A Network Virtual Machine for Real-Time Coordination Services

Slides:



Advertisements
Similar presentations
Information Society Technologies programme 1 IST Programme - 8th Call Area IV.2 : Computing Communications and Networks Area.
Advertisements

DELOS Highlights COSTANTINO THANOS ITALIAN NATIONAL RESEARCH COUNCIL.
Technology from seed Cloud-TM: A distributed transactional memory platform for the Cloud Paolo Romano INESC ID Lisbon, Portugal 1st Plenary EuroTM Meeting,
1 A Real-Time Communication Framework for Wireless Sensor-Actuator Networks Edith C.H. Ngai 1, Michael R. Lyu 1, and Jiangchuan Liu 2 1 Department of Computer.
1 Denial of Service in Sensor Networks Authors: Anthony D. Wood, John A. Stankovic Presented by: Aiyaz Amin Paniwala.
Corso di Sistemi in Tempo Reale Laurea in Ingegneria dell‘Automazione a.a Paolo Pagano
MMT (Multi Meshed Tree) Protocols for Cognitive Airborne Networks Nirmala Shenoy Lab for Wireless Networking and Security Rochester Institute of Technology.
Josh Alcorn Larry Brachfeld An in depth review of ad hoc mobile network & cloud security concerns.
1 Sensor Networks and Networked Societies of Artifacts Jose Rolim University of Geneva.
OCIN Workshop Wrapup Bill Dally. Thanks To Funding –NSF - Timothy Pinkston, Federica Darema, Mike Foster –UC Discovery Program Organization –Jane Klickman,
1 Quality Objects: Advanced Middleware for Wide Area Distributed Applications Rick Schantz Quality Objects: Advanced Middleware for Large Scale Wide Area.
Mobile Agent Systems. Mobility Mobile Agents A Mobile Agent is a software agent that exists in a software Environment and can migrate from machine to.
A Network Virtual Machine for Real-Time Coordination Services Professor Jack Stankovic, PI Department of Computer Science University of Virginia June 2001.
26th May, Middleware or Simulator for Autonomic Communications Yang Qiu Networking Laboratory Helsinki University of Technology
Community Manager A Dynamic Collaboration Solution on Heterogeneous Environment Hyeonsook Kim  2006 CUS. All rights reserved.
1 Energy Efficient Communication in Wireless Sensor Networks Yingyue Xu 8/14/2015.
Anthony D. Wood, John A. Stankovic, Gilles Virone, Leo Selavo, Zhimin He, Qiuhua Cao, Thao Doan, Yafeng Wu, Lei Fang, and Radu Stoleru University of Virginia.
Computer Science Perspective Ludek Matyska Faculty of Informatics, Masaryk University, Brno and also CESNET, Prague.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED.
Some Thoughts on Sensor Network Research Krishna Kant Program Director National Science Foundation CNS/CSR Program.
COLLABORATIVE SPECTRUM MANAGEMENT FOR RELIABILITY AND SCALABILITY Heather Zheng Dept. of Computer Science University of California, Santa Barbara.
Distributed Systems Principles and Paradigms
NEST 1 NEST System Working Group Meeting #1 Jack Stankovic University of Virginia September 2001 Boeing Huntington Beach, CA.
Wireless Networks of Devices (WIND) Hari Balakrishnan and John Guttag MIT Lab for Computer Science NTT-MIT Meeting, January 2000.
1. Process Gather Input – Today Form Coherent Consensus – Next two months.
Large Scale Deeply Embedded Networks Jack Stankovic, Tarek Abdelzaher, Sang Son, Chenyang Lu Department of Computer Science University of Virginia Fall.
Deeply Embedded Large Scale Networks Specify and Control Emerging Behavior.
Thinking Architecturally An information theory and complex system viewpoint.
Challenges Towards Elastic Power Management in Internet Data Centers Present by Sheng Cai.
Bio-Networking: Biology Inspired Approach for Development of Adaptive Network Applications 21 May 2005Ognen Paunovski Bio-Networking: Biology Inspired.
Internet of Things. IoT Novel paradigm – Rapidly gaining ground in the wireless scenario Basic idea – Pervasive presence around us a variety of things.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
PnP Networks Self-Aware Networks Self-Aware Networks Self-Healing and Self-Defense via Aware and Vigilant Networks PnP Networks, Inc. August, 2002.
SensorWare: Distributed Services for Sensor Networks Rockwell Science Center and UCLA.
Asynchronous Control for Coupled Markov Decision Systems Michael J. Neely University of Southern California Information Theory Workshop (ITW) Lausanne,
Adaptable and Reactive Security for Wireless Sensor Networks John A. Stankovic Department of Computer Science University of Virginia.
INTRODUCTION TO GRID & CLOUD COMPUTING U. Jhashuva 1 Asst. Professor Dept. of CSE.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
Towards a High Performance Extensible Grid Architecture Klaus Krauter Muthucumaru Maheswaran {krauter,
SENSOR FUSION LAB RESEARCH ACTIVITIES PART I : DATA FUSION AND DISTRIBUTED SIGNAL PROCESSING IN SENSOR NETWORKS Sensor Fusion Lab, Department of Electrical.
Cognitive Networking ECLT 5820 Presentation &
David P. Reed MIT CFP Draft May 2007
The Bay Area Research Wireless Access Network (BARWAN)
Wireless Networks of Devices
Introduction to Wireless Sensor Networks
Lei Chen and Wendi B. Heinzelman , University of Rochester
Failures of Technological Systems
Dynamics of Learning & Distributed Adaptation James P
NSF CSR PI Meeting Breakout Session: Integrated Networked Systems and Internet of Things Saurabh Bagchi Purdue University.
Wireless Ad-Hoc Networking
Data/Analysis Challenges in the Electronic Business Environment
DrillSim July 2005.
Towards Next Generation Panel at SAINT 2002
Data/Analysis Challenges in the Electronic Business Environment
The Globus Toolkit™: Information Services
1st International Conference on Semantics, Knowledge and Grid
CLUSTER COMPUTING.
Collaborative Open Market to Place Objects at your Service
Distributed systems: How did we get here?
Pervasive Computing Happening?
Wireless Networks of Devices (WIND)
Architectural Requirements for the Effective Support of Adaptive Mobile Applications Lawrence Li ICS 243F.
Architectural Requirements for the Effective Support of Adaptive Mobile Applications Lawrence Li ICS 243F.
Middleware for Internet of Things: A Survey
Develop distributed algorithms for sensor networks which provide:
Collaborative Smart House Environment Computer Science Department University of Cyprus Contact: Christodoulou Eleni.
Next-generation Internet architecture
Speaker: Ao Weng Chon Advisor: Kwang-Cheng Chen
A Distributed Clustering Scheme For Underwater Sensor Networks
Substation Automation IT Needs
Presentation transcript:

A Network Virtual Machine for Real-Time Coordination Services Network Virtual Machine (hides complexity of physical environment - battlefield awareness) New Ideas Integration of real-time computing theory, multi-mode MDP, and feedback control theory Composable and scalable micro-protocols that can self-organize distributed devices into collaborative teams to achieve aggregate goals New wireless communication protocol to support end-to-end delay Protocols for dynamic environmental data discovery Resource management, team formation, real-time, mobility, power Heterogeneous Sensors/Actuators/CPUs Impact Guaranteed aggregate behavior of NEST systems Control of mobile sensor/actuator/computer networks Large scale distributed team coordination Theory and practice for performance control Survival of essential services Schedule behavior spec. language wireless protocols demo Year 1 protocols for self-organizing nodes robust an adaptive controllers demo Year 2 Year 3 integrated theory NEST middleware demo John A. Stankovic (stankovic@cs.virginia.edu), University of Virginia University of Illinois, CMU, Lockheed Martin

A Network Virtual Machine for Real-Time Coordination Services Integrated Theory Middleware Architecture Multi-Mode Markov Decision Processes (chooses modes) Set of Adaptive Controllers 1 with Elastic RT Scheduling Set of Adaptive Controllers N with Elastic RT Scheduling Robust Feedback Control and Real-Time Scheduling Theory Combined to design each set of controllers