EXPRESS 2.0: An Intelligent Service Management Framework for AIoT Systems in the Edge
AIoT (Artificial Intelligence of Things) which integrates AI and IoT has received rapidly growing interest from the software engineering community in recent years. It is crucial to design scalable, efficient, and reliable software solutions for large-scale AIoT systems in edge computing environments. However, the lack of effective service management including the support for service collaboration, AI application, and data security in the edge, has seriously limited the development of AIoT systems. To seal this gap, we propose EXPRESS 2.0 which is an intelligent service management framework for AIoT in the edge. Specifically, on top of the existing EXPRESS platform, EXPRESS 2.0 includes the intelligent service collaboration management module, AI application management module, and data security management module. To demonstrate the effectiveness of the framework, we design and implement a last-mile delivery system using both UAVs (Unmanned Aerial Vehicles) and UGVs (Unmanned Ground Vehicles). The EXPRESS 2.0 is open-sourced at https://github.com/ISEC-AHU/EXPRESS2.0. A video demonstration of EXPRESS 2.0 is at https://youtu.be/GHKD_VvJD88.
Tue 12 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
13:30 - 15:00 | Cloud and Distributed Systems 2Research Papers / Tool Demonstrations / Journal-first Papers / Industry Showcase (Papers) at Plenary Room 2 Chair(s): Tim Menzies North Carolina State University | ||
13:30 12mTalk | EXPRESS 2.0: An Intelligent Service Management Framework for AIoT Systems in the Edge Tool Demonstrations Jia Xu School of Computer Science and Technology, Anhui University, Xiao Liu School of Information Technology, Deakin University, Wuzhen Pan School of Computer Science and Technology, Anhui University, Xuejun Li School of Computer Science and Technology, Anhui University, Aiting Yao School of Computer Science and Technology, Anhui University, Yun Yang Swinburne University of Technology Media Attached | ||
13:42 12mTalk | Prism: Revealing Hidden Functional Clusters of Massive Instances in Cloud Systems Research Papers Jinyang Liu The Chinese University of Hong Kong, Zhihan Jiang The Chinese University of Hong Kong, Jiazhen Gu Chinese University of Hong Kong, Junjie Huang The Chinese University of Hong Kong, Zhuangbin Chen School of Software Engineering, Sun Yat-sen University, Cong Feng Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, Zengyin Yang Computing and Networking Innovation Lab, Huawei Cloud Computing Technology Co., Ltd, Yongqiang Yang Huawei Technologies, Michael Lyu The Chinese University of Hong Kong Pre-print File Attached | ||
13:54 12mTalk | FaaSLight: General Application-Level Cold-Start Latency Optimization for Function-as-a-Service in Serverless Computing Journal-first Papers Xuanzhe Liu Peking University, Jinfeng Wen Peking University, Zhenpeng Chen University College London, Ding Li Peking University, Junkai Chen Peking University, China, Yi Liu Peking University, Haoyu Wang Huazhong University of Science and Technology, Xin Jin Peking University File Attached | ||
14:06 12mTalk | RocketHA: A High Availability Design Paradigm for Distributed Log-Based Storage System Industry Showcase (Papers) Juntao Ji Alibaba Cloud Computing Co. Ltd., Rongtong Jin Alibaba Cloud Computing Co. Ltd., Yubao Fu Alibaba Cloud Computing Co. Ltd., Yinyou Gu Alibaba Cloud Computing Co. Ltd., Tsung-han Tsai Alibaba Cloud Computing Co. Ltd., Qingshan Lin Alibaba Cloud Computing Co. Ltd. | ||
14:18 12mTalk | Rise of Distributed Deep Learning Training in the Big Model Era: From a Software Engineering Perspective Journal-first Papers Xuanzhe Liu Peking University, Diandian Gu Peking University, Zhenpeng Chen University College London, Jinfeng Wen Peking University, Zili Zhang Peking University, Yun Ma Peking University, Haoyu Wang Huazhong University of Science and Technology, Xin Jin Peking University Link to publication | ||
14:30 12mTalk | ConfTainter: Static Taint Analysis For Configuration OptionsRecorded talk Research Papers Teng Wang National University of Defense Technology, Haochen He National University of Defense Technology, Xiaodong Liu National University of Defense Technology, Shanshan Li National University of Defense Technology, Zhouyang Jia National University of Defense Technology, Yu Jiang Tsinghua University, Qing Liao Harbin Institute of Technology, Wang Li National University of Defense Technology Pre-print Media Attached |