ShallowForest: Optimizing All-to-All Data Transmission in WANs
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Date
2019-05-23
Authors
Tan, Hao
Advisor
Golab, Wojciech
Srinivasan, Keshav
Srinivasan, Keshav
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
All-to-all data transmission is a typical data transmission pattern in both consensus protocols and blockchain systems. Developing an optimization scheme that provides high throughput and low latency data transmission can significantly benefit the performance of those systems. This thesis investigates the problem of optimizing all-to-all data transmission in a wide area network (WAN) using overlay multicast. I first prove that in a congestion-free core network model, using shallow tree overlays with height up to two is sufficient for all-to-all data transmission to achieve the optimal throughput allowed by the available network resources. Based on this finding, I build ShallowForest, a data plane optimization for consensus protocols and blockchain systems. The goal of ShallowForest is to improve consensus protocols' resilience to skewed client load distribution. Experiments with skewed client load across replicas in the Amazon cloud demonstrate that ShallowForest can improve the commit throughput of the EPaxos consensus protocol by up to 100% with up to 60% reduction in commit latency
Description
Keywords
Overlay Network, Consensus Protocols, Blockchain