J
John Augustine
Researcher at Indian Institute of Technology Madras
Publications - 90
Citations - 1127
John Augustine is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Distributed algorithm & Dynamic network analysis. The author has an hindex of 17, co-authored 81 publications receiving 955 citations. Previous affiliations of John Augustine include Nanyang Technological University & University of California, Irvine.
Papers
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Guarding a Polygon Without Losing Touch
Barath Ashok,John Augustine,Aditya Mehekare,Sridhar Ragupathi,Srikkanth Ramachandran,Suman Sourav +5 more
TL;DR: In this article, the authors consider the case where agents must remain connected through line-of-sight links and provide a centralized algorithm for the visibly connected setting that runs in time O(n), which is of course optimal.
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Sustaining Moore's Law Through Inexactness.
TL;DR: The ability to classify problems as shown in this work will serve as a basis for formally reasoning about the effectiveness of inexactness in the context of a range of computational problems with energy being the primary resource.
Proceedings Article
Minimizing Testing Overheads in Database Migration Lifecycle
Sangameshwar Patil,Sasanka Roy,John Augustine,Amanda Redlich,Sachin Lodha,Harrick Vin,Anand Deshpande,Mangesh Gharote,Ankit Mehrotra +8 more
TL;DR: As part of their information management lifecycle, organizations periodically face the important and inevitable task of migrating databases from one software and hardware platform to another.
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Optimal Evacuation Flows on Dynamic Paths with General Edge Capacities
Guru Prakash Arumugam,John Augustine,Mordecai J. Golin,Yuya Higashikawa,Naoki Katoh,Prashanth Srikanthan +5 more
TL;DR: This paper addresses the-sink evacuation problem on a dynamic path network and provides solutions that run in O(n \log n) time for k=1 and $O(k n \log^2 n)$ for $k >1 and work for arbitrary edge capacities.
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Approximate Weighted Farthest Neighbors and Minimum Dilation Stars
TL;DR: In this paper, the problem of querying approximate multiplicatively weighted farthest neighbors in a metric space was reduced to the unweighted problem, and an O(n log n) expected time algorithm was given for choosing the center of a star topology network connecting a given set of points, so as to approximately minimize the maximum dilation between any pair of points.