R
Ravi Sundaram
Researcher at Northeastern University
Publications - 151
Citations - 4409
Ravi Sundaram is an academic researcher from Northeastern University. The author has contributed to research in topics: Approximation algorithm & Graph (abstract data type). The author has an hindex of 38, co-authored 149 publications receiving 4176 citations. Previous affiliations of Ravi Sundaram include University of Würzburg & Indian Institutes of Technology.
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Patent
Optimal route selection in a content delivery network
TL;DR: In this paper, the authors proposed a routing mechanism, service, or system operable in a distributed networking environment, which enables an edge server operating within a given CDN region to retrieve content (cacheable, non-cacheable and the like) from an origin server more efficiently by selectively routing through the CDN's own nodes.
Patent
Global load balancing across mirrored data centers
F. Thomson Leighton,Daniel M. Lewin,Ravi Sundaram,Rizwan S. Dhanidina,Robert Kleinberg,Matthew Levine,Andrian Soviani,Bruce M. Maggs,Hariharan Rahul,Srikanth Thirumalai,Jay G. Parikh,Yoav O. Yerushalmi,Madhukar R. Korupolu +12 more
TL;DR: In this paper, an intelligent traffic redirection system that does global load balancing is proposed, which can be used in any situation where an end-user requires access to a replicated resource.
Journal ArticleDOI
Bicriteria Network Design Problems
TL;DR: Here, the first polynomial-time approximation algorithms for a large class of bicriteria network design problems for the previously mentioned criteria are presented and it is shown how these pseudo-polynomial-time algorithms can be converted to fully polynomials time approximation schemes using a scaling technique.
Posted Content
Spanning trees short or small
TL;DR: It is shown that the kMST problem is NP-hard even for points in the Euclidean plane, and a simple technique is used to provide a polynomiM-time solution for finding k-trees of minimum diameter.
Proceedings ArticleDOI
Delay tolerant bulk data transfers on the internet
TL;DR: This paper proposes transmitting multiterabyte data through commercial ISPs by taking advantage of already-paid-for off-peak bandwidth resulting from diurnal traffic patterns and percentile pricing, and shows that between sender-receiver pairs with small time-zone difference, simple source scheduling policies are able to take advantage of most of the existing off- peak capacity.