An optimized approach to video traffic splitting in heterogeneous wireless networks with energy and QoE considerations

The IEEE 1918.1 “Tactile Internet” Standards Working Group and its Standards

“…In terms of scalability, the proposed architecture can support more than two tactile edges communicating among each other over a common network domain as part of a given TI use case. In addition, two tactile edges can communicate with each other over multiple network domains simultaneously which can significantly enhance reliability due to redundancy and reduce latency due to traffic splitting [49]. This is reflected in Fig.…”

A survey on QoE-oriented wireless resources scheduling

“…Morel and Randriamasy (2017) devised a QoE-based scheduling algorithm that aims at enhancing the video delivery over heterogeneous mobile networks, namely by limiting the inter-cell interference experienced by some users. The work presented in (Abbas et al, 2017) addresses the real-time traffic splitting across cellular and WiFi heterogeneous networks (focusing on video streaming applications) and provides a solution for resource allocation that enhances QoE while reducing delay and energy consumption (namely of mobile terminals). In (Zhu et al, 2015a), a QoE-driven allocation technique is proposed for video streaming through Device-to-Device (D2D) transmissions, where the wireless resource scheduling goal is to enhance the time-averaged quality of video streams trans-mitted over D2D communications, while constraining the number of stall events for each stream.…”

“…Uplink (Essaili et al, 2011;Wu et al, 2012;Condoluci et al, 2017;Liu et al, 2018;Ranjan et al, 2018) Multi-cell (Zheng et al, 2014;Cho et al, 2015;Kim et al, 2015;Miller et al, 2015) Heterogeneous networks (Toseef et al, 2011;Jailton et al, 2013;Seyedebrahimi and Peng, 2015;Morel and Randriamasy, 2017;Abbas et al, 2017) Device-to-device communications (Zhu et al, 2015a;Hong et al, 2017;Biswash and Jayakody, 2018) Vehicular networks (Xu et al, 2013;Yaacoub et al, 2015;Ding et al, 2018) Cognitive radio networks (Jiang et al, 2012;Wu et al, 2013;He et al, 2016;Zhang et al, 2017;Piran et al, 2017;Lin et al, 2017) Relay networks (Reis et al, 2010;Wu et al, 2013;Bethanabhotla et al, 2016;Xiang et al, 2017;Fan and Zhao, 2018) Multi-user MIMO networks (Cao et al, 2012;Bethanabhotla et al, 2016;Chen et al, 2017;Huang and Zhang, 2018) Base stations energy consumption (Ma et al, 2012;Li et al, 2012;Gabale and Subramanian, 2014;Draxler et al, 2014;Sapountzis et al, 2014;…”

SDN-assisted efficient LTE-WiFi aggregation in next generation IoT networks

“…[19,20] discussed the traffic portion split and the resource scheduling in heterogeneous environment in link aggregation by developing a low complexity solution for maximizing an α-optimal network utility. In [21], authors addressed the resource management issue using Lyapunov drift plus penalty optimization approach to capture queue backlog stability. This approach considers delay, power and Quality of Experience (QoE) as primary parameters to split the traffic.…”