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Project Description
Project Description
Mobile edge computing has emerged to address the long latency, low throughput, and unpredictability of cloud computing for serving modern mobile applications. Nevertheless, the lack of end-to-end performance guarantee in the form of service-level agreements (SLAs) can lead to performance degradation of critical applications during unexpected system dynamics, rendering these applications incompetent or unsafe to use. This project seeks to develop mathematical and systematic tools for edge providers to quantify and control, the risk associated with providing end-to-end SLAs for mobile applications. By designing multi-dimensional resource planning and orchestration algorithms that bound or minimize the risk associated with edge SLAs, this project aims to enable and enhance life-changing edge applications such as autonomous driving and mobile vision, promote investment and expedite development in mobile edge computing, and broaden awareness of risk management from a system perspective.
Project Personnel and Major Participants
Project Personnel and Major Participants
Graduate Students at ASU
Graduate Students at ASU
Xuanli Lin (PhD)
Yinxin Wan (PhD)
Graduate Students at NCSU
Graduate Students at NCSU
Zhouyu Li (PhD)
Fangtong Zhou (PhD)
Publications
Publications
Students receiving funding support from this project are marked with asterisk. PIs are underscored in the publications.
VeriEdge: Verifying and Enforcing Service Level Agreements for Pervasive Edge Computing
Xiaojian Wang, Ruozhou Yu, Dejun Yang, Huayue Gu, Zhouyu Li*,
I IEEE International Conference on Computer Communications (INFOCOM), 2024.INSPIRE: Instance-level Privacy-preserving Transformation for Vehicular Camera Videos [PDF] [Slides]
Zhouyu Li*, Ruozhou Yu, Anupam Das, Shaohu Zhang, Huayue Gu, Xiaojian Wang, Fangtong Zhou*, Aafaq Sabir, Dilawer Ahmed, Ahsan Zafar
In IEEE International Conference on Computer Communications and Networks (ICCCN), 2023.EA-Market: Empowering Real-Time Big Data Applications with Short-Term Edge SLA Leases [PDF] [Slides]
Ruozhou Yu, Huayue Gu, Xiaojian Wang, Fangtong Zhou*, Guoliang Xue, Dejun Yang
In IEEE International Conference on Computer Communications and Networks (ICCCN), 2023.Extracting Spatial Information of IoT Device Events for Smart Home Safety Monitoring
Yinxin Wan, Kuai Xu, Feng Wang, Guoliang Xue
In IEEE International Conference on Computer Communications (INFOCOM), 2023.IoT System Vulnerability Analysis and Network Hardening with Shortest Attack Trace in a Weighted Attack Graph
Yinxin Wan*, Xuanli Lin*, Abdulhakim Sabur, Alena Chang, Kuai Xu, Guoliang Xue
In ACM/IEEE Conference on Internet of Things Design and Implementation (IoTDI), 2023. (Best Paper Award)Exploring Machine Learning Algorithms for User Activity Inference from IoT Network Traffic
Kuai Xu, Yinxin Wan*, Xuanli Lin*, Feng Wang, Guoliang Xue
In IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS), 2023.FedAegis: Edge-Based Byzantine-Robust Federated Learning for Heterogeneous Data [PDF]
Fangtong Zhou*, Ruozhou Yu, Zhouyu Li*, Huayue Gu, Xiaojian Wang
In IEEE Global Communications Conference (GLOBECOM), 2022.IoTMosaic: Inferring User Activities from IoT Network Traffic in Smart Homes [PDF]
Yinxin Wan*, Kuai Xu, Feng Wang, Guoliang Xue
In IEEE International Conference on Computer Communications (INFOCOM), 2022.An Effective Machine Learning Based Algorithm for Inferring User Activities from IoT Device Events [PDF]
Guoliang Xue, Yinxin Wan*, Xuanli Lin*, Kuai Xu, Feng Wang
IEEE Journal on Selected Areas in Communications, Vol. 40, pp. 2733-2745, 2022.Principles and Practices for Application-Network Co-Design in Edge Computing
Ruozhou Yu, Guoliang Xue
IEEE Network Magazine, 2022.Data-Driven Edge Resource Provisioning for Inter-Dependent Microservices with Dynamic Load [PDF] [Slides]
Ruozhou Yu, Szu-Yu Lo, Fangtong Zhou*, Guoliang Xue
In IEEE Global Communications Conference (GLOBECOM), 2021.Edge-Assisted Collaborative Perception in Autonomous Driving: A Reflection on Communication Design [PDF] [Slides]
Ruozhou Yu, Dejun Yang, Hao Zhang
In ACM/IEEE Symposium on Edge Computing (SEC) Workshops, 2021.IoTAthena: Unveiling IoT Device Activities from Network Traffic [PDF]
Yinxin Wan*, Kuai Xu, Feng Wang, Guoliang Xue
IEEE Transactions on Wireless Communications, Vol. 21, pp. 651-664, 2021.
Datasets and Artifacts
Datasets and Artifacts
YOLO object detection microservice CPU, memory and GPU profiling (regression) [CPU-Memory-Fig] [GPU-Multi-Client-Fig]
[Experimental Data and Predictive Models: Benchmarking Microservice-based Application]Social network (DeathStarBench) application: network traffic profiling data [Dataset]
C-V2X NS-3 simulator with collaborative perception [GitHub]
Educational Activities, Outreach and Broader Impacts
Educational Activities, Outreach and Broader Impacts
9/2023: Eight NCSU undergraduate students started to participate in an REU experience related to testbed development of this project, receiving REU funding and/or CSC 299/498/499 course credits. Two local high school students from NCSSM has also participated in this project mentored by PhD student Zhouyu Li through the NCSSM Mentorship Program.
8/2023: A lightning talk on testbed development in this project is given during the NCSU CSC Undergraduate Research Lightning Talks in Fall 2023.
5/2023: One PhD student (Fangtong Zhou) received an NSF Student Travel Grant for IEEE INFOCOM 2023, and attended the conference in-person.
11/2022: PI Yu gave a virtual talk titled "Disentangling and Entangling Networked Distributed Systems: Edge-Cloud, AI and Quantum" at the IBM Back-to-School seminar series, being the first talk in the series after the pandemic.
9/2022: Two NCSU undergraduate students have participated in an REU experience related to testbed development of this project.
8/2022: A lightning talk on testbed development in this project is given during the NCSU CSC Undergraduate Research Lightning Talks in Fall 2022.
5/2022: Four PhD students from NCSU participated in IEEE INFOCOM 2022 as student volunteers.
5/2021: Two PhD students from ASU participated in IEEE INFOCOM 2022 as student volunteers.
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