Demo Data from VLDB 2026 / reviewers in the wild / expert
Jeremy Elson
dblp:02/3927
· DBLP profile ↗
26ranked-venue papers
7as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 8 · 1 first-authorSystems, architecture and hardware · 7 · 3 first-authorSoftware engineering, systems software and programming languages · 4 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2Applied, interdisciplinary, general and emerging computing · 2Artificial intelligence and machine learning · 1Security and privacy · 1 · 1 first-authorDatabases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous computing · 1Theory of computation · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
10 papers |
Cloud and datacenter computing · 36% Storage systems · 24% Distributed systems · 19% | |
| Computer networks
8 papers |
Internet of things and sensor networks · 77% Internet architecture and protocols · 14% Wireless sensing and localization · 7% | |
| Software engineering, system software, and programming languages
3 papers |
Operating systems · 71% Debugging and program repair · 29% | |
| Network and information security
2 papers |
Authentication and access control · 41% Usable security · 41% Web and mobile security · 18% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 30 heaviest of 37, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
cluster resource management and scheduling |
0.2 | 1 | 2016 | Slicer: Auto-Sharding for Datacenter Applications · OSDI 2016 |
Operating systems › resource management › process management
application launch |
0.2 | 1 | 2014 | Missive: Fast Application Launch From an Untrusted Buffer Cache · USENIX ATC 2014 |
Storage systems › storage architecture › block storage
cloud block storage |
0.2 | 1 | 2014 | Blizzard: Fast, Cloud-scale Block Storage for Cloud-oblivious Applications · NSDI 2014 |
Cloud and datacenter computing
datacenter storage |
0.1 | 1 | 2012 | Flat Datacenter Storage · OSDI 2012 |
Internet of things and sensor networks
wireless sensor network |
0.1 | 3 | 2004 | Methods for Scalable Self-Assembly of Ad Hoc Wireless Sensor Networks · IEEE Trans. Mob. Comput. 2004 EmStar: A Software Environment for Developing and Deploying Wireless Sensor Networks · USENIX ATC, General Track 2004 Coherent acoustic array processing and localization on wireless sensor networks · Proc. IEEE 2003 |
Parallel and multicore computing › parallel computation models
massively parallel computation |
0.1 | 1 | 2010 | The Utility Coprocessor: Massively Parallel Computation from the Coffee Shop · USENIX ATC 2010 |
Processor architecture and microarchitecture
speculative execution |
0.1 | 1 | 2010 | Crom: Faster Web Browsing Using Speculative Execution · NSDI 2010 |
Visualization and visual analytics
geospatial visualization |
0.1 | 1 | 2008 | Do I live in a flood basin?: synthesizing ten thousand maps · CHI 2008 |
Distributed systems
fault tolerance |
0.1 | 1 | 2008 | Handling Flash Crowds from Your Garage · USENIX ATC 2008 |
Distributed systems
replication |
0.1 | 1 | 2016 | Slicer: Auto-Sharding for Datacenter Applications · OSDI 2016 |
Distributed systems › distributed database
sharding |
0.1 | 1 | 2016 | Slicer: Auto-Sharding for Datacenter Applications · OSDI 2016 |
Authentication and access control › human interactive proofs
CAPTCHA |
0.1 | 1 | 2007 | Asirra: a CAPTCHA that exploits interest-aligned manual image categorization · CCS 2007 |
Internet of things and sensor networks › wireless sensor network
sensor network applications |
0.1 | 1 | 2006 | Tinker: a tool for designing data-centric sensor networks · IPSN 2006 |
Internet of things and sensor networks › wireless sensor network
sensor network simulation |
0.1 | 1 | 2006 | Tinker: a tool for designing data-centric sensor networks · IPSN 2006 |
Storage systems › buffer management
buffer cache management |
0.1 | 1 | 2014 | Missive: Fast Application Launch From an Untrusted Buffer Cache · USENIX ATC 2014 |
Storage systems
virtual storage |
0.1 | 1 | 2014 | Blizzard: Fast, Cloud-scale Block Storage for Cloud-oblivious Applications · NSDI 2014 |
Internet architecture and protocols › network topology
hierarchical network topology |
0.0 | 1 | 2004 | Methods for Scalable Self-Assembly of Ad Hoc Wireless Sensor Networks · IEEE Trans. Mob. Comput. 2004 |
Internet of things and sensor networks › wireless sensor network
self-organization |
0.0 | 1 | 2004 | Methods for Scalable Self-Assembly of Ad Hoc Wireless Sensor Networks · IEEE Trans. Mob. Comput. 2004 |
Internet of things and sensor networks › wireless sensor network
wireless sensor network platform |
0.0 | 1 | 2004 | Demonstration of EmStar · SenSys 2004 |
Cloud and datacenter computing › cluster resource management and scheduling
cluster resource management |
0.0 | 1 | 2012 | Flat Datacenter Storage · OSDI 2012 |
Wireless sensing and localization
acoustic source localization |
0.0 | 1 | 2003 | Coherent acoustic array processing and localization on wireless sensor networks · Proc. IEEE 2003 |
Internet of things and sensor networks › time synchronization
sensor network time synchronization |
0.0 | 1 | 2002 | Fine-Grained Network Time Synchronization Using Reference Broadcasts · OSDI 2002 |
Internet architecture and protocols › world wide web › web protocols
HTTP |
0.0 | 1 | 2010 | Crom: Faster Web Browsing Using Speculative Execution · NSDI 2010 |
Parallel and multicore computing
parallel computing |
0.0 | 1 | 2010 | The Utility Coprocessor: Massively Parallel Computation from the Coffee Shop · USENIX ATC 2010 |
Cloud and datacenter computing
serverless computing |
0.0 | 1 | 2008 | Handling Flash Crowds from Your Garage · USENIX ATC 2008 |
Computer vision › Image recognition and object detection
image classification |
0.0 | 1 | 2007 | Asirra: a CAPTCHA that exploits interest-aligned manual image categorization · CCS 2007 |
Embedded and real-time systems › wireless communication › wireless sensor networks
sensor network platforms |
0.0 | 1 | 2004 | EmStar: A Software Environment for Developing and Deploying Wireless Sensor Networks · USENIX ATC, General Track 2004 |
Performance modeling and evaluation
simulation and emulation |
0.0 | 1 | 2004 | A system for simulation, emulation, and deployment of heterogeneous sensor networks · SenSys 2004 |
Distributed systems
clock synchronization |
0.0 | 1 | 2003 | Coherent acoustic array processing and localization on wireless sensor networks · Proc. IEEE 2003 |
Wireless networking
wireless network protocols |
0.0 | 1 | 2002 | Fine-Grained Network Time Synchronization Using Reference Broadcasts · OSDI 2002 |
Methods — techniques the papers use, named apart from their topics
speculative execution · 0.2user-task taxonomy · 0.2interviews · 0.2simulation · 0.2manual image categorization · 0.1flat datacenter storage · 0.1visualization · 0.1emulation · 0.1maximum likelihood estimation · 0.1least-squares estimation · 0.1beamforming · 0.1high-level design tool · 0.1implementation · 0.0dual-radio architecture · 0.0time-delay estimation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Slicer: Auto-Sharding for Datacenter Applications
Atul Adya, Daniel Myers, Jon Howell, Jeremy Elson, Colin Meek, Vishesh Khemani, Stefan Fulger, Pan Gu, Lakshminath Bhuvanagiri, Jason Hunter, Roberto Peon, Larry Kai, Alexander Shraer, Arif Merchant, Kfir Lev-Ari |
OSDI | 4 |
| 2014 | Blizzard: Fast, Cloud-scale Block Storage for Cloud-oblivious Applications
James W. Mickens, Ed Nightingale, Jeremy Elson, Darren Gehring, Asim Kadav, Vijay Chidambaram, Krishna Nareddy |
NSDI | 3 |
| 2014 | Missive: Fast Application Launch From an Untrusted Buffer Cache
Jon Howell, Jeremy Elson, Bryan Parno, John R. Douceur |
USENIX ATC | 2 |
| 2012 | Flat Datacenter Storage
Ed Nightingale, Jeremy Elson, Jinliang Fan, Owen S. Hofmann, Jon Howell, Yutaka Suzue |
OSDI | 2 |
| 2010 | Mugshot: Deterministic Capture and Replay for JavaScript Applications
James W. Mickens, Jeremy Elson, Jon Howell |
NSDI | 2 |
| 2010 | Crom: Faster Web Browsing Using Speculative Execution
James W. Mickens, Jeremy Elson, Jon Howell, Jacob R. Lorch |
NSDI | 2 |
| 2010 | The Utility Coprocessor: Massively Parallel Computation from the Coffee Shop
John R. Douceur, Jeremy Elson, Jon Howell, Jacob R. Lorch |
USENIX ATC | 2 |
| 2008 | Do I live in a flood basin?: synthesizing ten thousand mapsabstractThe recent introduction of simple, web-based geographic visualization interfaces has unleashed a tidal wave of new geographic content now available on the Internet. There has been enormous attention on the development of data interchange standards and programming interfaces that make all this content interoperable, but far less thought about how the user experience should change when users have their choice of 10,000 maps.To inform the design of online mapping systems, we investigate the case of queries that require correlation of multiple maps---that is, discovery and synthesis of several map layers. We based our study on interviews with expert users of maps: archivists and librarians. This paper describes our user-task taxonomy distilled from these interviews, and presents MapSynthesizer, a prototype system that allows users to efficiently query, discover, and integrate many maps from a corpus of thousands. Miguel Elías, Jeremy Elson, Danyel Fisher, Jon Howell |
CHI | 2 |
| 2008 | Low-cost orthographic imageryabstractCommercial aerial imagery websites, such as Google Maps, MapQuest, Microsoft Virtual Earth, and Yahoo! Maps, provide high- seamless orthographic imagery for many populated areas, employing sophisticated equipment and proprietary image postprocessing pipelines. There are many areas of the world with poor coverage where locals might benefit from recent, high-resolution orthographic imagery, but which do not fit into the schedules and scaling model of the big sites. Péter Pesti, Jeremy Elson, Jon Howell, Drew Steedly, Matthew Uyttendaele |
GIS | 2 |
| 2008 | Leveraging Legacy Code to Deploy Desktop Applications on the Web
John R. Douceur, Jeremy Elson, Jon Howell, Jacob R. Lorch |
OSDI | 2 |
| 2008 | Handling Flash Crowds from Your Garage
Jeremy Elson, Jon Howell |
USENIX ATC | 1 |
| 2007 | Asirra: a CAPTCHA that exploits interest-aligned manual image categorizationabstractArticle Share on Asirra: a CAPTCHA that exploits interest-aligned manual image categorizationCCS '07: Proceedings of the 14th ACM conference on Computer and communications securityOctober 2007 Pages 366–374https://doi.org/10.1145/1315245.1315291Online:28 October 2007Publication History 51citation868DownloadsMetricsTotal Citations51Total Downloads868Last 12 Months74Last 6 weeks8 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access Jeremy Elson, John R. Douceur, Jon Howell, Jared Saul |
CCS | 1 |
| 2007 | Emstar: A software environment for developing and deploying heterogeneous sensor-actuator networksabstractRecent work in wireless embedded networked systems has followed heterogeneous designs, incorporating a mixture of elements from extremely constrained 8- or 16-bit “Motes” to less resource-constrained 32-bit embedded “Microservers.” Emstar is a software environment for developing and deploying complex applications on such heterogeneous networks. Emstar is designed to leverage the additional resources of Microservers by trading off some performance for system robustness in sensor network applications. It enables fault isolation, fault tolerance, system visiblity, in-field debugging, and resource sharing across multiple applications. In order to accomplish these objectives, Emstar is designed to run as a multiprocess system and consists of libraries that implement message-passing IPC primitives, services that support networking, sensing, and time synchronization, and tools that support simulation, emulation, and visualization of live systems, both real and simulated. We evaluate this work by discussing the Acoustic ENSBox, a platform for distributed acoustic sensing that we built using Emstar. We show that by leveraging existing Emstar services, we are able to significantly reduce development time while achieving a high degree of robustness. We also show that a sample application was developed much more quickly on this platform than it would have been otherwise. Lewis Girod, Nithya Ramanathan, Jeremy Elson, Thanos Stathopoulos, Martin Lukac, Deborah Estrin |
ACM Trans. Sens. Networks | 3 |
| 2006 | Tinker: a tool for designing data-centric sensor networksabstractWe describe Tinker, a high-level design tool that aids the exploration of the design space in sensor network applications. Tinker is targeted at applications that require real-time assignment of semantic meaning to data, rather than just data storage. Tinker lets users write simple programs, as if they were manipulating individual scalar values, and simulates those computations over continuous streams of sensor data. Tinker does not require (or allow) users to specify details such as routing algorithms or retransmission policies, freeing system designers to rapidly iterate among different broad designs before fleshing out details of the one that looks most promising. We demonstrate Tinker's use in the design and deployment of ElevatorNet, our distributed sensor application that retrofits buildings with per-floor displays of an elevator's position, determined using barometric altimetry. Jeremy Elson, Andrew Parker 0001 |
IPSN | 1 |
| 2004 | Global Synchronization in Sensornets
Jeremy Elson, Richard M. Karp, Christos H. Papadimitriou, Scott Shenker |
LATIN | 1 |
| 2004 | A system for simulation, emulation, and deployment of heterogeneous sensor networksabstractRecently deployed Wireless Sensor Network systems (WSNs) are increasingly following heterogeneous designs, incorporating a mixture of elements with widely varying capabilities. The development and deployment of WSNs rides heavily on the availability of simulation, emulation, visualization and analysis support. In this work, we develop tools specifically to support heterogeneous systems, as well as to support the measurement and visualization of operational systems that is critical to addressing the inevitable problems that crop up in deployment. Our system differs from related systems in three key ways: in its ability to simulate and emulate heterogeneous systems in their entirety, in its extensive support for integration and interoperability between motes and microservers, and in its unified set of tools that capture, view, and analyze real time debugging information from simulations, emulations, and deployments. Lewis Girod, Thanos Stathopoulos, Nithya Ramanathan, Jeremy Elson, Deborah Estrin, Eric Osterweil, Thomas Schoellhammer |
SenSys | 4 |
| 2004 | Demonstration of EmStarabstractNo abstract available. Andrew Parker 0001, Lewis Girod, Thanos Stathopoulos, Jeremy Elson, Richard G. Guy, Deborah Estrin |
SenSys | 4 |
| 2004 | EmStar: A Software Environment for Developing and Deploying Wireless Sensor Networks
Lewis Girod, Jeremy Elson, Alberto Cerpa, Thanos Stathopoulos, Nithya Ramanathan, Deborah Estrin |
USENIX ATC, General Track | 2 |
| 2004 | Methods for Scalable Self-Assembly of Ad Hoc Wireless Sensor NetworksabstractIn distributed wireless sensing applications such as unattended ground sensor systems, remote planetary exploration, and condition-based maintenance, where the deployment site is remote and/or the scale of the network is large, individual emplacement and configuration of the sensor nodes is difficult. Hence, network self-assembly and continuous network self-organization during the lifetime of the network in a reliable, efficient, and scalable manner are crucial for successful deployment and operation of such networks. This paper provides an overview of the concept of network self-assembly for ad hoc wireless sensor networks at the link layer, with descriptions of results from implementation of a novel network formation mechanism for wireless unattended ground sensor applications using a multicluster hierarchical topology and a novel dual-radio architecture. Katayoun Sohrabi, William Merrill, Jeremy Elson, Lewis Girod, Fredric Newberg, William J. Kaiser |
IEEE Trans. Mob. Comput. | 3 |
| 2003 | DSP implementation of a distributed acoustical beamformer on a wireless sensor platformabstractIn this paper, we consider the use of a Compaq iPAQ 3760s, equipped with a built-in microphone and an external wireless card, for acoustic acquisition and processing to perform a distributed acoustical beamforming. Time synchronization among the microphones is achieved by the reference-broadcast synchronization method. Two beamforming algorithms, based on the time difference of arrivals (TDOA) among the microphones followed by a least-squares estimation, and the maximum-likelihood (ML) parameter estimation method, are used to perform source detection, enhancement, localization, delay-steered beamforming, and direction-of-arrival estimation. Experimental beamforming results using the iPAQs and the wireless network are reported. Joe C. Chen, Len Yip, Hanbiao Wang, Daniela Maniezzo, Ralph E. Hudson, Jeremy Elson, Deborah Estrin |
ICASSP (2) | 6 |
| 2003 | Target classification and localization in habitat monitoringabstractWe are developing an acoustic habitat-monitoring sensor network that recognizes and locates specific animal calls in real time. We investigate the system requirements of such a real-time acoustic monitoring network. We propose a system architecture and a set of lightweight collaborative signal processing algorithms that achieve real-time behavior while minimizing inter-node communication to extend the system lifetime. In particular, the target classification is based on spectrogram pattern matching while the target localization is based on beamforming using time difference of arrival (TDOA). We describe our preliminary implementation on a commercial off the shelf (COTS) testbed and present its performance based on testbed measurements. Hanbiao Wang, Jeremy Elson, Lewis Girod, Deborah Estrin |
ICASSP (4) | 2 |
| 2003 | Coherent acoustic array processing and localization on wireless sensor networksabstractAdvances in microelectronics, array processing, and wireless networking have motivated the analysis and design of low-cost integrated sensing, computing, and communicating nodes capable of performing various demanding collaborative space-time processing tasks. In this paper, we consider the problem of coherent acoustic sensor array processing and localization on distributed wireless sensor networks. We first introduce some basic concepts of beamforming and localization for wide-band acoustic sources. A review of various known localization algorithms based on time-delay followed by least-squares estimations as well as the maximum-likelihood method is given. Issues related to practical implementation of coherent array processing, including the need for fine-grain time synchronization, are discussed. Then we describe the implementation of a Linux-based wireless networked acoustic sensor array testbed, utilizing commercially available iPAQs with built-in microphones, codecs, and microprocessors, plus wireless Ethernet cards, to perform acoustic source localization. Various field-measured results using two localization algorithms show the effectiveness of the proposed testbed. An extensive list of references related to this work is also included. Joe C. Chen, Len Yip, Jeremy Elson, Hanbiao Wang, Daniela Maniezzo, Ralph E. Hudson, Deborah Estrin |
Proc. IEEE | 3 |
| 2002 | Locating Tiny Sensors in Time and Space: A Case StudyabstractAs the cost of embedded sensors and actuators drops, new applications will arise that exploit high density networks of small devices capable of a variety of sensing tasks. Although individual devices may have limited functionality, the true value of the system comes from the emergent behavior that arises when data from many places in the system is combined. This type of data fusion has a number of requirements, but two of the most important are: 1) synchronized time, precise enough to resolve movement in the sensed phenomenon (e.g., sound); and 2) known geographic locations, on a similar scale to the sensors' size and deployment density. However, the installation cost of a localization system with sufficient granularity is considerable, because of the large amount of effort required to deploy such a system and make all the measurements required to tune it. In this paper, we describe a system based on COTS components that incorporates our novel time synchronization and acoustic ranging techniques. The result is a low-cost, readily available platform for distributed, coherent signal processing. Lewis Girod, Vladimir Bychkovskiy, Jeremy Elson, Deborah Estrin |
ICCD | 3 |
| 2002 | Fine-Grained Network Time Synchronization Using Reference Broadcasts
Jeremy Elson, Lewis Girod, Deborah Estrin |
OSDI | 1 |
| 2001 | Random, Ephemeral Transaction Identifiers in Dynamic Sensor NetworksabstractRecent advances in miniaturization and low-cost, low-power design have led to active research in large-scale, highly distributed systems of small, wireless, low-power unattended sensors and actuators. We explore the use of Random, Ephemeral TRansaction Identifiers (RETRI) in such systems, and contrast it with the typical design philosophy of using static identifiers in roles such as node addressing or efficient data naming. Instead of using statically assigned identifiers that are guaranteed to be unique, nodes randomly select probabilistically unique identifiers for each new transaction. We show how this randomized scheme can significantly improve the system's energy efficiency in contexts where that efficiency is paramount, such as energy-constrained wireless sensor networks. Benefits are realized if the typical data size is small compared to the size of an identifier, and the number of transactions seen by an individual node is small compared to the number of nodes that exist in the entire system. Our scheme is designed to scale well: identifier sizes grow with a system's density not its overall size. We quantify these benefits using an analytic model that predicts our scheme's efficiency. We also describe an implementation as applied to packet fragmentation and an experiment that validates our model. Jeremy Elson, Deborah Estrin |
ICDCS | 1 |
| 2001 | Time Synchronization for Wireless Sensor NetworksabstractIf one assumes I have not gone insane, credit for this may go to my family, who have provided endless emotional support.In particular, I'd like to thank my parents Norton and Sandy, and siblings Franny and David, for tirelessly being there through success and failure.I must thank Dana for giving me a great reason to be in Santa Monica by 6:17 every Friday, while having patience and understanding during the times that I can't make it.These people are so close to my heart, and have given me such strength and encouragement, that "thank" seems too cold and empty of a word.I'd also like to thank Gary Klapow-his patient instruction has made Michael Althsuler's words (Chapter 10) a literal reality for me.At a time when I felt that my life had been consumed by digital work, he helped me enjoy an old hobby in analog rather than digital form.Finally, I should of course thank Reza, without whom I might have gone down a completely different path.This one has worked out pretty well. Jeremy Elson, Deborah Estrin |
IPDPS | 1 |