ICTACT Journal on Communication Technology

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User-Centric Adaptive Multimedia Streaming in Interactive Communication Networks Using Shannon-Fano Genetic Algorithm


Affiliations
1 Department of Information Technology, St. Joseph’s College of Engineering, India
2 Department of Computer Science and Engineering, P.A. College of Engineering and Technology, India
3 Department of Computer Science and Engineering - Artificial Intelligence and Machine Learning, Malla Reddy College of Engineering, India
4 Department of Electrical and Electronics Engineering, Mai Nefhi College of Engineering and Technology, Eritrea
     

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In today’s rapidly evolving digital landscape, interactive communication networks play a pivotal role in facilitating real-time interactions among users. One of the critical challenges in these networks is ensuring the seamless delivery of multimedia content that caters to the diverse needs and preferences of individual users. This research endeavors to address this challenge by introducing a novel approach, where it places user satisfaction at its core, leveraging adaptive streaming techniques to dynamically adjust multimedia content delivery. By considering parameters such as network conditions, device capabilities, and user preferences, it optimizes the streaming experience in real-time. A key innovation lies in the integration of Shannon-Fano coding principles and genetic algorithms. Shannon-Fano coding enhances data compression efficiency, reducing bandwidth consumption, while genetic algorithms fine-tune the adaptive streaming parameters for each user. Our experimentation and evaluations demonstrate the effectiveness of this approach, showcasing improved multimedia streaming quality, reduced latency, and efficient bandwidth utilization. The synergy of user-centricity, adaptive streaming, Shannon-Fano coding, and genetic algorithms presents a promising avenue for enhancing multimedia communication in interactive networks.

Keywords

User-Centric, Adaptive Multimedia Streaming, Interactive Communication Networks, Shannon-Fano Coding, Genetic Algorithm.
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  • User-Centric Adaptive Multimedia Streaming in Interactive Communication Networks Using Shannon-Fano Genetic Algorithm

Abstract Views: 144  |  PDF Views: 2

Authors

Logeshwari Dhavamani
Department of Information Technology, St. Joseph’s College of Engineering, India
A. Kaliappan
Department of Computer Science and Engineering, P.A. College of Engineering and Technology, India
M. Sakthivel
Department of Computer Science and Engineering - Artificial Intelligence and Machine Learning, Malla Reddy College of Engineering, India
V. Balaji
Department of Electrical and Electronics Engineering, Mai Nefhi College of Engineering and Technology, Eritrea

Abstract


In today’s rapidly evolving digital landscape, interactive communication networks play a pivotal role in facilitating real-time interactions among users. One of the critical challenges in these networks is ensuring the seamless delivery of multimedia content that caters to the diverse needs and preferences of individual users. This research endeavors to address this challenge by introducing a novel approach, where it places user satisfaction at its core, leveraging adaptive streaming techniques to dynamically adjust multimedia content delivery. By considering parameters such as network conditions, device capabilities, and user preferences, it optimizes the streaming experience in real-time. A key innovation lies in the integration of Shannon-Fano coding principles and genetic algorithms. Shannon-Fano coding enhances data compression efficiency, reducing bandwidth consumption, while genetic algorithms fine-tune the adaptive streaming parameters for each user. Our experimentation and evaluations demonstrate the effectiveness of this approach, showcasing improved multimedia streaming quality, reduced latency, and efficient bandwidth utilization. The synergy of user-centricity, adaptive streaming, Shannon-Fano coding, and genetic algorithms presents a promising avenue for enhancing multimedia communication in interactive networks.

Keywords


User-Centric, Adaptive Multimedia Streaming, Interactive Communication Networks, Shannon-Fano Coding, Genetic Algorithm.

References