Vijay S. Kumar

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Hadoop and the associated MapReduce paradigm, has become the de facto platform for cost-effective analytics over “Big Data”. There is an increasing number of MapReduce applications associated with live business intelligence that require completion time guarantees. In this work, we introduce and analyze a set of complementary mechanisms that(More)
In this paper, we have presented the concept of cable less transmission i.e. power without the usage of any kind of the electrical conductor or wires. We present an idea discussed here, how energy can be transmitted as microwaves, so as to reduce the transmission and allocation losses, known as Microwave Power transmission (MPT). We have also cited several(More)
Integrative biomedical research projects query, analyze, and integrate many different data types and make use of datasets obtained from measurements or simulations of structure and function at multiple biological scales. With the increasing availability of high-throughput and high-resolution instruments, the integrative biomedical research imposes many(More)
Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as(More)
The era of precision medicine is best exemplified by the growing reliance on next-generation sequencing (NGS) technologies to provide improved disease diagnosis and targeted therapeutic selection. Well-established NGS data analysis software tools, in their unmodified form, can take days to identify and interpret single nucleotide and structural variations(More)
We present a combined task- and data-parallel approach for distributed execution of pre-processing operations to support efficient evaluation of polygonal aggregation queries on digitized microscopy images. Our approach targets out-of-core, pipelined processing of very large images on active storage clusters. Our experimental results show that the proposed(More)
Data analysis processes in scientific applications can be expressed as coarse-grain workflows of complex data processing operations with data flow dependencies between them. Performance optimization of these workflows can be viewed as a search for a set of optimal values in a multi-dimensional parameter space. While some performance parameters such as(More)
In many data analysis applications, application-level parameters influence the execution time of the data analysis method or program. Some of these parameters also affect the accuracy of output of the analysis. In this work, we investigate execution strategies for adaptive data analysis applications where the user is willing to trade-off accuracy of output(More)