Research and Application of Server Cluster Load Balancing Technology

Li, Bo; Shang, Jingtao; Dong, Mingming; He, Yongle

doi:10.1109/itnec48623.2020.9085082

Cited by 8 publications

(4 citation statements)

References 3 publications

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“…Load balancer yang diaplikasikan pada server terklaster disimpulkan memiliki response rate yang lebih rendah, sehingga pengguna dapat mengakses web lebih cepat. Hasil evaluasi Li ditunjukkan pada Tabel 1 bahwa semakin banyak koneksi yang terhubung bersamaan, server yang diklaster cenderung memiliki response time yang stabil [13]. Penelitian Akbar dan rekan mengombinasikan antara server load balancing dan juga link load balancing yang bertujuan mengurangi beban pada CPU server terdistribusi.…”

Section: Tinjauan Pustakaunclassified

Infrastruktur High-Available Learning Management System Universitas Menggunakan Least-Connected Load Balancer

Ramadhan¹,

Wulandari

2022

JMASIF

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IPB University berdiri sejak tahun 1963 sebagai salah satu perguruan tinggi ternama di Bogor. Pandemi membuat civitas akademik IPB University untuk melakukan kegiatan belajar mengajar jarak jauh. Namun, berjalannya Learning Management System (LMS) belum cukup untuk melayani ribuan pengguna tanpa kesalahan. High-availability menjadi desain lingkungan produksi esensial untuk meminimalisir kegagalan karena ada sistem lain yang dapat menggantikan sehingga proses produksi tidak terganggu. Untuk mewujudkan konsep high-availability pada LMS, diperlukan perencanaan skema sistem server yang matang. Penelitian ini mengimplementasikan konsep high-availability pada server LMS terdistribusi dengan menggunakan load balancing, web clustering, dan juga database clustering. Implementasi menggunakan serangkaian server basis data, server web, server NFS, server load balancing web, dan juga server load balancing basis data. Sistem terimplementasi telah diuji berdasarkan kebutuhan fungsional yang sesuai. Pengujian yang dilakukan ditinjau dari pengamatan terhadap waktu respon dan juga performa LMS. Hasil pengujian menunjukkan bahwa LMS telah mengaplikasikan konsep high-availability ketika terjadi suatu kesalahan pada salah satu server web. Pengujian juga menunjukkan bahwa kinerja server web telah seimbang menggunakan leastconnected load balancer. Ketika salah satu server web tidak dapat diakses, maka server web yang lain mengambil request client sehingga sistem tetap dapat berjalan.

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Section: Tinjauan Pustakaunclassified

Infrastruktur High-Available Learning Management System Universitas Menggunakan Least-Connected Load Balancer

Ramadhan¹,

Wulandari

2022

JMASIF

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“…If t ki > T k , it means that server S i is unable to complete the processing of task J k with the current load situation. The management server traverses all tasks and servers to obtain the edge set E. According to (1), the e ki in the edge set E is quantized to two values of 0 and 1, and the edge matrix E nn is obtained. From this, an edged bipartite graph can be obtained, representing which servers each task can be executed on, denoted as graph G 2 = (J, S, E), as shown in Figure 4.…”

Section: Algorithm Processmentioning

confidence: 99%

“…The program of management server and server cluster is written through the Java. There are task queues of a certain length in the task pool, and the complexity of each task obeys a uniform distribution in the interval (1,10). The task pool will send the task stream to the management server in real time.…”

Section: Simulationmentioning

confidence: 99%

“…For this reason, the industry mostly uses multiple servers to form a server cluster system. Multiple servers within the system work together to process parallel requests from users and provide services externally [1]. The server cluster system can quickly switch to the remaining servers for response and data backup when a single server crash [2].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Load Balancing Algorithm Based on Optimal Matching of Weighted Bipartite Graph

Hou

Meng

et al. 2022

IEEE Access

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When the server cluster is processing concurrent task requests, if the performance difference among servers is not fully considered, task allocation will be unreasonable, which will lead to an increase in task making span and a decrease in cluster resource utilization. As one of the core technologies of server cluster, load balancing is used to balance the load of each server by allocating tasks to each server through an algorithm before the task processing. Therefore, this paper proposes a dynamic load balancing algorithm based on optimal matching of weighted bipartite graph. First, we constructed a bipartite graph with servers and tasks as vertices. The management server collects the load indicators of each server in the cluster in real time, using the real-time processing rate of each server as the load indicator. Each edge of the bipartite graph is determined by comparing the expected completion time of the tasks with the load of each server. The degree of matching between each task amount and each server load capacity is defined as the weight matrix of the edges, and the bipartite graph is weighted to construct a weighted bipartite graph. The Kuhn-Munkres algorithm was used to solve the optimal matching of the weighted bipartite graph, and the optimal assignment of tasks to servers was achieved based on the result of the optimal matching. The proposed algorithm fully considers the differentiation of each task amount and each server load capacity. By building a server cluster example and conducting comparison experiments, it is demonstrated that the algorithm can achieve load balancing of the server cluster and improve the resource utilization efficiency of the cluster, while offsetting the extra time overhead caused by the algorithm.

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Evaluation Test and Improvement of Load Balancing Algorithms of Nginx

Chi

2022

IEEE Access

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Today most people can't live without electronic devices. And more and more new devices are coming to the market every day. Apps running on these devices often connect to one or several web-based server side applications, which in turn put a lot of load and management pressure on the servers and clusters serving these web applications. Technologies such as Nginx and Keepalived were invented to address the load issues faced by these high concurrency applications. This paper tested a server cluster environment based on Nginx and Keepalived, evaluated the performance of Nginx based algorithms such as WRR, IP_HASH and LEAST_CONN, and designed an optimized version of IP_HASH (named as NEW_HASH). Compared to the original IP_HASH, the NEW_HASH reduces the probability of hash collisions and improves the performance of searching back-end nodes. The test showed NEW_HASH outperforms the original method of IP_HASH, with reduced response time, lower failure rates and increased throughput. Overall, the server cluster performed better under the high load pressure using NEW_HASH.

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Research and Application of Server Cluster Load Balancing Technology

Cited by 8 publications

References 3 publications

Infrastruktur High-Available Learning Management System Universitas Menggunakan Least-Connected Load Balancer

Infrastruktur High-Available Learning Management System Universitas Menggunakan Least-Connected Load Balancer

Dynamic Load Balancing Algorithm Based on Optimal Matching of Weighted Bipartite Graph

Evaluation Test and Improvement of Load Balancing Algorithms of Nginx

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