activity
20102024
most citedPhoenixCloud: Provisioning Resources for Heterogeneous Cloud Workloads

6 citations · 14 across the 10 of their papers we have counts for

collaborators

10 papers

cs.MA20242 cited

Matching-Driven Deep Reinforcement Learning for Energy-Efficient Transmission Parameter Allocation in Multi-Gateway LoRa Networks

Ziqi Lin, Xu Zhang, Shimin Gong +3

Long-range (LoRa) communication technology, distinguished by its low power consumption and long communication range, is widely used in the Internet of Things. Nevertheless, the LoR…

cs.LG2024

Multi-Time Scale Service Caching and Pricing in MEC Systems with Dynamic Program Popularity

Yiming Chen, Xingyuan Hu, Bo Gu +2

In mobile edge computing systems, base stations (BSs) equipped with edge servers can provide computing services to users to reduce their task execution time. However, there is alwa…

cs.IT2024

AoI-aware Sensing Scheduling and Trajectory Optimization for Multi-UAV-assisted Wireless Backscatter Networks

Yusi Long, Songhan Zhao, Shimin Gong +4

This paper considers multiple unmanned aerial vehicles (UAVs) to assist sensing data transmissions from the ground users (GUs) to a remote base station (BS). Each UAV collects sens…

cs.IT2024

Primary Rate Maximization in Movable Antennas Empowered Symbiotic Radio Communications

Bin Lyu, Hao Liu, Wenqing Hong +2

In this paper, we propose a movable antenna (MA) empowered scheme for symbiotic radio (SR) communication systems. Specifically, multiple antennas at the primary transmitter (PT) ca…

cs.AI20232 cited

Multiagent Reinforcement Learning with an Attention Mechanism for Improving Energy Efficiency in LoRa Networks

Xu Zhang, Ziqi Lin, Shimin Gong +2

Long Range (LoRa) wireless technology, characterized by low power consumption and a long communication range, is regarded as one of the enabling technologies for the Industrial Int…

cs.LG20231 cited

Federated Learning Robust to Byzantine Attacks: Achieving Zero Optimality Gap

Shiyuan Zuo, Rongfei Fan, Han Hu +2

In this paper, we propose a robust aggregation method for federated learning (FL) that can effectively tackle malicious Byzantine attacks. At each user, model parameter is firstly…