web server cluster
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<p class="Abstrak">Untuk mewujudkan ketahanan pangan, diperlukan mekanisme pengumpulan data secara real-time dari produsen  bahan pangan, pendisitribusi bahan pangan sampai pengolah bahan pangan. Namun tidak semua organisasi yang berkecimpung dalam distribusi pangan memiliki infrastruktur sistem informasi yang cukup baik. Untuk mengatasi kendala infrastruktur, penelitian ini mengusulkan untuk membangun arsitektur <em>web server cluster</em> yang dapat menunjang kebutuhan <em>high availability</em> system menggunakan single board computer.  Komponen arsitektur terdiri dari dua tier yaitu: frontend dan backend. Untuk menjamin kehandalan sistem, arsitektur  yang diusulkan didukung dengan komponen <em>load balancing</em>, mekanisme failover dan replikasi database. Sistem telah diuji berasarkan kebutuhan fungsional dan kebutuhan non-fungsional yang sudah didefinisikan sesuai kebutuhan organisasi. Dari hasil pengujian, tingkat availabilitas yang dihasilkan sebesar 95.83%.</p><p class="Abstrak"> </p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="PreformattedText"><em>To achieve food security, a real-time data collection mechanism is needed from food producers, food distribution to food processing. However, not all organizations involved in food distribution have adequate information system infrastructure. To overcome infrastructure constraints, this study proposes to build a web server cluster architecture that can support the needs of a high availability system using a single board computer. The architectural component consists of two tiers, namely: frontend and backend. To ensure system reliability, the proposed architecture is supported by load balancing components, failover mechanisms, and database replication. The system has been tested based on functional requirements and non-functional requirements that have been defined according to organizational requirements. From the test results, the resulting availability level is 95.83%</em>.</p><p class="Abstrak"><em><br /></em></p>

With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster.

With the rapid development of big data and the national big data strategy is put forward, the Web server cluster facing more complex and severe challenges. The traditional load balancing algorithm has obvious limitations. This paper proposes a dynamic load-balancing model based on the SSAWF (Strong Suspend And Weak Forecast) mechanism. This model uses strong suspend mechanism and cubic exponential smoothing prediction method based on AHP algorithm for dynamic load balancing scheduling. Results of the experiments show that the improved model has more positive influence on read/ write performance of the cluster under abnormal system transient performance, high concurrency and high system load interaction, that's to say the load balancing effect is better than the traditional load balancing.