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Mayank Bawa
Researcher at Stanford University
Publications - 25
Citations - 2989
Mayank Bawa is an academic researcher from Stanford University. The author has contributed to research in topics: Information privacy & Network topology. The author has an hindex of 17, co-authored 25 publications receiving 2934 citations.
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Proceedings Article
Symphony: distributed hashing in a small world
TL;DR: Symphony, a novel protocol for maintaining distributed hash tables in a wide area network that is scalable, flexible, stable in the presence of frequent updates and offers small average latency with only a handful of long distance links per node.
Proceedings ArticleDOI
LSH forest: self-tuning indexes for similarity search
TL;DR: This index uses the well-known technique of locality-sensitive hashing (LSH), but improves upon previous designs by eliminating the different data-dependent parameters for which LSH must be constantly hand-tuned, and improving on LSH's performance guarantees for skewed data distributions while retaining the same storage and query overhead.
Proceedings Article
Two Can Keep a Secret: A Distributed Architecture for Secure Database Services
Gagan Aggarwal,Mayank Bawa,Prasanna Ganesan,Hector Garcia-Molina,Krishnaram Kenthapadi,Rajeev Motwani,Utkarsh Srivastava,Dilys Thomas,Ying Xu +8 more
TL;DR: This work proposes a new, distributed architecture that allows an organization to outsource its data management to untrusted servers while preserving data privacy, and shows how the presence of two servers enables efficient partitioning of data.
Book ChapterDOI
Online balancing of range-partitioned data with applications to peer-to-peer systems
TL;DR: This work proposes efficient, asymptotically optimal algorithms that ensure storage balance at all times, even against an adversarial insertion and deletion of tuples, in a P2P system that supports efficient range queries, while simultaneously guaranteeing storage balance.
Journal ArticleDOI
Turbo-charging vertical mining of large databases
Pradeep Shenoy,Jayant R. Haritsa,Sundararajarao Sudarshan,Gaurav Bhalotia,Mayank Bawa,Devavrat Shah +5 more
TL;DR: This work presents a new vertical mining algorithm called VIPER, which is general-purpose, making no special requirements of the underlying database, and analyzes the performance of VIPER for a range of synthetic database workloads.