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Sivakumar Kulasekaran

dblp:75/9913 · also Kulasekaran A. Sivakumar, Sivakumar Ayeegoundanpalay Kulasekaran · DBLP profile ↗
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8ranked-venue papers
5as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 4 · 4 first-authorSystems, architecture and hardware · 2Databases, data management, data science and information retrieval · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
High-performance computing · 77% Distributed systems · 23%
Computer networks
1 paper
Network performance modeling · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Network performance modeling › performance prediction
throughput prediction
0.112011
A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing · IEEE Trans. Parallel Distributed Syst. 2011
High-performance computing › high-throughput computing
many-task computing
0.112011
A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing · IEEE Trans. Parallel Distributed Syst. 2011
Distributed systems › distributed scheduling
data transfer scheduling
0.012011
A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing · IEEE Trans. Parallel Distributed Syst. 2011

Methods — techniques the papers use, named apart from their topics

mathematical modeling · 0.2iperf sampling · 0.2GridFTP sampling · 0.2
YearPublicationVenuePosition
2019 Computing environments for reproducibility: Capturing the "Whole Tale"
abstract
The act of sharing scientific knowledge is rapidly evolving away from traditional articles and presentations to the delivery of executable objects that integrate the data and computational details (e.g., scripts and workflows) upon which the findings rely. This envisioned coupling of data and process is essential to advancing science but faces technical and institutional barriers. The Whole Tale project aims to address these barriers by connecting computational, data-intensive research efforts with the larger research process—transforming the knowledge discovery and dissemination process into one where data products are united with research articles to create “living publications” or tales. The Whole Tale focuses on the full spectrum of science, empowering users in the long tail of science, and power users with demands for access to big data and compute resources. We report here on the design, architecture, and implementation of the Whole Tale environment.
Adam Brinckman, Kyle Chard, Niall Gaffney, Mihael Hategan, Matthew B. Jones, Kacper Kowalik, Sivakumar Kulasekaran, Bertram Ludäscher, Bryce D. Mecum, Jarek Nabrzyski, Victoria Stodden, Ian J. Taylor, Matthew J. Turk, Kandace Turner
Future Gener. Comput. Syst.7
2017 A Data Model for Lifecycle Management of Natural Hazards Engineering Data
Maria Esteva, Ashley Adair, Sivakumar Kulasekaran, Josue Balandrano Coronel, Craig Jansen
Dublin Core Conference3
2014 Metadata Integration for an Archaeology Collection Architecture
Sivakumar Kulasekaran, Jessica Trelogan, Maria Esteva
Dublin Core Conference1
2011 A Data Throughput Prediction and Optimization Service for Widely Distributed Many-Task Computing
abstract
In this paper, we present the design and implementation of an application-layer data throughput prediction and optimization service for many-task computing in widely distributed environments. This service uses multiple parallel TCP streams to improve the end-to-end throughput of data transfers. A novel mathematical model is developed to determine the number of parallel streams, required to achieve the best network performance. This model can predict the optimal number of parallel streams with as few as three prediction points. We implement this new service in the Stork Data Scheduler, where the prediction points can be obtained using Iperf and GridFTP samplings. Our results show that the prediction cost plus the optimized transfer time is much less than the nonoptimized transfer time in most cases. As a result, Stork data transfer jobs with optimization service can be completed much earlier, compared to nonoptimized data transfer jobs.
Dengpan Yin, Esma Yildirim, Sivakumar Kulasekaran, Brandon Ross, Tevfik Kosar
IEEE Trans. Parallel Distributed Syst.3
2008 Improving the resiliency of Ariadne
abstract
Ariadne is a popular secure ad hoc routing protocol based on the dynamic source routing (DSR) protocol. While Ariadne was designed to be capable of detecting attacks by non colluding attackers, it does not include measures to identify or narrow down perpetrators responsible for such attacks. We propose some modifications to Ariadne to improve its resiliency, by affording the ability to identify and route around malicious nodes.
Sivakumar Kulasekaran, Mahalingam Ramkumar
WOWMOM1
2007 An Efficient Secure Route Discovery Protocol for DSR
abstract
Ensuring cryptographic integrity of the route discovery process in on demand ad hoc routing approaches like dynamic source routing (DSR) require the ability to verify that no nodes have been deleted from the path, and no node can be inserted in the path without a valid authentication. We discuss the need for early detection of inconsistencies involving inserted or deleted nodes in route request (RREQ) packets and investigate the challenges associated with catering for this requirement. We propose an efficient strategy to achieve this employing only symmetric cryptographic primitives, which is made possible due to a recently proposed multi-source broadcast encryption scheme. We outline a protocol for secure route discovery in DSR that employs such a security primitive, and provide quantitative estimates (through simulations) of gains that can be achieved by early detection of inconsistent RREQs.
Sivakumar Kulasekaran, Mahalingam Ramkumar
GLOBECOM1
2007 Safeguarding Mutable Fields in AODV Route Discovery Process
abstract
Assuring cryptographic integrity of mutable fields in any on-demand ad hoc routing protocol is more challenging than that of non mutable fields. We propose an efficient authentication strategy for this purpose, which leverages a proposed broadcast encryption (BE) scheme. We investigate some shortcomings of SAODV, a popular secure extension of the ad hoc on-demand distance vector (AODV) protocol and suggest some modifications to the protocol to overcome the shortcomings. The modifications include proactive maintenance of a secure reliable delivery neighborhood (RDN) by each node and the use of the BE based authentication strategy for mutable fields.
Sivakumar Kulasekaran, Mahalingam Ramkumar
ICCCN1
2006 On the Effect of One-way Links on Route Discovery in DSR
abstract
One-way links are an unavoidable reality in wireless channels. The detrimental effects of one way links on many routing strategies, including the dynamic source routing protocol (DSR), have been investigated by many researchers. Apart from reducing the efficiency of DSR, we point out that disregarding possible one-way links also has some implications on the security of secure DSR extensions. Most secure extensions of DSR rely on the assumption that all links are bidirectional. We point out proactive strategies to indicate one-way links in route request (RREQ) packets to limit their use, with the intention of simultaneously improving the efficiency and security of secure DSR protocols.
Sivakumar Kulasekaran, Mahalingam Ramkumar
ICCCN1