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Search Results (8)
  • Open Access

    ARTICLE

    Machine-Learning Based Packet Switching Method for Providing Stable High-Quality Video Streaming in Multi-Stream Transmission

    Yumin Jo1, Jongho Paik2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4153-4176, 2024, DOI:10.32604/cmc.2024.047046

    Abstract Broadcasting gateway equipment generally uses a method of simply switching to a spare input stream when a failure occurs in a main input stream. However, when the transmission environment is unstable, problems such as reduction in the lifespan of equipment due to frequent switching and interruption, delay, and stoppage of services may occur. Therefore, applying a machine learning (ML) method, which is possible to automatically judge and classify network-related service anomaly, and switch multi-input signals without dropping or changing signals by predicting or quickly determining the time of error occurrence for smooth stream switching when there are problems such as… More >

  • Open Access

    ARTICLE

    Adaptive Learning Video Streaming with QoE in Multi-Home Heterogeneous Networks

    S. Vijayashaarathi1,*, S. NithyaKalyani2

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 2881-2897, 2023, DOI:10.32604/csse.2023.036864

    Abstract In recent years, real-time video streaming has grown in popularity. The growing popularity of the Internet of Things (IoT) and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience (QoE) and performance objectives. Most researchers focused on Forward Error Correction (FEC) techniques when attempting to strike a balance between QoE and performance. However, as network capacity increases, the performance degrades, impacting the live visual experience. Recently, Deep Learning (DL) algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks. But these algorithms… More >

  • Open Access

    ARTICLE

    Machine Learning Based Classifiers for QoE Prediction Framework in Video Streaming over 5G Wireless Networks

    K. B. Ajeyprasaath, P. Vetrivelan*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1919-1939, 2023, DOI:10.32604/cmc.2023.036013

    Abstract Recently, the combination of video services and 5G networks have been gaining attention in the wireless communication realm. With the brisk advancement in 5G network usage and the massive popularity of three-dimensional video streaming, the quality of experience (QoE) of video in 5G systems has been receiving overwhelming significance from both customers and service provider ends. Therefore, effectively categorizing QoE-aware video streaming is imperative for achieving greater client satisfaction. This work makes the following contribution: First, a simulation platform based on NS-3 is introduced to analyze and improve the performance of video services. The simulation is formulated to offer real-time… More >

  • Open Access

    ARTICLE

    Machine Learning-based Stable P2P IPTV Overlay

    Muhammad Javid Iqbal1,2, Ihsan Ullah2,*, Muhammad Ali2, Atiq Ahmed2, Waheed Noor2, Abdul Basit2

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5381-5397, 2022, DOI:10.32604/cmc.2022.024116

    Abstract Live video streaming is one of the newly emerged services over the Internet that has attracted immense interest of the service providers. Since Internet was not designed for such services during its inception, such a service poses some serious challenges including cost and scalability. Peer-to-Peer (P2P) Internet Protocol Television (IPTV) is an application-level distributed paradigm to offer live video contents. In terms of ease of deployment, it has emerged as a serious alternative to client server, Content Delivery Network (CDN) and IP multicast solutions. Nevertheless, P2P approach has struggled to provide the desired streaming quality due to a number of… More >

  • Open Access

    ARTICLE

    Encoder-Decoder Based LSTM Model to Advance User QoE in 360-Degree Video

    Muhammad Usman Younus1,*, Rabia Shafi2, Ammar Rafiq3, Muhammad Rizwan Anjum4, Sharjeel Afridi5, Abdul Aleem Jamali6, Zulfiqar Ali Arain7

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2617-2631, 2022, DOI:10.32604/cmc.2022.022236

    Abstract The development of multimedia content has resulted in a massive increase in network traffic for video streaming. It demands such types of solutions that can be addressed to obtain the user's Quality-of-Experience (QoE). 360-degree videos have already taken up the user's behavior by storm. However, the users only focus on the part of 360-degree videos, known as a viewport. Despite the immense hype, 360-degree videos convey a loathsome side effect about viewport prediction, making viewers feel uncomfortable because user viewport needs to be pre-fetched in advance. Ideally, we can minimize the bandwidth consumption if we know what the user motion… More >

  • Open Access

    ARTICLE

    Adaptive Quality-of-Service Allocation Scheme for Improving Video Quality over a Wireless Network

    Raed Alsaqour1, Ammar Hadi2, Maha Abdelhaq3,*

    Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 675-692, 2022, DOI:10.32604/iasc.2022.020482

    Abstract The need to ensure the quality of video streaming transmitted over wireless networks is growing every day. Video streaming is typically used for applications that are sensitive to poor quality of service (QoS) due to insufficient bandwidth, packet loss, or delay. These challenges hurt video streaming quality since they affect throughput and packet delivery of the transmitted video. To achieve better video streaming quality, throughput must be high, with minimal packet delay and loss ratios. A current study, however, found that the adoption of the adaptive multiple TCP connections (AM-TCP), as a transport layer protocol, improves the quality of video… More >

  • Open Access

    ARTICLE

    Efficient Computation Offloading in Mobile Cloud Computing for Video Streaming Over 5G

    Bokyun Jo1, Md. Jalil Piran2,*, Daeho Lee3, Doug Young Suh4,*

    CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 439-463, 2019, DOI:10.32604/cmc.2019.08194

    Abstract In this paper, we investigate video quality enhancement using computation offloading to the mobile cloud computing (MCC) environment. Our objective is to reduce the computational complexity required to covert a low-resolution video to high-resolution video while minimizing computation at the mobile client and additional communication costs. To do so, we propose an energy-efficient computation offloading framework for video streaming services in a MCC over the fifth generation (5G) cellular networks. In the proposed framework, the mobile client offloads the computational burden for the video enhancement to the cloud, which renders the side information needed to enhance video without requiring much… More >

  • Open Access

    ARTICLE

    Secure Video Streaming with Lightweight Cipher PRESENT in an SDN Testbed

    Pengcheng Liu1, †, Xiaojun Wang1, †, S. R. Chaudhry1, Khalid Javeed2, Yue Ma3, *, Martin Collier1

    CMC-Computers, Materials & Continua, Vol.57, No.3, pp. 353-363, 2018, DOI:10.32604/cmc.2018.04142

    Abstract The combination of traditional processors and Field Programmable Gate Arrays (FPGA) is shaping the future networking platform for intensive computation in resource-constrained networks and devices. These networks present two key challenges of security and resource limitations. Lightweight ciphers are suitable to provide data security in such constrained environments. Implementing the lightweight PRESENT encryption algorithm in a reconfigurable platform (FPGAs) can offer secure communication service and flexibility. This paper presents hardware acceleration of security primitives in SDN using NETFPGA-10G. We implement an efficient design of the PRESENT algorithm for faster, smaller and lower power consumption hardware circuit using Verilog. We evaluate… More >

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