Sanjeev Kulkarni

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We describe MW – a software framework that allows users to quickly and easily parallelize scientific computations using the master-worker paradigm on the computational grid. MW provides both a " top level " interface to application software and a " bottom level " interface to existing grid computing toolkits. Both interfaces are briefly described. We(More)
Storm has long served as the main platform for real-time analytics at Twitter. However, as the scale of data being processed in real-time at Twitter has increased, along with an increase in the diversity and the number of use cases, many limitations of Storm have become apparent. We need a system that scales better, has better debug-ability, has better(More)
The goal of this work is to create a tool that allows users to easily distribute large scientific computations on computational grids. Our tool MW relies on the simple master-worker paradigm. MW provides both a top level interface to application software and a bottom level interface to existing grid computing toolkits. Both interfaces are briefly described.(More)
The Burrows-Wheeler transform is a block-sorting algorithm which has been shown empirically to be useful in compressing text data. In this paper we study the output distribution of the transform for i.i.d. sources, tree sources and stationary ergodic sources. We can also give analytic bounds on the performance of some universal compression schemes which use(More)
Velocity is one of the 4 Vs commonly used to characterize Big Data [5]. In this regard, Forrester remarked the following in Q3 2014 [8]: " The high velocity, white-water flow of data from innumerable real-time data sources such as market data, Internet of Things, mobile, sensors, click-stream, and even transactions remain largely unnavigated by most firms.(More)
In linear decentralized estimation, several nodes concurrently aim to estimate the state of a common phenomenon by means of local measurements and data exchanges. In this contribution, an efficient algorithm for consistent estimation of linear systems in sensor networks is derived. The main theorems generalize Covariance Intersection by means of an explicit(More)
Sybil attacks are becoming increasingly widespread, and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the system to compromise security and privacy. Recent works have leveraged the use of social network-based trust relationships to defend against Sybil attacks. However , existing defenses(More)
Distributed Kalman filtering aims at optimizing an estimate at a fusion center based on information that is gathered in a sensor network. Recently, an exact solution based on local estimation tracks has been proposed and an extension to cope with packet losses has been derived. In this contribution, we generalize both algorithms to packet delays. The key(More)