Menu Close

Title: On Optimal Offloading of DNNs from IoTs to Cloud

Speaker: Prof. Jie Wu

Abstract:  As Deep Neural Networks (DNNs) have been widely used in various applications, including computer vision on image segmentation and recognition, it is important to reduce the makespan of DNN computation, especially when running on IoT devices. Offloading is a viable solution that offloads computation from a slow IoT device to a fast, but remote server in cloud. As DNN computation consists of a multiple-stage processing pipeline, it is critical to decide on what stage should offloading occur to minimize the makespan. Our observations show that the local computation time on a mobile device follows a linear increasing function, while the offloading time on a mobile device is monotonic decreasing and follows a convex curve as more DNN layers are computed in the mobile device. Based on this observation, we first study the optimal partition and scheduling for one line-structure DNN. Then, we extend the result to multiple line-structure DNNs. Heuristic results for general-structure DNNs, represented by Directed Acyclic Graphs (DAGs), are also discussed based on a path-based scheduling policy. Our proposed solutions are validated via real system implementation.

Bio: Jie Wu is Laura H. Carnell Professor at Temple University and the Director of the Center for Networked Computing (CNC). He served as Chair of the Department of Computer and Information Sciences from the summer of 2009 to the summer of 2016 and Associate Vice Provost for International Affairs from the fall of 2015 to the summer of 2017. Prior to joining Temple University, he was a program director at the National Science Foundation and was a distinguished professor at Florida Atlantic University. His current research interests include mobile computing and wireless networks, routing protocols, network trust and security, distributed algorithms, applied machine learning, and cloud computing. Dr. Wu regularly published in scholarly journals, conference proceedings, and books. He serves on several editorial boards, including IEEE Transactions on Service Computing, IEEE/ACM Transactions on Networking, and Journal of Computer Science and Technology. Dr. Wu is/was general chair/co-chair for IEEE IPDPS’23, ACM MobiHoc’23, and IEEE CCGrid 2024 as well as program chair/cochair for IEEE INFOCOM’11, CCF CNCC’13, and ICCCN’20. He was an IEEE Computer Society Distinguished Visitor, ACM Distinguished Speaker, and chair for the IEEE Technical Committee on Distributed Processing (TCDP). Dr. Wu is a Fellow of the AAAS and a Fellow of the IEEE.  He is a Member of the Academia Europaea (MAE).