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青年学者学术报告High-Performance Network Analytics via Approximate Techniques
2019-05-15
南京大学计算机软件新技术国家重点实验室   
摘 要:
Network data processing is indispensable to modern network management in clouds and data centers. This talk will present several recent works that made trade-offs among performance, accuracy and usability for massive data processing in networking architecture. leverage approximation techniques to optimize their designs, thereby providing a trade-off between performance and accuracy. In particular, this talk will introduce a classical streaming techniques namely sketches and demonstrate how to build efficient network measurement systems atop them.
报告人简介:
Qun Huang is an Associate Professor at Institute of Computing Technology, Chinese Academy of Sciences (ICT-CAS). Before joining ICT, he was a Researcher at Huawei Future Network Theory Lab in Hong Kong from 2015 to 2017, leading a group for network measurement and analytics. He got his Ph.D. degree in August 2015 from The Chinese University of Hong Kong, and B.S. degree from Peking University in 2011. He has published papers in several top conferences including ACM SIGCOMM, VLDB and INFOCOM.
时间:5月20日(星期一)10:00
地点:计算机科学技术楼229室

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