Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
USENIX Symposium on Networked Systems Design and Implementation (NSDI)
Datacenters are characterized by their large scale, comprising a large number of network links and switches. However, these hardware components can develop intermittent faults, resulting in randomly occurring packet drops or delays that harm application performance—several such faults occur daily in large production datacenters. Since the effects are intermittent, traditional detection techniques involving end-host and router statistics or active probe traffic can fall short in their ability to identify and locate these errors. In this article, we present our passive hybrid approach that combines network path information with end-host-based statistics to rapidly detect and pinpoint the location of datacenter network faults inside a production Facebook datacenter.
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Liqi Yan, Qifan Wang, Yiming Cu, Fuli Feng, Xiaojun Quan, Xiangyu Zhang, Dongfang Liu
Patrick Lewis, Barlas Oğuz, Wenhan Xiong, Fabio Petroni, Wen-tau Yih, Sebastian Riedel