Popularity Prediction for Social Media over Arbitrary Time Horizons
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
ACM SIGCOMM
Fiber cut events reduce the capacity of wide-area networks (WANs) by several Tbps. In this paper, we revive the lost capacity by reconfiguring the wavelengths from cut fibers into healthy fibers. We highlight two challenges that made prior solutions impractical and propose a system called ARROW to address them. First, our measurements show that contrary to common belief, in most cases, the lost capacity is only partially restorable. This poses a cross-layer challenge from the Traffic Engineering (TE) perspective that has not been considered before: “Which IP links should be restored and by how much to best match the TE objective?” To address this challenge, ARROW’s restoration-aware TE system takes a set of partial restoration candidates (that we call LotteryTickets) as input and proactively finds the best restoration plan. Second, prior work has not considered the reconfiguration latency of amplifiers. However, in practical settings, amplifiers add tens of minutes of reconfiguration delay. To enable fast and practical restoration, ARROW leverages optical noise loading and bypasses amplifier reconfiguration altogether. We evaluate ARROW using large-scale simulations and a testbed. Our testbed demonstrates ARROW’s end-to-end restoration latency is eight seconds. Our large-scale simulations compare ARROW to the state-of-the-art TE schemes and show it can support 2.0×–2.4× more demand without compromising 99.99% availability
Daniel Haimovich, Dima Karamshuk, Thomas Leeper, Evgeniy Riabenko, Milan Vojnovic
Liqi Yan, Qifan Wang, Yiming Cu, Fuli Feng, Xiaojun Quan, Xiangyu Zhang, Dongfang Liu
Barlas Oğuz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Wen-tau Yih