of application and popularization.

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.

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