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Aravind Srinivasan
Researcher at University of Maryland, College Park
Publications - 278
Citations - 14614
Aravind Srinivasan is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Approximation algorithm & Wireless network. The author has an hindex of 60, co-authored 266 publications receiving 13711 citations. Previous affiliations of Aravind Srinivasan include Graz University of Technology & Bell Labs.
Papers
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Journal ArticleDOI
Distributed Algorithms for End-to-End Packet Scheduling in Wireless Ad Hoc Networks
TL;DR: This work presents polylogarithmic/constant factor approximation algorithms for various families of disk graphs (which capture the geometric nature of wireless-signal propagation), as well as near-optimal approximation algorithms that are provably better in the worst case.
Posted Content
Approximation Algorithms for Radius-Based, Two-Stage Stochastic Clustering Problems with Budget Constraints.
Brian Brubach,Nathaniel Grammel,David G. Harris,Aravind Srinivasan,Leonidas Tsepenekas,Anil Vullikanti +5 more
TL;DR: This paper develops algorithms for a restricted version of each problem, in which all possible scenarios are explicitly provided, and exploits structural properties of these algorithms and generalize them to the black-box setting.
Book ChapterDOI
Maximum Bipartite Flow in Networks with Adaptive Channel Width
TL;DR: This work considers the problem of maximum bipartite flow, which has been studied extensively in the traditional network model and shows that the problem is NP-hard in the new model, and complements the lower bound by giving two algorithms for solving the problem approximately.
Proceedings Article
Follow Your Star: New Frameworks for Online Stochastic Matching with Known and Unknown Patience
TL;DR: In this article, a stochastic version of the online matching problem was introduced, where the patience is chosen randomly according to some known distribution and is not known until the point at which patience has been exhausted.
Proceedings ArticleDOI
Efficient algorithms for location and sizing problems in network design
TL;DR: A general class of such network design problems as Mixed-Integer Programs, which are computationally intractable in general, are formulated and it is shown how to compute near-optimal solutions under various asymptotic conditions.