Divyasheel Sharma

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In this paper, we introduce a <i>rotating interrogation</i> technique for sensor networks called <i>Whirlpool</i>. <i>Whirlpool</i> provides opportunities to optimize data delivery in time-critical monitoring applications. We explore concurrency opportunities while delivering data using the whirlpool strategy and investigate several whirlpool algorithms. We(More)
We propose a novel data delivery strategy, called Whirlpool, for efficient SHM using Wireless Sensor Networks. Whirlpool implements a rotating interrogation of a monitoring structure and provides collision-aware scheduling of the monitoring queries. The Whirlpool strategy can be tuned for the required Quality of Data (QoD). We apply Whirlpool to examine the(More)
In this paper we propose a query-driven approach for tuning the time/energy trade-off in sensor networks with mobile sensors. The tuning factors include re-positioning of mobile sensors and changing their transmission ranges. We propose an algebraic query optimization framework that explores these factors while utilizing collision-free concurrent data(More)
With the growth of adaptive educational systems available for students, semantic integration of user modeling information from these systems is emerging into an important practical task. Ontologies can serve as the major representational framework for such integration. However, not all adaptive systems rely on ontologies for representing domain knowledge.(More)
There are performance deficiencies that hamper the deployment of Wireless Sensor Networks (WSNs) in critical monitoring applications. Such applications are characterized by considerable network load generated as a result of sensing some characteristic(s) of the monitored system. Excessive packet collisions lead to packet losses and retransmissions,(More)
Sensor networks naturally apply to a broad range of applications that involve system monitoring and information tracking (e.g., airport security infrastructure, monitoring of children in metropolitan areas, product transition in warehouse networks, fine-grained weather/environmental measurements, etc.). Meanwhile, there are considerable performance(More)
The combined effect of various problems such as congestion, collisions and route unavailability for data in Data-Intensive Sensor Networks is hard to estimate. This is one of the major reasons why existing solutions that try to optimize all these do not scale and have limited applicability. Our light-weight approach uses decisions made locally by individual(More)
This paper describes a method for the recovering of software architectures from a set of similar (but unrelated) software products in binary form. One intention is to drive refactoring into software product lines and combine architecture recovery with run time binary analysis and existing clustering methods. Using our runtime binary analysis, we create(More)
Sensor databases extend database technology to query and monitor the physical world as a highly distributed database. In this paper we consider a Data Transmission Algebra (DTA) that allows a query optimizer to utilize lower layer communication protocols in scheduling sensor database queries. By being able to determine the order in which data are processed(More)
Sensor databases extend database technology to query and monitor the physical world as a highly distributed database. In this paper we consider a Data Transmission Algebra (DTA) that allows a query optimizer to utilize lower layer communication protocols in scheduling sensor database queries. By being able to determine the order in which data are processed(More)
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