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RETRACTED ARTICLE: Maximizing quality of multimedia streaming services in heterogeneous wireless networks using optimal multi-server technique

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This article was retracted on 21 December 2022

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Abstract

User expectations pertaining to multimedia data is huge. Issues in streaming like slow start and buffering hinder the quality of received content. Many authors have addressed the buffering issues. Their solutions in order to avoid buffering focussed on reducing the received multimedia quality in an attempt to avoid buffering. In this proposed work, quality issues in multimedia streaming have been focussed upon in WLAN-4G networks. A modified cat swarm optimization algorithm for optimal server selection (MCSO-SS) has been proposed to maximize the multimedia quality in terms of quality of service (QoS) and quality of experience (QoE). The proposed technique has been tested in a heterogeneous wireless environment that includes WLAN and 4G cellular networks. Experimental results prove that our proposed MCSO-SS based streaming technique increases the received multimedia content quality compared to existing techniques in terms of QoS (delay, throughput, service failure rate), and QoE (PSNR, SSIM).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, 600119, India

    S. Duraimurugan

  2. Department of Information Technology, St. Joseph’s College of Engineering, OMR, Chennai, Tamil Nadu, 600119, India

    S. Duraimurugan

  3. Department of Computer Science and Engineering, Jeppiaar Engineering College, OMR, Chennai, Tamil Nadu, 600119, India

    P. Jesu Jayarin

Authors
  1. S. Duraimurugan
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  2. P. Jesu Jayarin
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Correspondence to S. Duraimurugan.

Additional information

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s10586-022-03938-z

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Duraimurugan, S., Jesu Jayarin, P. RETRACTED ARTICLE: Maximizing quality of multimedia streaming services in heterogeneous wireless networks using optimal multi-server technique. Cluster Comput 22 (Suppl 5), 12883–12895 (2019). https://doi.org/10.1007/s10586-018-1797-8

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  • DOI: https://doi.org/10.1007/s10586-018-1797-8

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