Sensor Networks: Next Generation Problems Frank Vernon Scripps Institution of Oceanography University of California at San Diego SAMSI Sensor Network Workshop.

Slides:



Advertisements
Similar presentations
Data Mining and the Web Susan Dumais Microsoft Research KDD97 Panel - Aug 17, 1997.
Advertisements

KANSEI TESTBED OHIO STATE UNIVERSITY. HETEREGENOUS TESTBED Multiple communication networks, computation platforms, multi-modal sensors/actuators, and.
Open problems How can I acquire desired RT data? How can I discover/access desired RT data? How can I share/integrate the data? Can I integrate dynamically?
High Performance Wireless Research and Education Network
DELOS Highlights COSTANTINO THANOS ITALIAN NATIONAL RESEARCH COUNCIL.
Retrieval of Information from Distributed Databases By Ananth Anandhakrishnan.
An Operational Metadata Framework For Searching, Indexing, and Retrieving Distributed GIServices on the Internet By Ming-Hsiang.
Data, Cyberinfrastructure, and Interoperability: Highlights from Infrastructure Studies Florence Millerand, Karen S. Baker, David Ribes *Florence:
LifeSize ® Control ™ 4.0 Regain Control of your Video Communications Network.
1 Cyberinfrastructure Framework for 21st Century Science & Engineering (CF21) IRNC Kick-Off Workshop July 13,
EU-GRID Work Program Massimo Sgaravatto – INFN Padova Cristina Vistoli – INFN Cnaf as INFN members of the EU-GRID technical team.
Chronopolis: Preserving Our Digital Heritage David Minor UC San Diego San Diego Supercomputer Center.
A Platform for WEbS (wireless embedded sensor/actuator) systems David Culler Eric Brewer Dave Wagner.
CS 501: Software Engineering Fall 2000 Lecture 16 System Architecture III Distributed Objects.
CS538: Advanced Topics in Information Systems. 2 Secure Location transparency Consistent Real-Time Available Black Box: Distributed Storage [GMM] ? Data.
Robust Tools for Archiving and Preserving Digital Data Joseph JaJa, Mike Smorul, and Mike McGann Institute for Advanced Computer Studies Department of.
Systems Oceanography: Observing System Design. Why not hard-wire the system? Efficiency of interface management –Hard-wire when component number small,
An Agent-Oriented Approach to the Integration of Information Sources Michael Christoffel Institute for Program Structures and Data Organization, University.
Web-based Portal for Discovery, Retrieval and Visualization of Earth Science Datasets in Grid Environment Zhenping (Jane) Liu.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
V. Chandrasekar (CSU), Mike Daniels (NCAR), Sara Graves (UAH), Branko Kerkez (Michigan), Frank Vernon (USCD) Integrating Real-time Data into the EarthCube.
Distributed Database The University of California Berkeley Extension Copyright © 2011 Patrick McDermott.
ABSTRACT Real-time systems applied to seismic data acquisition, asynchronous processing, and data archiving tasks have clearly demonstrated their utility.
Distributed Real-Time Systems for the Intelligent Power Grid Prof. Vincenzo Liberatore.
Domestic Nuclear Detection Office (DNDO) NITRD Workshop What are the Biggest Opportunities in Networking Problem? Sept. 20, 2012 Timothy Ashenfelter, PhD.
Internet GIS (and its applications to transportation) Keivan Khoshons GEOG 516 March 9, 2004.
WPS Application Patterns at the Workshop “Models For Scientific Exploitation Of EO Data” ESRIN, October 2012 Albert Remke & Daniel Nüst 52°North Initiative.
NORDUnet NORDUnet The Fibre Generation Lars Fischer CTO NORDUnet.
DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S
San Diego Supercomputer CenterUniversity of California, San Diego Preservation Research Roadmap Reagan W. Moore San Diego Supercomputer Center
Information-Based Building Energy Management SEEDM Breakout Session #4.
 Applied Architectures and Styles Chapter 11, Part 2 Service-Oriented Architectures and Web Services Architectures from Specific Domains Robotics Wireless.
NEPTUNE Canada Workshop Oceans 2.0 Project Environment NEPTUNE Canada DMAS Team Victoria, BC February 16, 2009.
Introduction to Apache OODT Yang Li Mar 9, What is OODT Object Oriented Data Technology Science data management Archiving Systems that span scientific.
Wireless Networks of Devices (WIND) Hari Balakrishnan and John Guttag MIT Lab for Computer Science NTT-MIT Meeting, January 2000.
Project IDA (International Deployment of Accelerometers) Project IDA Project IDA: Managing Seismic Data on a Global Scale GEOSS Seismic Workshop August.
MOME MOME: An advanced measurement meta-repository IPS-MoMe Workshop, Warsaw, Poland March 14, 2005 Felix Strohmeier Authors:
A Wide Range of Scientific Disciplines Will Require a Common Infrastructure Example--Two e-Science Grand Challenges –NSF’s EarthScope—US Array –NIH’s Biomedical.
Rule-Based Programming for VORBs Bertram Ludaescher Arcot Rajasekar Data and Knowledge Systems San Diego Supercomputer Center U.C. San Diego.
October 7, 1999Reactive Sensor Network1 Workshop - RSN Update Richard R. Brooks Head Distributed Intelligent Systems Dept. Applied Research Laboratory.
Oct-24-07US France Workshop On Environment and and Sensor Nets Environment and Sensor Networks Workshop US France Young Engineering Scientists Symposium.
Grid Computing & Semantic Web. Grid Computing Proposed with the idea of electric power grid; Aims at integrating large-scale (global scale) computing.
1 Distributed Databases BUAD/American University Distributed Databases.
Information Technology Needs and Trends in the Electric Power Business Mladen Kezunovic Texas A&M University PS ERC Industrial Advisory Board Meeting December.
Microsoft Research Faculty Summit Liqian Luo Networked Embedded Computing Microsoft Research.
Distributed database system
GRID Overview Internet2 Member Meeting Spring 2003 Sandra Redman Information Technology and Systems Center and Information Technology Research Center National.
Non-Traditional Databases. Reading 1. Scientific data management at the Johns Hopkins institute for data intensive engineering and science Yanif Ahmad,
Enabling the Future Service-Oriented Internet (EFSOI 2008) Supporting end-to-end resource virtualization for Web 2.0 applications using Service Oriented.
Abstract A Structured Approach for Modular Design: A Plug and Play Middleware for Sensory Modules, Actuation Platforms, Task Descriptions and Implementations.
Digital Library The networked collections of digital text, documents, images, sounds, scientific data, and software that are the core of today’s Internet.
Distributed Data Analysis & Dissemination System (D-DADS ) Special Interest Group on Data Integration June 2000.
August 2003 At A Glance The IRC is a platform independent, extensible, and adaptive framework that provides robust, interactive, and distributed control.
1 HPEC'02 Distributed Data Management Architecture for Embedded Computing The Problem: –Integrated real-time management of large, distributed, heterogeneous.
CUAHSI HIS: Science Challenges Linking small integrated research sites (
Scientific and Technical Issues on Environmental Data Access Gilberto Câmara Director for Earth Observation National Institute for Space Research.
National Archives and Records Administration1 Integrated Rules Ordered Data System (“IRODS”) Technology Research: Digital Preservation Technology in a.
Michael Hamilton, Vanessa Rivera del Rio and Sean Askay University of California James San Jacinto Mountains Reserve.
Distributed Data Servers and Web Interface in the Climate Data Portal Willa H. Zhu Joint Institute for the Study of Ocean and Atmosphere University of.
CIMA and Semantic Interoperability for Networked Instruments and Sensors Donald F. (Rick) McMullen Pervasive Technology Labs at Indiana University
Cyberinfrastructure Overview of Demos Townsville, AU 28 – 31 March 2006 CREON/GLEON.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
Panel: "QoS Provisioning at the Network Edge" John Vicente Intel Corporation / Columbia University USENIX Special Workshop on Intelligence at the Network.
Grid Services for Digital Archive Tao-Sheng Chen Academia Sinica Computing Centre
DMQ4:Instruments & Sensors for online remote access
The Globus Toolkit™: Information Services
Distributed Data Management Architecture for Embedded Computing
VORB Virtual Object Ring Buffers
Distributed Systems Bina Ramamurthy 4/22/2019 B.Ramamurthy.
Presentation transcript:

Sensor Networks: Next Generation Problems Frank Vernon Scripps Institution of Oceanography University of California at San Diego SAMSI Sensor Network Workshop October 2003

Open problems How can I acquire desired RT data? How can I discover/access desired RT data? How can I share/integrate the data? Can I integrate dynamically? Can I share with other disciplines? Can I integrate seamlessly with data from other disciplines Can I integrate with archived data?

Sensor Networks Desires Timing –Critical issue for any modal analysis or array processing analysis –Need to synchronize across all sensors Communications systems –Power < 1W for remote sites –IP –Aggregate data rate ≥ 1 Mbit/sec –Scalable for array apertures from 100s meters => megameters

What is needed for a real-time data exchange systems: System should be “data neutral” –Variable packet size –All formatting at application level System should allow data query functions System should allow dynamic updates of instrument metadata –metadata not embedded in every data packet Packet descriptions should be available in real-time –Self-describing

What is needed for a real-time data exchange systems: System should be network transparent with respect to read/write/local/remote access System should be error-free and robust –Impervious to communications failures –Impervious to computer shutdown-startup –Generally means non-volatile buffers, auto- reconnects, auto-restarts, etc. Interoperable with other real-time data exchange systems and new real-time data sources

Design Goals for Future Real-Time Sensor Networks capture, process, control for quality, and integrate real-time data streaming from different sources-- collected for different purposes, on different time and spatial scales, and measured by different methods; make heterogeneities in platforms, physical location and naming of resources, data formats and data models, supported programming interfaces, and query languages transparent to the user; adapt to new and changing user requirements for data and data products;

Design Goals for Future Real-Time Sensor Networks dynamically reconfigure with the addition or removal of observational equipment and/or scientific instrumentation –self-healing topology –decentralized resource registration provide Internet access to integrated data collections along with visualization, data mining, analysis, and modeling capabilities