Strona: Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW Service / Zakład Systemów Złożonych

Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW Service

2021-11-18
, red.  Bartosz Kowal
Logo Energies

W ramach zadania nr 2 w projekcie Regionalne Centrum Doskonałości Automatyki i Robotyki, Informatyki, Elektrotechniki, Elektroniki oraz Telekomunikacji Politechniki Rzeszowskiej przeprowadzono prace naukowo-badawcze, których wyniki zostały opublikowane w czasopiśmie Energies (IF: 3.004, 140 pkt MNiSW): https://www.mdpi.com/1996-1073/14/22/7719

Dymora, P.; Mazurek, M.; Sudek, B. Comparative Analysis of Selected Open-Source Solutions for Traffic Balancing in Server Infrastructures Providing WWW Service. Energies 2021, 14, 7719. https://doi.org/10.3390/en14227719

Abstract
As the number of users increased over the years, pioneering technologies and solutions in given areas ceased to be sufficient even in terms of performance. Therefore, there was a need for their development or even redesign and redefinition. One of the issues that undoubtedly has a huge impact on the current shape of the global network and the way information is processed in it is the issue of traffic balancing, especially the one in the server infrastructure related to the WWW service, providing users with the possibility of efficient and reliable web browsing. The paper presents a comparative analysis of selected open-source solutions used for traffic balancing in server infrastructures providing WWW service based on selected criteria. The designed architecture of the test environment and the test results of selected tools implementing the traffic-balancing functionality are presented. Methodologies, test plans, and comparison criteria are proposed. A comparative analysis of results based on specific criteria was performed. The balance between network traffic optimization and load balancing distribution among servers is crucial for the development of energy-efficient data processing centers.

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