Research on Nginx Dynamic Load Balancing Algorithm

Qin, E; Wang, Yuanli; Yuan, Liping; Zhong, Yiwen

doi:10.1109/icmtma50254.2020.00138

Cited by 13 publications

(3 citation statements)

References 4 publications

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“…Web server Nginx adalah salah satu software web server yang memiliki kelebihan yaitu open source, ringan dan berkinerja tinggi sebagai HTTP dan reverse proxy. Dengan menggunakan sumber daya sistem yang efisien, Nginx dapat menyediakan konten statis dengan cepat dan dapat menyebarkan konten HTTP secara dinamis di jaringan [8] [9]. Selain itu dengan mengubah profilnya, Nginx dapat mengirimkan permintaan untuk menghubungkan server yang paling mampu pada node cluster yang digunakan [10].…”

Section: A Pendahuluanunclassified

Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx

Baeturohman,

Banu Santoso

2024

ijcs

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Semakin meningkatnya pengunjung website mengakibatkan web server menjadi sibuk merespons permintaan klien. Untuk mengatasi masalah kelebihan beban, penggunaan load balancing menjadi solusi yang efektif. Nginx merupakan aplikasi web server memiliki keunggulan sebagai perangkat lunak sumber terbuka, ringan, dan berkinerja tinggi sebagai HTTP dan reverse proxy. Dalam konteks ini, algoritma penjadwalan menjadi penting untuk menyeimbangkan beban Algoritma penjadwalan seperti Weighted Round Robin (WRR) dan Weighted Least Connection (WLC) menjadi pilihan yang relevan. Pengujian dilakukan dengan mengirimkan 1000, 2000, dan 5000 permintaan dengan bobot server 10:15:20, analisis throughput menunjukkan bahwa algoritma WLC lebih unggul daripada algoritma WRR. WLC mencapai waktu throughput terbaik dengan nilai 108.988 Kbits/sec. Parameter respon time menunjukkan bahwa algoritma WRR memiliki kinerja lebih baik, dengan waktu rata-rata respon sebesar 2.761ms. Untuk parameter packet loss, algoritma WRR juga menunjukkan hasil yang lebih baik, dengan rata-rata nilai packet loss sebesar 56%.

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Section: A Pendahuluanunclassified

Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx

Baeturohman,

Banu Santoso

2024

ijcs

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“…A variety of services and resources are adaptable in live production environments therefore CSP cannot rely upon this circumstance. On existing information, while considering analytics in real time, the clients' criteria are provided for adaptability and flexibility [10][11][12].…”

Section: Dynamic Lb Algorithmmentioning

confidence: 99%

Load Balancing in Cloud Environment: A State-of-the-Art Review

Lohumi,

Gangodkar,

Srivastava

et al. 2023

IEEE Access

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IT services and resources on-demand through Internetwork are offered by Cloud Computing (CC), including the pay-for-you-go aspect. A lot is offered by the CC paradigm, such as Infrastructure related services, computing services, storage, and environments for deployment are also provided. The objective of this study is to survey one of the significant challenges in cloud computing, which is a multi-variant, multi-constraint issue termed Load unbalancing, resulting in the demising of the scalability, efficiency, and performance of the system. Equilibrium in the server workload distribution is still strived for by cloud service providers. The unbalancing issue is resolved by load balancing solutions in two ways: overloading and underloading. An extensive structural literature analysis of Load balancing and its constituent domains with the inclusion of various parameters, such as scalability, make-span, and throughput, are depicted in this research paper to enhance the QoS. A detailed and organized taxonomy of all the Load balancing algorithms based on nature system state, techniques, functionality, and types is also presented. The major focus of the survey is around the Static, dynamic, hybrid, and nature-inspired Load-Balancing algorithms.

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“…Each server is connected via a 1 Gbps internet connection to ensure fast upload and download speeds. In SWADESH, NGINX has been used to handle load balancing to reduce the load on a single server and to improve system performance (60). NGINX is presently using the round-robin algorithm for performing load balancing on the client requests (61).…”

Section: Back-endmentioning

confidence: 99%

SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform

Mandal,

Jindal,

Roy

et al. 2023

Front. Neurol.

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Multimodal neuroimaging data of various brain disorders provides valuable information to understand brain function in health and disease. Various neuroimaging-based databases have been developed that mainly consist of volumetric magnetic resonance imaging (MRI) data. We present the comprehensive web-based neuroimaging platform “SWADESH” for hosting multi-disease, multimodal neuroimaging, and neuropsychological data along with analytical pipelines. This novel initiative includes neurochemical and magnetic susceptibility data for healthy and diseased conditions, acquired using MR spectroscopy (MRS) and quantitative susceptibility mapping (QSM) respectively. The SWADESH architecture also provides a neuroimaging database which includes MRI, MRS, functional MRI (fMRI), diffusion weighted imaging (DWI), QSM, neuropsychological data and associated data analysis pipelines. Our final objective is to provide a master database of major brain disease states (neurodegenerative, neuropsychiatric, neurodevelopmental, and others) and to identify characteristic features and biomarkers associated with such disorders.

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Research on Nginx Dynamic Load Balancing Algorithm

Cited by 13 publications

References 4 publications

Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx

Analisis Kinerja Algoritme WRR dengan WLC pada Load Balancing Nginx

Load Balancing in Cloud Environment: A State-of-the-Art Review

SWADESH: a multimodal multi-disease brain imaging and neuropsychological database and data analytics platform

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