Federated Learning (FL) is a distributed optimization method in which multiple client nodes collaborate to train a machine learning model without sharing data with a central server …
A Mirzaeinnia, M Mirzaeinia, A Rezgui - arXiv preprint arXiv:2009.03715, 2020 - arxiv.org
Modern applications are highly sensitive to communication delays and throughput. This paper surveys major attempts on reducing latency and increasing the throughput. These …
R Nath - Deep Learning Technologies for the Sustainable …, 2023 - Springer
Abstract The Fourth Generation (4G) wireless communication network is widely implemented with standardized framework of operation and QoS constraints. Emergence of …
During congestion in LTE network, most of the algorithms succeed in either address the queue overflow problem or bufferbloat problem through implicit congestion control …
Cellular-based networks keep large buffers at base stations to smooth out the bursty data traffic, which has a negative impact on the user's Quality of Experience (QoE). With the boom …
Recently, low latency has become one of the most critical requirements in Wi-Fi networks (eg, for Internet access). Many factors and events such as bufferbloat, which unexpectedly …
Y Im, P Rahimzadeh, B Shouse, S Park… - Proceedings of the …, 2019 - dl.acm.org
Emerging applications like virtual reality (VR), augmented reality (AR), and 360-degree video aim to exploit the unprecedentedly low latencies promised by technologies like the …
JM Ppallan, S Singh… - ICC 2024-IEEE …, 2024 - ieeexplore.ieee.org
Operating in high-frequency bands such as mmWave and Terahertz poses challenges due to frequent variations in channel quality. These fluctuations impact the radio protocol stack …
K Liu, Z Zha, W Wan, V Aggarwal, B Fu… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Recent advances in high-speed mobile networks have revealed new bottlenecks in ubiquitous TCP protocol deployed in the Internet. In addition to differentiating non …