Yun Yang

CSEdge: Enabling Collaborative Edge Storage for Multi-Access Edge Computing Based on Blockchain

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 08-2022

DOI: 10.1109/TPDS.2021.3131680

Online User and Power Allocation in Dynamic NOMA-Based Mobile Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2022

DOI: 10.1109/TMC.2022.3193366

Multiple Cooperative Task Assignment on Reliability-Oriented Social Crowdsourcing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 11-2022

DOI: 10.1109/TSC.2021.3103636

Multiple Cooperative Task Allocation in Group-Oriented Social Mobile Crowdsensing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 11-2022

DOI: 10.1109/TSC.2021.3086097

EDIndex: Enabling Fast Data Queries in Edge Storage Systems

Publisher: ACM

Date: 18-07-2023

DOI: 10.1145/3539618.3591676

EdgeDis: Enabling Fast, Economical, and Reliable Data Dissemination for Mobile Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2023

DOI: 10.1109/TSC.2023.3328991

Formulating Criticality-Based Cost-Effective Fault Tolerance Strategies for Multi-Tenant Service-Based Systems

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 03-2018

DOI: 10.1109/TSE.2017.2681667

CoopEdge+: Enabling Decentralized, Secure and Cooperative Multi-Access Edge Computing Based on Blockchain

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 03-2023

DOI: 10.1109/TPDS.2022.3231296

Interference-Aware SaaS User Allocation Game for Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2022

DOI: 10.1109/TCC.2020.3008448

Special Issue on Service-Oriented Collaborative Computing and Applications

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 03-2018

DOI: 10.1109/TSC.2017.2764559

Energy-Aware Computation Management Strategy for Smart Logistic System With MEC

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 06-2022

DOI: 10.1109/JIOT.2021.3115346

Predicting temporal violations for parallel business cloud workflows

Publisher: Wiley

Date: 05-12-2018

DOI: 10.1002/SPE.2554

Cost-Effective User Allocation in 5G NOMA-Based Mobile Edge Computing Systems

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 12-2022

DOI: 10.1109/TMC.2021.3077470

Trading off Between User Coverage and Network Robustness for Edge Server Placement

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2022

DOI: 10.1109/TCC.2020.3008440

Inspecting Edge Data Integrity With Aggregate Signature in Distributed Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 10-2022

DOI: 10.1109/TCC.2021.3059448

Joint Coverage-Reliability for Budgeted Edge Application Deployment in Mobile Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 12-2022

DOI: 10.1109/TPDS.2022.3166163

Cost-Effective App User Allocation in an Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2022

DOI: 10.1109/TCC.2020.3001570

Efficient Verification of Edge Data Integrity in Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 11-2022

DOI: 10.1109/TSC.2021.3090173

FlexiFed: Personalized Federated Learning for Edge Clients with Heterogeneous Model Architectures

Publisher: ACM

Date: 30-04-2023

DOI: 10.1145/3543507.3583347

EESaver: Saving Energy Dynamically for Green Multi-Access Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2011

DOI: 10.1109/TPDS.2023.3277619

Runtime Verification of Business Cloud Workflow Temporal Conformance

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 03-2020

DOI: 10.1109/TSC.2019.2962666

EdgeMove: Pipelining Device-Edge Model Training for Mobile Intelligence

Publisher: ACM

Date: 30-04-2023

DOI: 10.1145/3543507.3583540

A Game-Theoretical Approach for Mitigating Edge DDoS Attack

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2022

DOI: 10.1109/TDSC.2021.3055559

Enhancing Fault Injection Testing of Service Systems via Fault-Tolerance Bottleneck

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2023

DOI: 10.1109/TSE.2023.3285357

FedEdge: Accelerating Edge-Assisted Federated Learning

Publisher: ACM

Date: 30-04-2023

DOI: 10.1145/3543507.3583264

Rate-Adaptive Fog Service Platform for Heterogeneous IoT Applications

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2020

DOI: 10.1109/JIOT.2019.2945328

Dynamic User Allocation in Stochastic Mobile Edge Computing Systems

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 09-2022

DOI: 10.1109/TSC.2021.3063148

An Agent-Based Integrated Self-Evolving Service Composition Approach in Networked Environments

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 11-2019

DOI: 10.1109/TSC.2016.2631598

TFormer: A Transmission-Friendly ViT Model for IoT Devices

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 02-2023

DOI: 10.1109/TPDS.2022.3222765

Cooperative Assurance of Cache Data Integrity for Mobile Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2021

DOI: 10.1109/TIFS.2021.3111747

Hypernetwork Dismantling via Deep Reinforcement Learning

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 09-2022

DOI: 10.1109/TNSE.2022.3174163

Diversified Third-Party Library Prediction for Mobile App Development

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2022

DOI: 10.1109/TSE.2020.2982154

A Novel Workflow-Level Data Placement Strategy for Data-Sharing Scientific Cloud Workflows

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 05-2019

DOI: 10.1109/TSC.2016.2625247

Revisiting Graph-based Recommender Systems from the Perspective of Variational Auto-Encoder

Publisher: Association for Computing Machinery (ACM)

Date: 07-02-2023

DOI: 10.1145/3573385

Abstract: Graph-based recommender system has attracted widespread attention and produced a series of research results. Because of the powerful high-order connection modeling capabilities of the Graph Neural Network, the performance of these graph-based recommender systems are far superior to those of traditional neural network-based collaborative filtering models. However, from both analytical and empirical perspectives, the apparent performance improvement is accompanied with a significant time overhead, which is noticeable in large-scale graph topologies. More importantly, the intrinsic data-sparsity problem substantially limits the performance of graph-based recommender systems, which compelled us to revisit graph-based recommendation from a novel perspective. In this article, we focus on analyzing the time complexity of graph-based recommender systems to make it more suitable for real large-scale application scenarios. We propose a novel end-to-end graph recommendation model called the Collaborative Variational Graph Auto-Encoder (CVGA), which uses the information propagation and aggregation paradigms to encode user–item collaborative relationships on the user–item interaction bipartite graph. These relationships are utilized to infer the probability distribution of user behavior for parameter estimation rather than learning user or item embeddings. By doing so, we reconstruct the whole user–item interaction graph according to the known probability distribution in a feasible and elegant manner. From the perspective of the graph auto-encoder, we convert the graph recommendation task into a graph generation problem and are able to do it with approximately linear time complexity. Extensive experiments on four real-world benchmark datasets demonstrate that CVGA can be trained at a faster speed while maintaining comparable performance over state-of-the-art baselines for graph-based recommendation tasks. Further analysis shows that CVGA can effectively mitigate the data sparsity problem and performs equally well on large-scale datasets.

Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2022

DOI: 10.1109/TCC.2019.2947678

An Algorithm for Finding the Minimum Cost of Storing and Regenerating Datasets in Multiple Clouds

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 04-2018

DOI: 10.1109/TCC.2015.2491920

OL-EUA: Online User Allocation for NOMA-Based Mobile Edge Computing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 04-2023

DOI: 10.1109/TMC.2021.3112941

Trading off Between Multi-Tenancy and Interference: A Service User Allocation Game

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 07-2022

DOI: 10.1109/TSC.2020.3028760

Auditing Cache Data Integrity in the Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 05-2021

DOI: 10.1109/TPDS.2020.3043755

Optimizing Graph Neural Network With Multiaspect Hilbert-Schmidt Independence Criterion

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 2022

DOI: 10.1109/TNNLS.2022.3171419

READ: Robustness-Oriented Edge Application Deployment in Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 05-2022

DOI: 10.1109/TSC.2020.3015316

PipeEdge: A Trusted Pipelining Collaborative Edge Training based on Blockchain

Publisher: ACM

Date: 30-04-2023

DOI: 10.1145/3543507.3583413

Covering-Based Web Service Quality Prediction via Neighborhood-Aware Matrix Factorization

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 09-2021

DOI: 10.1109/TSC.2019.2891517

A Game-Theoretical Approach for User Allocation in Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 03-2020

DOI: 10.1109/TPDS.2019.2938944

Transferable graph neural networks with deep alignment attention

Publisher: Elsevier BV

Date: 09-2023

DOI: 10.1016/J.INS.2023.119232

Joint Shareability and Interference for Multiple Edge Application Deployment in Mobile-Edge Computing Environment

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Date: 02-2022

DOI: 10.1109/JIOT.2021.3088493

Swinburne University Of Technology

Location: Australia

View Organisation

Linkage Projects - Grant ID: LP110100228

Start Date: 2011

End Date: 12-2013

Amount: $400,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP150101775

Start Date: 2015

End Date: 12-2017

Amount: $295,900.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP0669660

Start Date: 03-2007

End Date: 12-2011

Amount: $235,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP210301393

Start Date: 03-2023

End Date: 02-2026

Amount: $241,960.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP0990393

Start Date: 07-2010

End Date: 06-2014

Amount: $380,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP220100482

Start Date: 2023

End Date: 12-2025

Amount: $492,651.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP200102491

Start Date: 04-2021

End Date: 03-2025

Amount: $360,000.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP130100324

Start Date: 07-2013

End Date: 10-2017

Amount: $360,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP230101790

Start Date: 2023

End Date: 12-2025

Amount: $405,610.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP180100212

Start Date: 2018

End Date: 12-2022

Amount: $362,734.00

Funder: Australian Research Council

Linkage Projects - Grant ID: LP0562500

Start Date: 11-2005

End Date: 11-2008

Amount: $207,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP0663841

Start Date: 2006

End Date: 12-2009

Amount: $233,680.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP160102412

Start Date: 2016

End Date: 12-2019

Amount: $311,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP110101340

Start Date: 2011

End Date: 12-2014

Amount: $360,000.00

Funder: Australian Research Council