285 citations · 475 across the 15 of their papers we have counts for
15 papers
Practice of Alibaba Cloud on Elastic Resource Provisioning for Large-scale Microservices Cluster
Minxian Xu, Lei Yang, Yang Wang +6
Cloud-native architecture is becoming increasingly crucial for today's cloud computing environments due to the need for speed and flexibility in developing applications. It utilize…
APBench: A Unified Benchmark for Availability Poisoning Attacks and Defenses
Tianrui Qin, Xitong Gao, Juanjuan Zhao +2
The efficacy of availability poisoning, a method of poisoning data by injecting imperceptible perturbations to prevent its use in model training, has been a hot subject of investig…
Resource Management for GPT-based Model Deployed on Clouds: Challenges, Solutions, and Future Directions
Yongkang Dang, Minxian Xu, Kejiang Ye
The widespread adoption of the large language model (LLM), e.g. Generative Pre-trained Transformer (GPT), deployed on cloud computing environment (e.g. Azure) has led to a huge inc…
Learning the Unlearnable: Adversarial Augmentations Suppress Unlearnable Example Attacks
Tianrui Qin, Xitong Gao, Juanjuan Zhao +2
Unlearnable example attacks are data poisoning techniques that can be used to safeguard public data against unauthorized use for training deep learning models. These methods add st…
Heterogeneous Domain Adaptation for IoT Intrusion Detection: A Geometric Graph Alignment Approach
Jiashu Wu, Hao Dai, Yang Wang +2
Data scarcity hinders the usability of data-dependent algorithms when tackling IoT intrusion detection (IID). To address this, we utilise the data rich network intrusion detection…
Flareon: Stealthy any2any Backdoor Injection via Poisoned Augmentation
Tianrui Qin, Xianghuan He, Xitong Gao +3
Open software supply chain attacks, once successful, can exact heavy costs in mission-critical applications. As open-source ecosystems for deep learning flourish and become increas…
Edge-Assisted V2X Motion Planning and Power Control Under Channel Uncertainty
Zongze Li, Shuai Wang, Shiyao Zhang +4
Edge-assisted vehicle-to-everything (V2X) motion planning is an emerging paradigm to achieve safe and efficient autonomous driving, since it leverages the global position informati…
Joint Semantic Transfer Network for IoT Intrusion Detection
Jiashu Wu, Yang Wang, Binhui Xie +4
In this paper, we propose a Joint Semantic Transfer Network (JSTN) towards effective intrusion detection for large-scale scarcely labelled IoT domain. As a multi-source heterogeneo…
Towards Fast Theta-join: A Prefiltering and Amalgamated Partitioning Approach
Jiashu Wu, Yang Wang, Xiaopeng Fan +2
As one of the most useful online processing techniques, the theta-join operation has been utilized by many applications to fully excavate the relationships between data streams in…
Multi-Point Integrated Sensing and Communication: Fusion Model and Functionality Selection
Guoliang Li, Shuai Wang, Kejiang Ye +3
Integrated sensing and communication (ISAC) represents a paradigm shift, where previously competing wireless transmissions are jointly designed to operate in harmony via the shared…
EsDNN: Deep Neural Network based Multivariate Workload Prediction Approach in Cloud Environment
Minxian Xu, Chenghao Song, Huaming Wu +3
Cloud computing has been regarded as a successful paradigm for IT industry by providing benefits for both service providers and customers. In spite of the advantages, cloud computi…
Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting
Jiexia Ye, Furong Zheng, Juanjuan Zhao +2
Accurate traffic state prediction is the foundation of transportation control and guidance. It is very challenging due to the complex spatiotemporal dependencies in traffic data. E…
PDMA: Probabilistic Service Migration Approach for Delay-aware and Mobility-aware Mobile Edge Computing
Minxian Xu, Qiheng Zhou, Huaming Wu +3
As a key technology in the 5G era, Mobile Edge Computing (MEC) has developed rapidly in recent years. MEC aims to reduce the service delay of mobile users, while alleviating the pr…
How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey
Jiexia Ye, Juanjuan Zhao, Kejiang Ye +1
In recent years, various deep learning architectures have been proposed to solve complex challenges (e.g. spatial dependency, temporal dependency) in traffic domain, which have ach…
Multi-Graph Convolutional Network for Relationship-Driven Stock Movement Prediction
Jiexia Ye, Juanjuan Zhao, Kejiang Ye +1
Stock price movement prediction is commonly accepted as a very challenging task due to the volatile nature of financial markets. Previous works typically predict the stock price ma…