Catnet “Catallactic Mechanisms for Service Control and Resource Allocation in Large Scale Dynamic Application Networks” EU project: IST-2001-34030 Partners:

Slides:



Advertisements
Similar presentations
Collaborative Commerce. Electronic CommercePrentice Hall © Collaborative Commerce collaborative commerce (c-commerce) The use of digital technologies.
Advertisements

Allocation in Application Layer Networks T. Eymann, M. Reinicke Albert-Ludwigs-University, Freiburg (DE) O. Ardaiz, P. Artigas, L. Díaz de Cerio, F. Freitag,
Decentralized vs. Centralized Economic Coordination of Resource Allocation in Grids T. Eymann, M. Reinicke Albert-Ludwigs-University, Freiburg (DE) O.
SCAN: A Dynamic, Scalable, and Efficient Content Distribution Network Yan Chen, Randy H. Katz, John D. Kubiatowicz {yanchen, randy,
Evaluation of Ad hoc Routing Protocols under a Peer-to-Peer Application Authors: Leonardo Barbosa Isabela Siqueira Antonio A. Loureiro Federal University.
Peer-to-peer Multimedia Streaming and Caching Service Jie WEI, Zhen MA May. 29.
HK-NUCA: Boosting Data Searches in Dynamic NUCA for CMPs Javier Lira ψ Carlos Molina ф Antonio González ψ,λ λ Intel Barcelona Research Center Intel Labs.
Parallel Programming on the SGI Origin2000 With thanks to Moshe Goldberg, TCC and Igor Zacharov SGI Taub Computer Center Technion Mar 2005 Anne Weill-Zrahia.
Carnegie Mellon University Complex queries in distributed publish- subscribe systems Ashwin R. Bharambe, Justin Weisz and Srinivasan Seshan.
Rutgers PANIC Laboratory The State University of New Jersey Self-Managing Federated Services Francisco Matias Cuenca-Acuna and Thu D. Nguyen Department.
Decentralized Resource Allocation in Application Layer Networks T. Eymann, M. Reinicke University Freiburg, Germany O. Ardaiz, P. Artigas, F. Freitag,
1 Client-Server versus P2P  Client-server Computing  Purpose, definition, characteristics  Relationship to the GRID  Research issues  P2P Computing.
An Overlay Multicast Infrastructure for Live/Stored Video Streaming Visual Communication Laboratory Department of Computer Science National Tsing Hua University.
A.M. Florea, Cognitive systems, COST Action IC0801 – WG1, 15 December, Ayia Napa, Cyprus.
1 GRID D. Royo, O. Ardaiz, L. Díaz de Cerio, R. Meseguer, A. Gallardo, K. Sanjeevan Computer Architecture Department Universitat Politècnica de Catalunya.
UCB Communication Networks: Big Picture Jean Walrand U.C. Berkeley
Web Caching and CDNs March 3, Content Distribution Motivation –Network path from server to client is slow/congested –Web server is overloaded Web.
Diffusion scheduling in multiagent computing system MotivationArchitectureAlgorithmsExamplesDynamics Robert Schaefer, AGH University of Science and Technology,
Peer-to-peer Multimedia Streaming and Caching Service by Won J. Jeon and Klara Nahrstedt University of Illinois at Urbana-Champaign, Urbana, USA.
“Multi-Agent Systems for Distributed Data Fusion in Peer-to-Peer Environment” Smirnova Vira ”Cheese Factory”/
Focus on Distributed Hash Tables Distributed hash tables (DHT) provide resource locating and routing in peer-to-peer networks –But, more than object locating.
1 Bridging Clouds with CernVM: ATLAS/PanDA example Wenjing Wu
1 Efficient Management of Data Center Resources for Massively Multiplayer Online Games V. Nae, A. Iosup, S. Podlipnig, R. Prodan, D. Epema, T. Fahringer,
Mobility in the Virtual Office: A Document-Centric Workflow Approach Ralf Carbon, Gregor Johann, Thorsten Keuler, Dirk Muthig, Matthias Naab, Stefan Zilch.
Grid Monitoring By Zoran Obradovic CSE-510 October 2007.
Active Network Applications Tom Anderson University of Washington.
LIGHTNESS Introduction 10th Oct, 2012 Low latency and hIGH Throughput dynamic NEtwork infrastructureS for high performance datacentre interconnectS.
OPTIMAL SERVER PROVISIONING AND FREQUENCY ADJUSTMENT IN SERVER CLUSTERS Presented by: Xinying Zheng 09/13/ XINYING ZHENG, YU CAI MICHIGAN TECHNOLOGICAL.
Catnet Project Review Project participants:  T. Eymann, M. Reinicke Albert-Ludwigs-University, Freiburg (D)  O. Ardaiz, P. Artigas, L. Díaz de Cerio,
A Lightweight Platform for Integration of Resource Limited Devices into Pervasive Grids Stavros Isaiadis and Vladimir Getov University of Westminster
Presented by Xiaoyu Qin Virtualized Access Control & Firewall Virtualization.
CSC8320. Outline Content from the book Recent Work Future Work.
SmartGRID Ongoing research work in Univ. Fribourg and Univ. Applied Sciences of Western Switzerland (HES-SO) SwiNG Grid Day, Bern, Nov. 26th, 2009 Ye HUANG.
Peer-to-Peer Distributed Shared Memory? Gabriel Antoniu, Luc Bougé, Mathieu Jan IRISA / INRIA & ENS Cachan/Bretagne France Dagstuhl seminar, October 2003.
The Grid System Design Liu Xiangrui Beijing Institute of Technology.
Running large scale experimentation on Content-Centric Networking via the Grid’5000 platform Massimo GALLO (Bell Labs, Alcatel - Lucent) Joint work with:
Copyright © 2002 Intel Corporation. Intel Labs Towards Balanced Computing Weaving Peer-to-Peer Technologies into the Fabric of Computing over the Net Presented.
Service - Oriented Middleware for Distributed Data Mining on the Grid ,劉妘鑏 Antonio C., Domenico T., and Paolo T. Journal of Parallel and Distributed.
Software Defined Networks for Dynamic Datacenter and Cloud Environments.
Mobile Agent Migration Problem Yingyue Xu. Energy efficiency requirement of sensor networks Mobile agent computing paradigm Data fusion, distributed processing.
Department of Electronic Engineering Challenges & Proposals INFSO Information Day e-Infrastructure Grid Initiatives 26/27 May.
Research of P2P Architecture based on Cloud Computing Speaker : 吳靖緯 MA0G0101.
Windows Azure for scalable compute and storage SQL Azure for relational storage for the cloud AppFabric infrastructure to connect the cloud.
A Grid-enabled Multi-server Network Game Architecture Tianqi Wang, Cho-Li Wang, Francis C.M.Lau Department of Computer Science and Information Systems.
CoreGRID Workpackage 5 Virtual Institute on Grid Information and Monitoring Services Michał Jankowski, Paweł Wolniewicz, Jiří Denemark, Norbert Meyer,
Globus and PlanetLab Resource Management Solutions Compared M. Ripeanu, M. Bowman, J. Chase, I. Foster, M. Milenkovic Presented by Dionysis Logothetis.
Managing Web Server Performance with AutoTune Agents by Y. Diao, J. L. Hellerstein, S. Parekh, J. P. Bigus Presented by Changha Lee.
Data Communications and Networks Chapter 9 – Distributed Systems ICT-BVF8.1- Data Communications and Network Trainer: Dr. Abbes Sebihi.
MiddleMan: A Video Caching Proxy Server NOSSDAV 2000 Brian Smith Department of Computer Science Cornell University Ithaca, NY Soam Acharya Inktomi Corporation.
Overlay Networks : An Akamai Perspective
3/12/2013Computer Engg, IIT(BHU)1 PARALLEL COMPUTERS- 1.
09/13/04 CDA 6506 Network Architecture and Client/Server Computing Peer-to-Peer Computing and Content Distribution Networks by Zornitza Genova Prodanoff.
Mobile Analyzer A Distributed Computing Platform Juho Karppinen Helsinki Institute of Physics Technology Program May 23th, 2002 Mobile.
Our Place in the Cloud DCIA P2P & Cloud Market Conference March 9, 2010.
What is Cloud Computing? Irving Wladawsky-Berger.
The best of WF 4.0 and AppFabric Damir Dobric MVP-Connected System Developer Microsoft Connected System Division Advisor Visual Studio Inner Circle member.
Presenter: Kuei-Yu Hsu Advisor: Dr. Kai-Wei Ke 2013/9/30 Performance analysis of video streaming on different hybrid CDN & P2P infrastructure.
A Practical Performance Analysis of Stream Reuse Techniques in Peer-to-Peer VoD Systems Leonardo B. Pinho and Claudio L. Amorim Parallel Computing Laboratory.
Towards a High Performance Extensible Grid Architecture Klaus Krauter Muthucumaru Maheswaran {krauter,
DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING CLOUD COMPUTING
PEER-TO-PEER NETWORK FAMILIES
Information Collection and Presentation Enriched by Remote Sensor Data
Introduction | Model | Solution | Evaluation
Globus —— Toolkits for Grid Computing
Network Requirements Javier Orellana
Mobile Agents.
Consideration on applying ICN to Edge Computing
Market-based Dynamic Task Allocation in Mobile Surveillance Systems
Deterministic and Semantically Organized Network Topology
Chapter 2: System models
Presentation transcript:

Catnet “Catallactic Mechanisms for Service Control and Resource Allocation in Large Scale Dynamic Application Networks” EU project: IST Partners: Albert-Ludwigs-Universität Freiburg Universitat Politècnica de Catalunya

Partners Albert-Ludwigs-Universität Freiburg, Institut für Informatik und Gesellschaft (IIG), Abteilung Telematik - Background: Economics, multi-agent systems Univ. Politècnica de Catalunya (UPC), Computer Architecture Department: - Background: Distributed Systems, Content Distribution Networks.

Outline Intro: Grid Scenario Problem: Resource Allocation Solution: Catallaxy Workplan

Grid Scenario (I) Today: Computation and Data Grids Future: Service Grids (or Application Networks): –each job requires resources at multiple locations, –several types of resources cpu + bw + storage. F.e. Grid used to deploy ASP services. F.e. Job Specifications: “4 pentium server connected by 4 Mbytes with 1 Mbytes Proxy Caches between servers”

Grid Scenario (II) Large Scale grids: Millions of resource nodes, as Peer-to-peer networks. Dynamic Environment: Mobile resources, with high service allocation switching.

Problem: Resource Allocation Current Grids Resource Allocation: Globus GRAM, etc -> centralized system. Future Grids Resource Allocation: (millions of resources, mobile resources, multiple types of resources) too complex task. Solution: “Catallaxy” [Hayek 1988] “market-based coordination of autonomous agents with constitutional intelligence”

Catallaxy “market-based coordination of autonomous agents with constitutional intelligence” Market based : agents are selfish ->optimize Coordination of autonomous agents: no central allocator -> scales. With constitutional intelligence: operates with incomplete information -> work in dynamic environments.

Service Market Resource-Market Catalactic Resource Allocation ClientServiceResource

Catnet WorkPackages Service Grid Simulator: –Multiple resource: storage, bw, cpu. –Built on top of network simulator Javasim: accurate message delays. Simulations: –Dynamic Workloads: CDN & P2P clients trace. –Metrics: Social Welfare.