Streaming Media Load Balancing with Improved Genetic Algorithm

Yang Zhang, Xing Yang, Yuan Xu, Yanlin He, Mingqing Zhang, Qunxiong Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The load balancing algorithm of streaming media server is facing unique challenges. Different from the traditional Web server, the streaming media server needs to consider the characteristics of real-time, bandwidth occupation and multimedia data transmission. Therefore, the traditional load balancing algorithm is not necessarily suitable for streaming media servers, and needs special design and research. Aiming at the network requests of streaming media server clusters, a multi-dimensional matrix evaluation method based on streaming media characteristics is proposed, the genetic algorithm is improved, and it is applied to the dynamic load balancing algorithm scheduling scenario, and analyzed and simulated. Experimental results show that the algorithm can effectively reduce the average execution time of all requests, speed up the average response time and improve throughput.

Original languageEnglish
Title of host publicationProceedings of the 36th Chinese Control and Decision Conference, CCDC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6251-6256
Number of pages6
ISBN (Electronic)9798350387780
DOIs
Publication statusPublished - 2024
Externally publishedYes
Event36th Chinese Control and Decision Conference, CCDC 2024 - Xi'an, China
Duration: 25 May 202427 May 2024

Publication series

NameProceedings of the 36th Chinese Control and Decision Conference, CCDC 2024

Conference

Conference36th Chinese Control and Decision Conference, CCDC 2024
Country/TerritoryChina
CityXi'an
Period25/05/2427/05/24

Keywords

  • cluster server
  • genetic algorithm
  • load balancing
  • streaming media

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