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Sumit Rangwala

Bio: Sumit Rangwala is an academic researcher from Cisco Systems, Inc.. The author has contributed to research in topics: Wireless sensor network & Structural health monitoring. The author has an hindex of 14, co-authored 22 publications receiving 2500 citations. Previous affiliations of Sumit Rangwala include University of Southern California & University of California, Los Angeles.

Papers
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Proceedings ArticleDOI
03 Nov 2004
TL;DR: Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization.
Abstract: Structural monitoring---the collection and analysis of structural response to ambient or forced excitation--is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by low-power wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

1,195 citations

Journal ArticleDOI
11 Aug 2006
TL;DR: Interferenceaware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law.
Abstract: In a wireless sensor network of N nodes transmitting data to a single base station, possibly over multiple hops, what distributed mechanisms should be implemented in order to dynamically allocate fair and efficient transmission rates to each node? Our interferenceaware fair rate control (IFRC) detects incipient congestion at a node by monitoring the average queue length, communicates congestion state to exactly the set of potential interferers using a novel low-overhead congestion sharing mechanism, and converges to a fair and efficient rate using an AIMD control law. We evaluate IFRC extensively on a 40-node wireless sensor network testbed. IFRC achieves a fair and efficient rate allocation that is within 20-40% of the optimal fair rate allocation on some network topologies. Its rate adaptation mechanism is highly effective: we did not observe a single instance of queue overflow in our many experiments. Finally, IFRC can be extended easily to support situations where only a subset of the nodes transmit, where the network has multiple base stations, or where nodes are assigned different transmission weights.

313 citations

Journal ArticleDOI
TL;DR: This article describes two systems the authors recently deployed in real-world structures that can autonomously and proactively assess the structural integrity of bridges, buildings, and aerospace vehicles.
Abstract: Structural health monitoring (SHM) is an active area of research devoted to systems that can autonomously and proactively assess the structural integrity of bridges, buildings, and aerospace vehicles. Recent technological advances promise the eventual ability to cover a large civil structure with low-cost wireless sensors that can continuously monitor a building's structural health, but researchers face several obstacles to reaching this goal, including high data-rate, data-fidelity, and time-synchronization requirements. This article describes two systems the authors recently deployed in real-world structures.

288 citations

Patent
16 Sep 2011
TL;DR: In this article, a method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchical-arranged data center, clustering nodes based on groups of capabilities information and sending the histogram to a next higher-level in the hierarchy.
Abstract: A method for summarizing capabilities in a hierarchically arranged data center includes receiving capabilities information, wherein the capabilities information is representative of capabilities of respective nodes at a first hierarchical level in the hierarchically arranged data center, clustering nodes based on groups of capabilities information, generating a histogram that represents individual node clusters, and sending the histogram to a next higher level in the hierarchically arranged data center. Relative rankings of capabilities may be used to order a sequence of clustering operations.

144 citations

Proceedings ArticleDOI
14 Sep 2008
TL;DR: In this paper, the authors propose a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme called Wireless Control Protocol with Capacity Estimation (WCPCap).
Abstract: Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

123 citations


Cited by
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Proceedings ArticleDOI
04 Nov 2009
TL;DR: In this paper, the authors evaluate datapath validation and adaptive beaconing in CTP Noe, a sensor network tree collection protocol, on both interference-free and interference-prone channels.
Abstract: This paper presents and evaluates two principles for wireless routing protocols. The first is datapath validation: data traffic quickly discovers and fixes routing inconsistencies. The second is adaptive beaconing: extending the Trickle algorithm to routing control traffic reduces route repair latency and sends fewer beacons.We evaluate datapath validation and adaptive beaconing in CTP Noe, a sensor network tree collection protocol. We use 12 different testbeds ranging in size from 20--310 nodes, comprising seven platforms, and six different link layers, on both interference-free and interference-prone channels. In all cases, CTP Noe delivers > 90% of packets. Many experiments achieve 99.9%. Compared to standard beaconing, CTP Noe sends 73% fewer beacons while reducing topology repair latency by 99.8%. Finally, when using low-power link layers, CTP Noe has duty cycles of 3% while supporting aggregate loads of 30 packets/minute.

1,516 citations

Journal ArticleDOI
TL;DR: This paper is intended to serve as a summary review of the collective experience the structural engineering community has gained from the use of wireless sensors and sensor networks for monitoring structural performance and health.
Abstract: In recent years, there has been an increasing interest in the adoption of emerging sensing technologies for instrumentation within a variety of structural systems. Wireless sensors and sensor networks are emerging as sensing paradigms that the structural engineering field has begun to consider as substitutes for traditional tethered monitoring systems. A benefit of wireless structural monitoring systems is that they are inexpensive to install because extensive wiring is no longer required between sensors and the data acquisition system. Researchers are discovering that wireless sensors are an exciting technology that should not be viewed as simply a substitute for traditional tethered monitoring systems. Rather, wireless sensors can play greater roles in the processing of structural response data; this feature can be utilized to screen data for signs of structural damage. Also, wireless sensors have limitations that require novel system architectures and modes of operation. This paper is intended to serve as a summary review of the collective experience the structural engineering community has gained from the use of wireless sensors and sensor networks for monitoring structural performance and health.

1,497 citations

Proceedings ArticleDOI
25 Apr 2007
TL;DR: A Wireless Sensor Network for Structural Health Monitoring is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge and the collected data agrees with theoretical models and previous studies of the bridge.
Abstract: A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.

992 citations

Proceedings ArticleDOI
06 Nov 2006
TL;DR: An approach to time rectification of the acquired signals that can recover accurate timing despite failures of the underlying time synchronization protocol is described.
Abstract: We present a science-centric evaluation of a 19-day sensor network deployment at Reventador, an active volcano in Ecuador. Each of the 16 sensors continuously sampled seismic and acoustic data at 100 Hz. Nodes used an event-detection algorithm to trigger on interesting volcanic activity and initiate reliable data transfer to the base station. During the deployment, the network recorded 229 earthquakes, eruptions, and other seismoacoustic events.The science requirements of reliable data collection, accurate event detection, and high timing precision drive sensor networks in new directions for geophysical monitoring. The main contribution of this paper is an evaluation of the sensor network as a scientific instrument, holding it to the standards of existing instrumentation in terms of data fidelity (the quality and accuracy of the recorded signals) and yield (the quantity of the captured data). We describe an approach to time rectification of the acquired signals that can recover accurate timing despite failures of the underlying time synchronization protocol. In addition, we perform a detailed study of the sensor network's data using a direct comparison to a standalone data logger, as well as an investigation of seismic and acoustic wave arrival times across the network.

731 citations

Book
20 Nov 2014
TL;DR: This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions.
Abstract: This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions The book is intended for a professional audience composed of researchers and practitioners in industry This book is also appropriate for advanced-level students in computer science

726 citations