382 citations · 1.6k across the 39 of their papers we have counts for
8 papers · 1 filter
Learning Scheduling Algorithms for Data Processing Clusters
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan +2
Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms. Current systems, however, use simple generalized heuristics and ignore work…
High Throughput Cryptocurrency Routing in Payment Channel Networks
Vibhaalakshmi Sivaraman, Shaileshh Bojja Venkatakrishnan, Kathy Ruan +5
Despite growing adoption of cryptocurrencies, making fast payments at scale remains a challenge. Payment channel networks (PCNs) such as the Lightning Network have emerged as a via…
Secure Incentivization for Decentralized Content Delivery
Prateesh Goyal, Ravi Netravali, Mohammad Alizadeh +1
Prior research has proposed technical solutions to use peer-to-peer (P2P) content delivery to serve Internet video, showing that it can reduce costs to content providers. Yet, such…
Variance Reduction for Reinforcement Learning in Input-Driven Environments
Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf +1
We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system. Input processes arise in many appl…
Homa: A Receiver-Driven Low-Latency Transport Protocol Using Network Priorities (Complete Version)
Behnam Montazeri, Yilong Li, Mohammad Alizadeh +1
Homa is a new transport protocol for datacenter networks. It provides exceptionally low latency, especially for workloads with a high volume of very short messages, and it also sup…
Elasticity Detection: A Building Block for Internet Congestion Control
Prateesh Goyal, Akshay Narayan, Frank Cangialosi +3
This paper introduces Nimbus, a robust technique to detect whether the cross traffic competing with a flow is "elastic", and shows that this elasticity detector improves congestion…
Graph2Seq: Scalable Learning Dynamics for Graphs
Shaileshh Bojja Venkatakrishnan, Mohammad Alizadeh, Pramod Viswanath
Neural networks have been shown to be an effective tool for learning algorithms over graph-structured data. However, graph representation techniques---that convert graphs to real-v…
RoadTracer: Automatic Extraction of Road Networks from Aerial Images
Favyen Bastani, Songtao He, Sofiane Abbar +5
Mapping road networks is currently both expensive and labor-intensive. High-resolution aerial imagery provides a promising avenue to automatically infer a road network. Prior work…