https://publications.eai.eu/index.php/inis <p>EAI Endorsed Transactions on Industrial Networks and Intelligent Systems is open access, a peer-reviewed scholarly journal focused on ubiquitous computing, cloud computing, and cyber-physical system, all kinds of networks in large-scale factories, including a lot of traditional and new industries. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications with a quarterly frequency (four issues per year). This journal is co-organized, and managed by Duy Tan University, Vietnam.</p> <p><strong>INDEXING</strong>: Scopus (CiteScore: 3.1), Compendex, DOAJ, ProQuest, EBSCO, DBLP</p> European Alliance for Innovation (EAI) en-US EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 2410-0218 <p>This is an open-access article distributed under the terms of the Creative Commons Attribution <a href="https://creativecommons.org/licenses/by/3.0/" target="_blank" rel="noopener">CC BY 3.0</a> license, which permits unlimited use, distribution, and reproduction in any medium so long as the original work is properly cited.</p> https://publications.eai.eu/index.php/inis/article/view/8587 <p style="-qt-block-indent: 0; text-indent: 0px; margin: 0px;">The reduction of greenhouse gas emissions in the Internet and ICT sectors has become a critical challenge. According to recent research, the key contributors to greenhouse gas emissions in Internet include high energy consumption factors such as data centers, transmission network devices, and end-user devices. Among Internet services, video streaming is one of the services having the highest traffic volume and number of users. Consequently, developing energy-efficient solutions for video streaming networks, particularly for end-user devices, is an urgent research priority. Reducing energy consumption in end-user devices in a video streaming system often requires compromises in parameters that impact the quality of user experience (QoE). Therefore, achieving an optimal trade-off between minimizing energy consumption and maintaining an acceptable QoE is a key objective. In this study, a cost function that integrates QoE and energy consumption is developed using the Lagrange multiplier method. Based on this function, an adaptive bitrate algorithm is proposed to select optimal video segments for video players, ensuring maximum QoE while minimizing energy consumption. The performance of the proposed method is evaluated using various types of video samples under varying network bandwidth conditions. Experimental results show that the proposed method reduces energy consumption of end-user devices by up to 6.7% and enhances QoE by 20% compared to previous methods.</p> Tien Vu Huu Thao Nguyen Thi Huong Copyright (c) 2025 Tien Vu Huu, Thao Nguyen Thi Huong https://creativecommons.org/licenses/by-nc-sa/4.0 2025-04-14 2025-04-14 12 3 10.4108/eetinis.v12i3.8587 https://publications.eai.eu/index.php/inis/article/view/8604 <p class="ICST-abstracttext"><span lang="EN-GB">This article proposes a hybrid satellite-terrestrial relaying network (HSTRN) that integrates physical-layer security (PLS), Fountain codes (FCs), non-orthogonal multiple access (NOMA), and partial relay selection (PRS) to enhance system performance in terms of reliability, data rate, and security. In the proposed system, a satellite uses NOMA to simultaneously transmit Fountain packets to two clusters of terrestrial users. Data transmission is assisted by one of the terrestrial relay stations, selected by the PRS algorithm. We derive exact expressions for outage probability (OP) and system outage probability (SOP) at the legitimate users, as well as intercept probability (IP) and system intercept probability (SIP) at eavesdroppers. Monte Carlo simulations are realized to validate the accuracy of the analytical results, illustrate performance trends, and analyze the impact of key parameters on the considered performance.</span></p> Toan Van Nguyen Trung Duy Tran Ngoc Son Pham Viet Tuan Pham Lam Thanh Tu Copyright (c) 2025 Toan Van Nguyen, Trung Duy Tran, Ngoc Son Pham, Viet Tuan Pham, Lam Thanh Tu https://creativecommons.org/licenses/by-nc-sa/4.0 2025-04-11 2025-04-11 12 3 10.4108/eetinis.v12i3.8604