activity
20192023
most citedMatching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks

28 citations · 36 across the 5 of their papers we have counts for

collaborators

5 papers

cs.DC2023★ 28 cited

Matching-based Hybrid Service Trading for Task Assignment over Dynamic Mobile Crowdsensing Networks

Houyi Qi, Minghui Liwang, Seyyedali Hosseinalipour +4

By opportunistically engaging mobile users (workers), mobile crowdsensing (MCS) networks have emerged as important approach to facilitate sharing of sensed/gathered data of heterog…

cs.DC2022

A Survey on UAV-enabled Edge Computing: Resource Management Perspective

Xiaoyu Xia, Sheik Mohammad Mostakim Fattah, Muhammad Ali Babar

Edge computing facilitates low-latency services at the network's edge by distributing computation, communication, and storage resources within the geographic proximity of mobile an…

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★ 8 cited

Evaluation of Distributed Data Processing Frameworks in Hybrid Clouds

Faheem Ullah, Shagun Dhingra, Xiaoyu Xia +1

Distributed data processing frameworks (e.g., Hadoop, Spark, and Flink) are widely used to distribute data among computing nodes of a cloud. Recently, there have been increasing ef…

cs.DC2019

Edge User Allocation with Dynamic Quality of Service

Phu Lai, Qiang He, Guangming Cui +6

In edge computing, edge servers are placed in close proximity to end-users. App vendors can deploy their services on edge servers to reduce network latency experienced by their app…