2 research outputs found
To Talk or to Work: Flexible Communication Compression for Energy Efficient Federated Learning over Heterogeneous Mobile Edge Devices
Recent advances in machine learning, wireless communication, and mobile
hardware technologies promisingly enable federated learning (FL) over massive
mobile edge devices, which opens new horizons for numerous intelligent mobile
applications. Despite the potential benefits, FL imposes huge communication and
computation burdens on participating devices due to periodical global
synchronization and continuous local training, raising great challenges to
battery constrained mobile devices. In this work, we target at improving the
energy efficiency of FL over mobile edge networks to accommodate heterogeneous
participating devices without sacrificing the learning performance. To this
end, we develop a convergence-guaranteed FL algorithm enabling flexible
communication compression. Guided by the derived convergence bound, we design a
compression control scheme to balance the energy consumption of local computing
(i.e., "working") and wireless communication (i.e., "talking") from the
long-term learning perspective. In particular, the compression parameters are
elaborately chosen for FL participants adapting to their computing and
communication environments. Extensive simulations are conducted using various
datasets to validate our theoretical analysis, and the results also demonstrate
the efficacy of the proposed scheme in energy saving.Comment: Accepted for publication in INFOCOM'2
Adaptive Bitrate Video Streaming for Wireless nodes: A Survey
In today's Internet, video is the most dominant application and in addition
to this, wireless networks such as WiFi, Cellular, and Bluetooth have become
ubiquitous. Hence, most of the Internet traffic is video over wireless nodes.
There is a plethora of research to improve video streaming to achieve high
Quality of Experience (QoE) over the Internet. Many of them focus on wireless
nodes. Recent measurement studies often show QoE of video suffers in many
wireless clients over the Internet. Recently, many research papers have
presented models and schemes to optimize the Adaptive BitRate (ABR) based video
streaming for wireless and mobile users. In this survey, we present a
comprehensive overview of recent work in the area of Internet video specially
designed for wireless network. Recent research has suggested that there are
some new challenges added by the connectivity of clients through wireless. Also
these challenges become more difficult to handle when these nodes are mobile.
This survey also discusses new potential areas of future research due to the
increasing scarcity of wireless spectrum