338 citations · 346 across the 6 of their papers we have counts for
9 papers
BESS Aided Reconfigurable Energy Supply using Deep Reinforcement Learning for 5G and Beyond
Hao Yuan, Guoming Tang, Deke Guo +4
The year of 2020 has witnessed the unprecedented development of 5G networks, along with the widespread deployment of 5G base stations (BSs). Nevertheless, the enormous energy consu…
FedNILM: Applying Federated Learning to NILM Applications at the Edge
Yu Zhang, Guoming Tang, Qianyi Huang +3
Non-intrusive load monitoring (NILM) helps disaggregate the household's main electricity consumption to energy usages of individual appliances, thus greatly cutting down the cost i…
More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring
Yu Zhang, Guoming Tang, Qianyi Huang +2
Non-intrusive load monitoring (NILM) is a well-known single-channel blind source separation problem that aims to decompose the household energy consumption into itemised energy usa…
PLVER: Joint Stable Allocation and Content Replication for Edge-assisted Live Video Delivery
Huan Wang, Guoming Tang, Kui Wu +1
The live streaming services have gained extreme popularity in recent years. Due to the spiky traffic patterns of live videos, utilizing the distributed edge servers to improve view…
Quantifying Low-Battery Anxiety of Mobile Users and Its Impacts on Video Watching Behavior
Guoming Tang, Kui Wu, Yangjing Wu +3
People nowadays are increasingly dependent on mobile phones for daily communication, study, and business. Along with this it incurs the low-battery anxiety (LBA). Although having b…
A Survey on Edge Computing Systems and Tools
Fang Liu, Guoming Tang, Youhuizi Li +3
Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provi…