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ACM Transactions on

Sensor Networks (TOSN)

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About TOSN

TOSN publishes original research papers (approximately 30-40 printed pages each in ACM Transaction style) and tutorial and survey papers (approximately 30-50 printed pages each). We also accept short technical notes that focus on industrial technologies and practical experience.
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Forthcoming Articles
Harmonium: Ultra Wideband Pulse Generation with Bandstitched Recovery for Fast, Accurate, and Robust Indoor Localization

We introduce Harmonium, a novel ultra-wideband RF localization architecture that achieves decimeter-scale accuracy indoors. Harmonium strikes a balance between tag simplicity and processing complexity to provide fast and accurate indoor location estimates. Harmonium uses only commodity components and consists of a small, inexpensive, lightweight, and FCC-compliant ultra-wideband transmitter or tag, fixed infrastructure anchors with known locations, and centralized processing that calculates the tags position. Anchors employ a new frequency-stepped narrowband receiver architecture that rejects narrowband interferers and extracts high-resolution timing information without the cost or complexity of traditional ultra-wideband approaches. In a complex environment, 90% of position estimates obtained with Harmonium exhibit less than 31cm of error with an average 9cm of inter-sample noise. In non-line-of-sight conditions (i.e. through-wall), 90% of position error is less than 42cm. The tag draws 75mW when actively transmitting, or 3.9mJ per location fix at the 19Hz update rate. Furthermore, VLSI-based design concepts are identified for a simple, low-power realization of the Harmonium tag to offer a roadmap for the realization of Harmonium concepts in future integrated systems. Harmonium introduces a new design point for indoor localization and enables localization of small, fast objects such as micro quadrotors, devices previously restricted to expensive optical systems.

Democratizing Authority in the Built Environment

Operating systems and applications in the built environment have relied upon central authorization and management mechanisms which restrict their scalability, especially with respect to administrative overhead. We propose a new set of primitives encompassing syndication, security, and service execution that unifies the management of applications and services across the built environment, while enabling participants to individually delegate privilege across multiple administrative domains with no loss of security or manageability. We show how to leverage a decentralized authorization syndication platform to extend the design of building operating systems beyond the single administrative domain of a building. The authorization system leveraged is based on blockchain smart contracts to permit decentralized and democratized delegation of authorization without central trust. Upon this, a publish/subscribe syndication tier and a containerized service execution environment are constructed. Combined, these mechanisms solve problems of delegation, federation, device protection and service execution that arise throughout the built environment. We leverage a high-fidelity city-scale emulation to verify the scalability of the authorization tier, and briefly describe a prototypical democratized operating system for the built environment using this foundation.

AutoCalib: Automatic Traffic Camera Calibration at Scale

Emerging smart cities are typically equipped with thousands of outdoor cameras. However, these cameras are typically not calibrated, i.e., information such as their precise mounting height and orientation is not available. Calibrating these cameras allows measurement of real-world distances from the video, thereby, enabling a wide range of novel applications such as identifying speeding vehicles, city road planning, etc. Unfortunately, robust camera calibration is a manual process today and is not scalable. In this paper, we propose AutoCalib, a system for scalable, automatic calibration of traffic cameras. AutoCalib exploits deep learning to extract selected key-point features from car images in the video and uses a novel filtering and aggregation algorithm to automatically produce a robust estimate of the camera calibration parameters from just hundreds of samples.We have implemented AutoCalib as a service on Azure that takes in a video segment and outputs the camera calibration parameters. Using video from real-world traffic cameras, we show that AutoCalib is able to estimate real-world distances with an error of less than 12%

Design and Analysis of a Query Processor for Brick

Brick is a recently proposed metadata schema and ontology for describing building components and the relationships between them. It represents buildings as directed labeled graphs using the RDF data model. Using the SPARQL query language, building-agnostic applications query a Brick graph to discover the set of resources and relationships they require to operate. Latency-sensitive applications, such as user interfaces, demand response and model-predictive control, require fast queries --- conventionally less than 100ms. We benchmark a set of popular open-source and commercial SPARQL databases against three real Brick models using seven application queries and find that none of them meet this performance target. This lack of performance can be attributed to design decisions that optimize for queries over large graphs consisting of billions of triples, but give poor spatial locality and join performance on the small dense graphs typical of Brick. We present the design and evaluation of HodDB, a RDF/SPARQL database for Brick built over a node-based index structure. HodDB performs Brick queries 3-700x faster than leading SPARQL databases and consistently meets the 100ms threshold, enabling the portability of important latency-sensitive building applications. This paper is an extension of a previously published work (same title, published BuildSys 2017).

Opportunistic Spectrum Allocation for Interference Mitigation Amongst Coexisting Wireless Body Area Networks

Wireless Body Area Networks (WBANs) are seen as the enabling technology for developing new generations of medical applications, such as remote health monitoring. As such it is expected that WBANs will predominantly transport mission-critical and delay sensitive data. A key strategy towards building a reliable WBAN is to ensure such networks are highly immune to interference. To achieve this, new and intelligent wireless spectrum allocation strategies are required not only to avoid interference, but also to make bestuse of the limited available spectrum. This paper presents a new spectrum allocation scheme referred to as Smart Channel Assignment (SCA), which maximizes the resource usage and transmission speed by deploying a partially-orthogonal channel assignment scheme between coexisting WBANs as well as offering a convenient trade-off between spectral reuse efficiency, transmission rate and outage. Detailed analytical and experimental studies verify that the proposed SCA strategy is robust to variations in channel conditions, increase in sensor node-density within each WBAN and an increase in number of coexisting WBANs.

Non-Bayesian Social Learning with Observation Reuse and Soft Switching

We propose a non-Bayesian social learning update rule for agents in a network, which minimizes the sum of the Kullback Leibler divergence between the true distribution generating the agents' local observations and the agents' beliefs (parametrized by a hypothesis set), and a weighted varentropy term. The varentropy term allows our update rule to directly control the rate of convergence of our update rule, which also reuses some of the most recent observations of each agent to speed up the convergence. Under mild technical conditions, we show that the belief of each agent concentrates on the optimal hypothesis set, and we derive a bound for the convergence rate. Furthermore, in order to overcome the performance degradation due to misinforming agents, who use a corrupted likelihood functions in their belief updates, we propose to use multiple social networks that update their beliefs independently using our update rule, and a convex combination mechanism among the beliefs of all the networks. Simulation results demonstrate that our proposed algorithms offer significant improvements over two other current state-of-the art non-Bayesian social learning algorithms.

Exploiting Electrical Grid for Accurate and Secure Clock Synchronization

Desynchronized clocks among network nodes in critical infrastructures can degrade system performance and even lead to safety incidents. Clock synchronization protocols based on network message exchanges, though widely used in current network systems, are susceptible to delay attacks against the packet transmission. This vulnerability cannot be solved by conventional security measures such as encryption, and remains an open problem. This paper proposes to use the sine voltage waveform of a utility power grid to synchronize network nodes connected to the same grid. Our experiments demonstrate that minute fluctuations of the voltage's cycle length encode fine-grained global time information in a city-scale utility grid. Based on this key result, we develop a clock synchronization approach that achieves sub-ms accuracy and is provably secure against packet delay attacks. Implementation results show that our approach achieves microsecond accuracy within a building floor and achieves an average synchronization error of 0.1ms between two network nodes that are 10km apart. When the proposed system is deployed within the same floor of a building, the error reduces to 10us.

Natural Timestamps in Powerline Electromagnetic Radiation

The continuous fluctuation of electric network frequency (ENF) presents a fingerprint indicative of time, which we call natural timestamp. This paper studies the time accuracy of these natural timestamps obtained from powerline electromagnetic radiation (EMR), which is mainly excited by powerline voltage oscillations at the rate of the ENF. However, since the EMR signal is often weak and noisy, extracting the ENF is challenging, especially on resource-limited sensor platforms. We design an efficient EMR conditioning algorithm and evaluate the time accuracy of EMR natural timestamps on two representative classes of IoT platforms  a high-end single-board computer with a customized EMR antenna and a low-end mote with a normal conductor wire acting as EMR antenna. Extensive measurements at six sites in a city, which are away from each other for up to 24 km, show that the high-end and low-end nodes achieve median time errors of about 50 ms and 150 ms, respectively. To demonstrate the use of the EMR natural timestamps, we discuss three applications, namely, time recovery, run-time clock verification, and secure clock synchronization.

Flux: a platform for dynamically reconfigurable mobile crowd-sensing

Flux is a platform for dynamically reconfigurable crowd-sensing using mobile devices, programmed under a notion of region-based sensing. Each region is defined by a set of physical constraints that determine the sensing scope, e.g., based on device position or other environmental variables, plus a set of periodic tasks that perform the actual sensing. The resulting behavior is inherently dynamic: as a device's state changes, e.g. moves in space, it enters and/or leaves different regions, thereby changing the set of active tasks; moreover, regions can be added, deleted, and reprogrammed on-the-fly. Flux makes use of a domain-specific language for sensing tasks that is compiled into abstract bytecode, later executed by a low-footprint virtual machine within a device, guaranteeing runtime safety by construction. For region dissemination, Flux employs a broker which holds a centralised (but changeable) region configuration plus gateways that mirror the configuration throughout different network access points to which devices connect. Sensing data is streamed by devices to gateways and then back to the broker. Live or archived data streams are in turn fed by the broker to data processing clients, that interface with the broker using a publish/subscribe API. Two case-study experiments illustrate \flux{} at work.

Differentiating Clear Channel Assessment using Transmit Power Variation

Clear Channel Assessment (CCA) is a core element of Wireless Sensor Network (WSN) Medium Access Control (MAC) protocols which is used on transmitter and receiver side. Current CCA implementations cannot determine the device type occupying the media, leaving nodes unable to differentiate between WSN traffic and interference. However, this would be valuable as MAC protocols benefit from reacting differently depending on the channel occupier. In this paper we describe a method called Power Differentiating Clear Channel Assessment (P-DCCA). Transmitters vary the output power of the radio while the packet is being sent. Receivers are able to identify signals with this characteristic, enabling a Differentiating Clear Channel Assessment (DCCA) check to reveal if the medium is currently occupied by WSN traffic or other interference. We present an implementation and thorough evaluation of P-DCCA. Using ContikiMAC as example we describe how P-DCCA can be integrated within Medium Access Control (MAC) protocols. We show via large-scale testbed experiments and deployments that P-DCCA enabled networks have a significant improved performance. For example, we show that a P-DCCA enabled network can improve Packet Reception Rate (PRR) by up to a factor of 10 while reducing energy usage by over 80% under heavy interference.

Networking Wireless Energy in Embedded Networks

Wireless energy transfer has recently emerged as a promising alternative to realize the long standing vision of perpetual embedded wireless networks. However, this technology transforms the notion of energy from merely a nodes local commodity to, similar to data, a deployment-wide shareable resource. The challenges of managing a shareable energy resource are much more complicated and radically different from the research of the past decade: Besides energy efficient operation of individual devices, we also need to optimize network wide energy distribution. To counteract these challenges, we propose an energy stack, a layered software model for energy management in future transiently powered embedded networks. An initial specification of the energy stack, which is based on the historically successful layered approach for data networking, consists of three layers: (i) the transfer layer; dealing with the physical transfer of energy, (ii) the scheduling layer; optimizing energy distribution over a single hop, and (iii) the network layer; creating a global view of the energy in the network for optimizing its network-wide distribution. As a contribution, we define the interfacing APIs between these layers, delineate their responsibilities, identify corresponding challenges, and provide a first implementation of the energy stack.

Energy-Harvesting Wireless Sensor Networks (EH-WSNs): A Review

Wireless Sensor Networks (WSNs) are crucial in supporting continuous environmental monitoring, where sensor nodes are deployed and must remain operational to collect and transfer data from the environment to a base-station. However, sensor nodes have limited energy in their primary power storage unit, and this energy may be quickly drained if the sensor node remains operational over long periods of time. Therefore, the idea of harvesting ambient energy from the immediate surroundings of the deployed sensors, to recharge the batteries and to directly power the sensor nodes, has recently been proposed. The deployment of energy harvesting in environmental field systems eliminates the dependency of sensor nodes on battery power, drastically reducing the maintenance costs required to replace batteries. In this paper, we review the state-of-the-art in energy harvesting WSNs for environmental monitoring applications including Animal Tracking, Air Quality Monitoring, Water Quality Monitoring, and Disaster Monitoring to improve the ecosystem and human life. In addition to presenting the technologies for harvesting energy from ambient sources and the protocols that can take advantage of the harvested energy, we present challenges that must be addressed to further advance energy harvesting-based WSNs, along with some future work directions to address these challenges.

Integrated coverage and connectivity configuration for energy conservation in sensor networks

VigilNet: An integrated sensor network system for energy-efficient surveillance

Distributed weighted-multidimensional scaling for node localization in sensor networks

Models and solutions for radio irregularity in wireless sensor networks

Radio link quality estimation in wireless sensor networks: A survey

LEAP+: Efficient security mechanisms for large-scale distributed sensor networks

An analysis of unreliability and asymmetry in low-power wireless links

Reputation-based framework for high integrity sensor networks

On the lifetime of wireless sensor networks

Using mobile phones to determine transportation modes

Bibliometrics

Publication Years 2005-2018
Publication Count 490
Citation Count 3879
Available for Download 490
Downloads (6 weeks) 2464
Downloads (12 Months) 20015
Downloads (cumulative) 471118
Average downloads per article 961
Average citations per article 8
First Name Last Name Award
Pankaj Agarwal ACM Fellows (2002)
Saurabh Bagchi ACM Distinguished Member (2013)
ACM Senior Member (2009)
Stefano Basagni ACM Distinguished Member (2015)
ACM Senior Member (2006)
Elisa Bertino ACM Fellows (2003)
Nirupama Bulusu ACM Senior Member (2014)
Jiannong Cao ACM Distinguished Member (2017)
Shigang Chen ACM Distinguished Member (2016)
Jon Crowcroft ACM Fellows (2002)
David Culler ACM Fellows (2002)
Djamel Djenouri ACM Senior Member (2016)
Falko Dressler ACM Senior Member (2009)
Deborah Estrin ACM Athena Lecturer Award (2006)
ACM Fellows (2000)
Johannes Gehrke ACM Fellows (2014)
Erol Gelenbe ACM Fellows (2001)
Phillip B Gibbons ACM Fellows (2006)
Ramesh Govindan ACM Fellows (2011)
Leonidas J Guibas ACM AAAI Allen Newell Award (2007)
ACM Fellows (1999)
Rajesh Gupta ACM Fellows (2016)
Jiawei Han ACM Fellows (2003)
Wendi Beth Heinzelman ACM Distinguished Member (2012)
ACM Senior Member (2009)
Ahmed A Helmy ACM Distinguished Member (2014)
ACM Senior Member (2012)
Mary Jane Irwin ACM Athena Lecturer Award (2010)
ACM Distinguished Service Award (2005)
ACM Fellows (1996)
Sitharama Iyengar ACM Fellows (2001)
Michael I. Jordan ACM Fellows (2010)
ACM AAAI Allen Newell Award (2009)
Anne-Marie Kermarrec ACM Fellows (2016)
Jon Kleinberg ACM AAAI Allen Newell Award (2014)
ACM Fellows (2013)
ACM Prize in Computing (2008)
Ajay Kshemkalyani ACM Distinguished Member (2009)
ACM Senior Member (2009)
Ming Li ACM Fellows (2006)
Xiang-Yang Li ACM Distinguished Member (2014)
Yingshu Li ACM Senior Member (2017)
Yunhao Liu ACM Fellows (2015)
Yunhao Liu ACM Presidential Award (2013)
Prasant Misra ACM Senior Member (2017)
Klara Nahrstedt ACM Fellows (2012)
Peng Ning ACM Senior Member (2007)
David Peleg ACM Fellows (2016)
K. K. Ramakrishnan ACM Fellows (2017)
Krithivasan Ramamritham ACM Fellows (2001)
Daniela Rus ACM Fellows (2014)
Sartaj K Sahni ACM Karl V. Karlstrom Outstanding Educator Award (2003)
ACM Fellows (1996)
Alberto Luigi Sangiovanni Vincentelli ACM Fellows (2014)
Rijurekha Sen ACM India Doctoral Dissertation Award (2014)
Lui Sha ACM Fellows (2005)
Cyrus Shahabi ACM Distinguished Member (2009)
Prashant J Shenoy ACM Distinguished Member (2009)
ACM Senior Member (2006)
Prasun Sinha ACM Distinguished Member (2016)
John A Stankovic ACM Fellows (1996)
Subhash Suri ACM Fellows (2010)
ACM Distinguished Member (2007)
Gene Tsudik ACM Fellows (2014)
ACM Senior Member (2013)
Martin Vetterli ACM Fellows (2009)
Isabel Wagner ACM Senior Member (2017)
Yu Wang ACM Senior Member (2011)
Matt Welsh ACM Senior Member (2009)
Emmerich Welzl ACM Fellows (1998)
Jie Wu ACM Senior Member (2006)
Qiang Yang ACM Fellows (2017)
ACM Distinguished Member (2011)
HongJiang Zhang ACM Fellows (2007)
Ying Zhang ACM Senior Member (2009)
Gang Zhou ACM Senior Member (2013)
Albert Zomaya ACM Distinguished Member (2006)

First Name Last Name Paper Counts
Guoliang Xing 15
Tian He 14
Tarek Abdelzaher 10
John Stankovic 7
Mani Srivastava 7
Gang Zhou 6
Rui Tan 5
Jie Gao 5
Ramesh Govindan 5
Peng Ning 5
Xiaorui Wang 5
Xiaohua Jia 4
Radu Stoleru 4
Yunhao Liu 4
Sajal Das 4
Sencun Zhu 4
Wenliang Du 4
Subhash Suri 4
Anurag Kumar 4
Luca Mottola 4
Dan Wang 4
Qing Cao 4
Shan Lin 4
Ioannis Paschalidis 4
Kamin Whitehouse 4
Deborah Estrin 4
Radha Poovendran 4
Raja Jurdak 4
Marimuthu Palaniswami 4
Jeonggil Ko 4
Nageswara Rao 4
Xiaodong Wang 4
Alberto Cerpa 4
Jiannong Cao 4
Lance Kaplan 4
Jiangchuan Liu 3
Rajesh Gupta 3
Jinzhu Chen 3
Bhaskaran Raman 3
Mo Li 3
Yu Wang 3
Branislav Kusy 3
Hongbo Jiang 3
Omprakash Gnawali 3
Simon Dobson 3
Guiling Wang 3
Yuchee Tseng 3
Jeongyeup Paek 3
Upamanyu Madhow 3
Chris Bleakley 3
Qian Zhang 3
Wensheng Zhang 3
Lin Gu 3
Twan Basten 3
Elisa Bertino 3
Ryo Sugihara 3
Liqian Luo 3
Daniela Rus 3
Utz Roedig 3
David Yau 3
Sanjay Jha 3
Yu Gu 3
Thomas La Porta 3
Yunhuai Liu 3
Bhaskar Krishnamachari 3
Chenyang Lu 3
Wade Trappe 3
Jiming Chen 3
Anne Kermarrec 3
Cormac Sreenan 3
Wendi Heinzelman 3
Andrew Campbell 3
Li Xiao 3
Sutharshan Rajasegarar 3
Jennifer Hou 3
Rik Sarkar 3
Mark Hansen 3
Shane Eisenman 3
Anish Arora 3
Loukas Lazos 3
Xiaobing Wu 3
Francesco Restuccia 3
Gregory O'Hare 2
Aldar Chan 2
Jeroen Doumen 2
Indranil Gupta 2
Julie McCann 2
Behnam Dezfouli 2
Marjan Radi 2
Desheng Zhang 2
Abu Kamal 2
Alex Rogers 2
Fred Cohen 2
Douglas Stinson 2
Anis Koubâa 2
Rong Zheng 2
Nadjib Badache 2
Yanyong Zhang 2
Deokwoo Jung 2
Yingshu Li 2
Nicholas Jennings 2
Wolf Pöttner 2
Miguel Carreira-Perpiñán 2
Neal Patwari 2
Yeewei Law 2
David Smith 2
Matthew Johnson 2
Suyoung Yoon 2
Patrick Tague 2
Chiehyih Wan 2
Antonio Ruzzelli 2
Bogdan Carbunar 2
Pei Zhang 2
Yainwhar Si 2
Hengchang Liu 2
Daniele Midi 2
Edward Coyle 2
Tao Liu 2
Thomas Wettergren 2
Zhenjiang Li 2
Keith Martin 2
Michele Rossi 2
Rui Tan 2
Affan Syed 2
Dong Guo 2
Wenbo He 2
Sanjeev Setia 2
Diethelm Ostry 2
Carlo Fischione 2
Md Razzaque 2
Gul Agha 2
Pedro Marrón 2
Rajesh Panta 2
Nithya Ramanathan 2
Habib Ammari 2
Philip Levis 2
Ilker Demirkol 2
Pankaj Agarwal 2
Steven Gortler 2
Pieter Hartel 2
Ting Yan 2
Chen Wang 2
Jie Dong 2
Mallikarjun Shankar 2
Chatschik Bisdikian 2
Maura Paterson 2
Faramarz Fekri 2
Andreas Savvides 2
Lui Sha 2
Marc Geilen 2
Mehul Motani 2
Ronghua Wang 2
Pascal Vicaire 2
Donggang Liu 2
Frank Mokaya 2
Sehang Cheong 2
Xianjin Zhu 2
Yong Yang 2
Laura Balzano 2
Neeraj Jaggi 2
Russell Costa 2
Qingfeng Huang 2
Yafeng Wu 2
Falko Dressler 2
Shucheng Yu 2
Chiara Petrioli 2
Konrad Iwanicki 2
Hongjiang ZHANG 2
Andreas Meier 2
Mihail Sichitiu 2
David Brady 2
Michael Segal 2
Wilfried Philips 2
Hairong Qi 2
Gian Picco 2
Robert Pless 2
Deepak Ganesan 2
Thomas La Porta 2
Chuntung Chou 2
Guohong Cao 2
James Brown 2
Wen Hu 2
Saurabh Bagchi 2
Claude Castelluccia 2
Wenzhan Song 2
Dheeraj Kumar 2
Rong Zheng 2
Kevin Ni 2
Mahmut Karakaya 2
Mohamed Younis 2
Sajal Das 2
Paul Havinga 2
Wenyuan Xu 2
Jianxun Wang 2
Thomas Kunz 2
Xue Liu 2
Majid Nabi 2
Christina Fragouli 2
Lu Su 2
Guihai Chen 2
Chifu Huang 2
Marco Zamalloa 2
Eddie Kohler 2
Theodore Brown 2
Christos Anagnostopoulos 2
Prabal Dutta 2
John Hicks 2
Hamid Aghajan 2
Sushil Jajodia 2
Lars Wolf 2
Ákos Lédeczi 2
János Sallai 2
Koen Langendoen 2
Peter Corke 2
Gregory Pottie 2
Samir Das 2
Dong Xuan 2
Sudha Krishnamurthy 2
Nisheeth Shrivastava 2
Md Bhuiyan 2
Shusen Yang 2
Ashutosh Sabharwal 2
Sitharama Iyengar 2
Gene Tsudik 2
Marwan Krunz 2
Sol Lederer 2
Djamel Djenouri 2
Stathes Hadjiefthymiades 2
Xiaobo Tan 2
Mingyan Liu 2
Yong Liu 2
Guang Tan 2
Pangun Park 2
Felix Büsching 2
Péter Völgyesi 2
Ziguo Zhong 1
Leonardo Bobadilla 1
Alireza Ghaffarkhah 1
Alejandro Frery 1
Amotz Bar-Noy 1
Jin Teng 1
Antônio Loureiro 1
Jing Dong 1
Sirin Tekinay 1
Yin Chen 1
Geyong Min 1
Mario Strasser 1
Boris Danev 1
Yuanchao Shu 1
Rashid Ansari 1
Athanasios Vasilakos 1
Bingsheng He 1
Wenzheng Xu 1
Tom Taylor 1
Bill Moran 1
Zhi Guan 1
Michael Smith 1
Sundeep Pattem 1
Kokkiong Yap 1
Arshad Jhumka 1
Sabrina Sicari 1
Himanshu Gupta 1
Gaurav Mathur 1
Nirupama Bulusu 1
Raghuraman Mudumbai 1
Yue Wang 1
Andreas Lachenmann 1
Foad Dabiri 1
Yu Chen 1
Haohau Chu 1
Simon Wang 1
Chris Crossman 1
Wenjing Lou 1
Katerina Argyraki 1
Kaiqi Xiong 1
Somnath Mitra 1
Maarten Van Steen 1
Santosh Kumar 1
Cecilia Mascolo 1
Bence Pásztor 1
Wook Choi 1
Sanem Kabadayı 1
Yong Yao 1
Xun Su 1
Prasanna Ballal 1
Srinivasagopalan Srivathsan 1
Alon Efrat 1
Yibei Ling 1
Zainul Charbiwala 1
Xue Liu 1
Xiaoye Jiang 1
João Hespanha 1
Jerry Burman 1
Jie Gao 1
Tao He 1
Koushik Kar 1
Adrian Munteanu 1
Jürgen Slowack 1
Peter Van Hese 1
Jorge Niño-Castañeda 1
B Manjunath 1
Mikhail Afanasyev 1
Sinan Isik 1
Yonghong Tan 1
Xi Ju 1
Lili Wang 1
João Barros 1
Johnsen Kho 1
Jan Hauer 1
Ming Xia 1
Azzedine Boukerche 1
Jun Liu 1
Weijia Jia 1
Varick Erickson 1
Kiyoung Jang 1
Matteo Ceriotti 1
Periklis Liaskovitis 1
Curt Schurgers 1
Zhu Han 1
Miloud Bagaa 1
Srdjan Čapkun 1
Erol Gelenbe 1
Ying Zhang 1
Lu Ruan 1
Amin Rasekh 1
Mo’taz Al-Hami 1
Douglas Cochran 1
Ulf Kulau 1
Hungmin Sun 1
Babak Shirmohammadi 1
Giacomo Ghidini 1
Vladimir Dyo 1
Ting Zhu 1
Sagar Bijwe 1
Yuan Zhou 1
Younghun Kim 1
Sarangapani Jagannathan 1
David Culler 1
Paweł Gburzyński 1
Xiaohui Liu 1
Domenic Forte 1
Ankur Srivastava 1
Hanan Shpungin 1
Jangping Sheu 1
Tingyu Wang 1
Manuel Roveri 1
Jiajun Bu 1
Wei Dong 1
Michał Ren 1
Marcel Steine 1
Michael LeMay 1
Bernard Mulgrew 1
Deukhyoun Heo 1
Elizabeth Basha 1
Sharadh Ramaswamy 1
Richard Cagley 1
Marin Bertier 1
Weidong Shi 1
Venu Vasudevan 1
Richard Brooks 1
Martin Vetterli 1
Emanuele Viterbo 1
Aqeel Kazmi 1
Min Mun 1
Donnie Kim 1
Liqun Li 1
Dong Liang 1
Benjamin Gaudette 1
Bijun Li 1
Spyros Voulgaris 1
Mengfan Shan 1
Leonid Barenboim 1
Haosheng Fan 1
Xianwei Sun 1
Yamina Shams 1
Amarjeet Singh 1
Davide Zordan 1
Shameek Bhattacharjee 1
Hayder Radha 1
Muhammad Alizai 1
Ivan Minakov 1
Uichin Lee 1
Junehwa Song 1
Richard Martin 1
Kaiwei Fan 1
Bin Tang 1
Rohini Kurkal 1
Ted Lai 1
Shankar Sastry 1
Lorenzo Keller 1
Novella Bartolini 1
Yaron Lipman 1
Santanu Guha 1
Habib Youssef 1
Carlo Boano 1
Kharsim Yousef 1
Chieh Liang 1
Yin Chen 1
Andreas Terzis 1
Jun Zhang 1
Di Ma 1
Priya Kasirajan 1
Marco Caccamo 1
Jinling Liang 1
Yinyu Ye 1
Huailei Fu 1
Xiaolong Huang 1
Antonio Marullo 1
Pengfei Zhou 1
Yuanqing Zheng 1
Weichih Liao 1
Vahid Salmani 1
Qingsi Wang 1
Marek Klonowski 1
Kumar Viswanatha 1
Ankur Saxena 1
Cristina Pinotti 1
Xing Fu 1
Kui Ren 1
Jaspreet Singh 1
Yang Yu 1
Marc Parlange 1
Pablo Soldati 1
Deborah Estrin 1
Yan Liu 1
Nihat Altiparmak 1
Sanghyuk Son 1
Avinash Kalyanaraman 1
Carlos Ruiz 1
Zheng Sun 1
Ali Jaber 1
Gang Li 1
Yulan Guo 1
Zhong Liu 1
Eisa Zarepour 1
Zhipeng Cai 1
Xu Ning 1
Abhishek Sharma 1
Stefano Soatto 1
Jing Wang 1
William Plishker 1
Cunqing Hua 1
Deep Medhi 1
John Mitchell 1
Kyle Jamieson 1
Alexander Dean 1
Gaurav Sukhatme 1
Nicholas Lane 1
Gahngseop Ahn 1
Sorabh Gandhi 1
Wei Yu 1
Carlos Guestrin 1
Samuel Midkiff 1
Dylan Thurston 1
Tianqi Wang 1
Bülent Tavli 1
Yu Wang 1
Laukik Chitnis 1
Phillip Gibbons 1
Kafai Yiu 1
Kongyang Chen 1
Yawei Zhao 1
Zhen Peng 1
Lorenzo Taponecco 1
Heejung Yoon 1
Naveen Aggarwal 1
Mahima Choudhary 1
Rajnish Kumar 1
Brian Cooper 1
Tarik Tabet 1
Peter Kinget 1
Tan Yan 1
Adriano Branco 1
Yongtae Park 1
Andrew Sugaya 1
Costas Busch 1
Heikki Karvonen 1
Matthew Dobson 1
Xiaojun Zhu 1
Sriram Premnath 1
Bugong Xu 1
Gruia Roman 1
Sangeeta Bhattacharya 1
Miklós Maróti 1
Sebestyén Dóra 1
David Nguyen 1
Guanghui He 1
XuanLong Nguyen 1
Bin He 1
Parth Pathak 1
Timothy Scott 1
Ji Li 1
Mohammad Rahimi 1
Abtin Keshavarzian 1
Prasant Misra 1
Shibo He 1
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Paulo Gil 1
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Prabal Dutta 1
Qishi Wu 1
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Gunnar Schaefer 1
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Euhanna Ghadimi 1
Ali Tosun 1
Dora Spenza 1
Gong Zhang 1
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Jeffrey Kharoufeh 1
Vinay Hanumaiah 1
Rüdiger Kapitza 1
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Chinjung Liu 1
Rafail Ostrovsky 1
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Myounggyu Won 1
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Mort Naraghi-Pour 1
Shashi Prabh 1
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Lanny Sitanayah 1
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Sharon Coe 1
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Jie Wu 1
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Saewoong Bahk 1
Antonio D'Amico 1
Sokratis Kartakis 1
Taejoon Park 1
Mohammad Moazzami 1
Behnaam Aazhang 1
Arnab Chakrabarti 1
Alex Kesselman 1
Azad Ali 1
Shaohan Hu 1
Ioannis Kymissis 1
Baradwaj Vigraham 1
Roberto Ierusalimschy 1
Kaushik Chowdhury 1
Jihun Ha 1
Wendi Heinzelman 1
Mukundan Sridharan 1
Mo Li 1
Yucel Altunbasak 1
D Manjunath 1
Tarik Arici 1
Konstantinos Psounis 1
Cyrus Shahabi 1
Sunhee Yoon 1
David Forrester 1
Zhaohui Yuan 1
Tal Anker 1
Mo Li 1
Yi Yang 1
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Saurabh Ganeriwal 1
Xin Yao 1
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Santhoshkumar Sunderrajan 1
Carter De Leo 1
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Hongwei Zhang 1
Xin Che 1
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Matthew Miller 1
Dong Wang 1
Michael Hamilton 1
Matthias Gauger 1
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Youxian Sun 1
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Ricardo Silva 1
David Moss 1
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Jose Cecilio 1
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Chao Wang 1
Hailun Tan 1
Beakcheol Jang 1
Aman Kansal 1
Ronald Peterson 1
Vana Kalogeraki 1
Kung Yao 1
Mo Sha 1
Octavian Carbunar 1
Ananth Grama 1
Jan Vitek 1
Alfred Hero, 1
Jose Costa 1
Bo Xie 1
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Seungjun Baek 1
Pablo Peñil 1
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Luis Muñoz-González 1
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Li Chen 1
Stefano Basagni 1
Kofi Adu-Manu 1
Cristiano Tapparello 1
Changda Wang 1
James Ritcey 1
Toygar Akgun 1
Rich Rosasco 1

Affiliation Paper Counts
Indraprastha Institute of Information Technology Delhi 1
INRIA Saclay 1
IBM United Kingdom Limited 1
IMDEA Networks Institute 1
Ministry of Public Security of the People's Republic of China 1
Fujian Normal University 1
Singapore Management University 1
Tianjin University 1
Graz University of Technology 1
Kennesaw State University 1
University of Paderborn 1
University of Calabria 1
Catholic University of America 1
University of Louisville 1
Sun Yat-Sen University 1
University of Greenwich 1
The University of Warwick 1
Shanghai Normal University 1
Technion - Israel Institute of Technology 1
Frostburg State University 1
University of Connecticut 1
University of Delaware 1
Portland State University 1
University of Pannonia 1
South China University of Technology 1
Hanyang University 1
University of Tokyo 1
University of Thessaly 1
Broadcom Corporation 1
Lawrence Livermore National Laboratory 1
Zhejiang University of Technology 1
Qufu Normal University 1
University of Exeter 1
University of Edinburgh 1
Universite de Pau et des Pays de L'Adour 1
Technical University of Madrid 1
City College of New York 1
Kadir Has University 1
Southern Illinois University at Carbondale 1
TOBB University of Economics and Technology 1
University of Missouri-St. Louis 1
Free University of Berlin 1
California State University Los Angeles 1
University of Patras 1
Curtin University of Technology, Perth 1
Teledyne Technologies 1
Utah State University 1
Universite de Nantes 1
University of Kuwait 1
Lahore University of Management Sciences 1
University of Sousse 1
University of Szeged Bolyai Institute 1
Gwangju Institute of Science and Technology 1
University of Sciences and Technology Houari Boumediene 1
Jiangsu University of Science and Technology 1
Naval University of Engineering 1
National University of Computer and Emerging Sciences Islamabad 1
Berlin Museum of Natural Sciences 1
SAP AG 1
Cyprus University of Technology 1
Community Based Medical College, Bangladesh 1
New York Institute of Technology 1
Huawei Technologies Co., Ltd. 1
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Ohio State University 25
Stony Brook University 27
Purdue University 40
University of Illinois at Urbana-Champaign 44
University of Virginia 44
Michigan State University 45
University of California, Los Angeles 58

ACM Transactions on Sensor Networks (TOSN)
Archive


2018
Volume 14 Issue 2, March 2018  Issue-in-Progress
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2017
Volume 13 Issue 4, December 2017
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2016
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2015
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2014
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2013
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2012
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2011
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2010
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2009
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2008
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2007
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2006
Volume 2 Issue 4, November 2006
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2005
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