activity
20202026
most citedMatching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks

28 citations · 35 across the 18 of their papers we have counts for

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Showing 2022Show all

5 papers · 1 filter

cs.DC2022

Accelerating the Delivery of Data Services over Uncertain Mobile Crowdsensing Networks

Minghui Liwang, Zhipeng Cheng, Wei Gong +6

The challenge of exchanging and processing of big data over mobile crowdsensing (MCS) networks calls for designing seamless data service provisioning mechanisms to enable utilizati…

cs.LG2022★ 1 cited

Learning-Based Client Selection for Federated Learning Services Over Wireless Networks with Constrained Monetary Budgets

Zhipeng Cheng, Xuwei Fan, Minghui Liwang +2

We investigate a data quality-aware dynamic client selection problem for multiple federated learning (FL) services in a wireless network, where each client offers dynamic datasets…

cs.GT2022

Auction-Promoted Trading for Multiple Federated Learning Services in UAV-Aided Networks

Zhipeng Cheng, Minghui Liwang, Xiaoyu Xia +3

Federated learning (FL) represents a promising distributed machine learning paradigm that allows smart devices to collaboratively train a shared model via providing local data sets…

cs.DC2022★ 2 cited

Long-Term or Temporary? Hybrid Worker Recruitment for Mobile Crowd Sensing and Computing

Minghui Liwang, Zhibin Gao, Seyyedali Hosseinalipour +3

This paper investigates a novel hybrid worker recruitment problem where the mobile crowd sensing and computing (MCSC) platform employs workers to serve MCSC tasks with diverse qual…

cs.LG2022

Distributed Machine Learning in D2D-Enabled Heterogeneous Networks: Architectures, Performance, and Open Challenges

Zhipeng Cheng, Xuwei Fan, Minghui Liwang +3

The ever-growing concerns regarding data privacy have led to a paradigm shift in machine learning (ML) architectures from centralized to distributed approaches, giving rise to fede…