南京大学计算机科学与技术系

软件新技术与产业化协同创新中心

摘 要：

Facing serious challenges in bandwidth and latency, currently adopted cloud computing is no longer effective for performing the real-time tasks from Internet of Vehicles (IoV) in the smart cities. An emerging computing paradigm, i.e., edge computing, is proposed to complement cloud computing by offloading the tasks to the edge of the network. Generally, the task offloading is implemented based on the premise that edge servers (ESs) are appropriately quantified and located. However, the quantification of the ESs is often offered according to the empirical knowledge, lacking analysis on the real traffic condition in IoV. Thus, the quantity and locations of the ESs need to be thoroughly discussed ahead, otherwise additional latency and network congestion will occur. In this talk, I will address the abovementioned problem, and show a designed collaborative method for the quantification and placement of the ESs in IoV.

报告人简介:

Xiaolong Xu received his Ph.D. degree from Nanjing University, China, in Dec. 2016. He is currently a lecture with the school of computer and software, Nanjing University of Information Science and Technology. He worked as a research scholar at Michigan State University, USA, from Apr. 2017 to May 2018. His research interests include edge computing, fog computing, cloud computing and big data. He has published more than 40 peer review papers in international journals and conferences, including IEEE TII, IEEE TCC, IEEE TBD, IEEE IOT, IEEE TCSS, IEEE TETCI, WWWJ, SPE, IEEE ICWS, ICSOC, etc.

时间：12月20日 14:00-16:00

地点：计算机科学技术楼231室