Resources Management and Component Placement Presenter:Bo Sheng.

Slides:



Advertisements
Similar presentations
Network Resource Broker for IPTV in Cloud Computing Lei Liang, Dan He University of Surrey, UK OGF 27, G2C Workshop 15 Oct 2009 Banff,
Advertisements

All rights reserved © 2006, Alcatel Grid Standardization & ETSI (May 2006) B. Berde, Alcatel R & I.
PlanetLab: An Overlay Testbed for Broad-Coverage Services Bavier, Bowman, Chun, Culler, Peterson, Roscoe, Wawrzoniak Presented by Jason Waddle.
Adaptive QoS Control Based on Benefit Optimization for Video Servers Providing Differential Services Ing-Ray Chen, Sheng-Yun Li, I-Ling Yen Presented by.
Agreement-based Distributed Resource Management Alain Andrieux Karl Czajkowski.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 12 Slide 1 Distributed Systems Design 2.
Effective Coordination of Multiple Intelligent Agents for Command and Control The Robotics Institute Carnegie Mellon University PI: Katia Sycara
CoreGRID Workpackage 5 Virtual Institute on Grid Information and Monitoring Services Authorizing Grid Resource Access and Consumption Erik Elmroth, Michał.
Distributed Systems Architectures
Resource Management – a Solution for Providing QoS over IP Tudor Dumitraş, Frances Jen-Fung Ning and Humayun Latif.
A Grid Resource Broker Supporting Advance Reservations and Benchmark- Based Resource Selection Erik Elmroth and Johan Tordsson Reporter : S.Y.Chen.
Improving Robustness in Distributed Systems Jeremy Russell Software Engineering Honours Project.
A Mobile Agent Infrastructure for QoS Negotiation of Adaptive Distributed Applications Roberto Speicys Cardoso & Fabio Kon University of São Paulo – USP.
1 Introduction to Load Balancing: l Definition of Distributed systems. Collection of independent loosely coupled computing resources. l Load Balancing.
Grids and Grid Technologies for Wide-Area Distributed Computing Mark Baker, Rajkumar Buyya and Domenico Laforenza.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 12 Slide 1 Distributed Systems Architectures.
Bandwidth Allocation in a Self-Managing Multimedia File Server Vijay Sundaram and Prashant Shenoy Department of Computer Science University of Massachusetts.
Improving Data Access in P2P Systems Karl Aberer and Magdalena Punceva Swiss Federal Institute of Technology Manfred Hauswirth and Roman Schmidt Technical.
23 September 2004 Evaluating Adaptive Middleware Load Balancing Strategies for Middleware Systems Department of Electrical Engineering & Computer Science.
Computer System Lifecycle Chapter 1. Introduction Computer System users, administrators, and designers are all interested in performance evaluation. Whether.
Mobile Agents in Wireless Sensor Networks Ivan Vukasinovic Zoran Babovic Goran Rakocevic.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
Self-Organizing Agents for Grid Load Balancing Junwei Cao Fifth IEEE/ACM International Workshop on Grid Computing (GRID'04)
Adaptive Control of Virtualized Resources in Utility Computing Environments HP Labs: Xiaoyun Zhu, Mustafa Uysal, Zhikui Wang, Sharad Singhal University.
Virtual Machine Hosting for Networked Clusters: Building the Foundations for “Autonomic” Orchestration Based on paper by Laura Grit, David Irwin, Aydan.
Copyright © 2006 CyberRAVE LLC. All rights reserved. 1 Virtual Private Network Service Grid A Fixed-to-Mobile Secure Communications Framework Managed Security.
©Ian Sommerville 2006Software Engineering, 8th edition. Chapter 12 Slide 1 Distributed Systems Architectures.
SCAN: a Scalable, Adaptive, Secure and Network-aware Content Distribution Network Yan Chen CS Department Northwestern University.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED.
DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S
Active Monitoring in GRID environments using Mobile Agent technology Orazio Tomarchio Andrea Calvagna Dipartimento di Ingegneria Informatica e delle Telecomunicazioni.
WP9 Resource Management Current status and plans for future Juliusz Pukacki Krzysztof Kurowski Poznan Supercomputing.
Profile Driven Component Placement for Cluster-based Online Services Christopher Stewart (University of Rochester) Kai Shen (University of Rochester) Sandhya.
An Autonomic Framework in Cloud Environment Jiedan Zhu Advisor: Prof. Gagan Agrawal.
Resilient Peer-to-Peer Streaming Presented by: Yun Teng.
Challenges towards Elastic Power Management in Internet Data Center.
The Grid System Design Liu Xiangrui Beijing Institute of Technology.
October 18, 2005 Charm++ Workshop Faucets A Framework for Developing Cluster and Grid Scheduling Solutions Presented by Esteban Pauli Parallel Programming.
Automated Control in Cloud Computing: Challenges and Opportunities Harold C. Lim, Shivnath Babu, Jeffrey S. Chase, and Sujay S. Parekh ACM’s First Workshop.
DISTRIBUTED COMPUTING Introduction Dr. Yingwu Zhu.
Investigating Survivability Strategies for Ultra-Large Scale (ULS) Systems Vanderbilt University Nashville, Tennessee Institute for Software Integrated.
9 Systems Analysis and Design in a Changing World, Fourth Edition.
1 Integrating security in a quality aware multimedia delivery platform Paul Koster 21 november 2001.
VGreen: A System for Energy Efficient Manager in Virtualized Environments G. Dhiman, G Marchetti, T Rosing ISLPED 2009.
A Utility-based Approach to Scheduling Multimedia Streams in P2P Systems Fang Chen Computer Science Dept. University of California, Riverside
PROP: A Scalable and Reliable P2P Assisted Proxy Streaming System Computer Science Department College of William and Mary Lei Guo, Songqing Chen, and Xiaodong.
ICDCS 2014 Madrid, Spain 30 June-3 July 2014
A Grid-enabled Multi-server Network Game Architecture Tianqi Wang, Cho-Li Wang, Francis C.M.Lau Department of Computer Science and Information Systems.
Globus and PlanetLab Resource Management Solutions Compared M. Ripeanu, M. Bowman, J. Chase, I. Foster, M. Milenkovic Presented by Dionysis Logothetis.
Distributed Computing Systems CSCI 4780/6780. Scalability ConceptExample Centralized servicesA single server for all users Centralized dataA single on-line.
Distributed System Architectures Yonsei University 2 nd Semester, 2014 Woo-Cheol Kim.
Computer Science and Engineering 1 Mobile Computing and Security.
GRID ANATOMY Advanced Computing Concepts – Dr. Emmanuel Pilli.
Large-Scale Resource Allocation Amin Vahdat Dec 8, 2002
Content Delivery Networks: Status and Trends Speaker: Shao-Fen Chou Advisor: Dr. Ho-Ting Wu 5/8/
Introduction to: Tycoon A Market Based Resource Allocation System by Alejandro García López.
Architecture for Resource Allocation Services Supporting Interactive Remote Desktop Sessions in Utility Grids Vanish Talwar, HP Labs Bikash Agarwalla,
1 Network related topics Bartosz Belter, Wojbor Bogacki, Marcin Garstka, Maciej Głowiak, Radosław Krzywania, Roman Łapacz FABRIC meeting Poznań, 25 September.
Tanenbaum & Van Steen, Distributed Systems: Principles and Paradigms, 2e, (c) 2007 Prentice-Hall, Inc. All rights reserved DISTRIBUTED SYSTEMS.
Spark on Entropy : A Reliable & Efficient Scheduler for Low-latency Parallel Jobs in Heterogeneous Cloud Huankai Chen PhD Student at University of Kent.
Tunis, Tunisia, 28 April 2014 Requirements of network virtualization for Future Networks Nozomu Nishinaga New Generation Network Laboratory Network Research.
Distributed Systems Architectures Chapter 12. Objectives  To explain the advantages and disadvantages of different distributed systems architectures.
Distributed Systems Architectures. Topics covered l Client-server architectures l Distributed object architectures l Inter-organisational computing.
Architecture and Algorithms for an IEEE 802
Introduction to Load Balancing:
CSC 480 Software Engineering
Providing Secure Storage on the Internet
Basic Grid Projects – Condor (Part I)
DISTRIBUTED SYSTEMS Principles and Paradigms Second Edition ANDREW S
Towards Predictable Datacenter Networks
Presentation transcript:

Resources Management and Component Placement Presenter:Bo Sheng

Outline SHARP: Secure Resources Peering  Motivation  Overview  Key techniques  Evaluation Profile-driven Component Placement

Motivation Research threads: Federated sharing of distributed resources under coordinated control  Internet service utility  Computational network (PlanetLab, Netbed)  P2P and Grid computing  Location independent service naming

Motivation Resource Management

Motivation Flexible Policy-based System  Reserve resources across the system  Admission control  Balance global resources sharing  Robust  Secure

SHARP SHARP (Secure Highly Available Resource Peering)  Soft-state timed claims  Oversubscribe  Accountable delegation

SHARP-Architecture Overview  Site/node  Slice  Service manager  Site authority  Local resource scheduler  Agents

SHARP-Architecture Overview

SHARP-Architecture Resources Claims  Claim record  Signed by the issuer Resources Obtainment  Ticket  Lease Resources Delegation  Self-describing / Self-certifying

SHARP-Architecture Probabilistic Claims  Oversubscribe  Accountable Conflict Rejection  Reputation service  Degree control

SHARP-Architecture SHARP Interface  Request  Claim  Grant  Reject

SHARP-Architecture Agents  Site agents Distribute claims for site resources Peering policy  User agents Gather tickets for global resources  Brokers  Community banking  Adaptive provisioning

SHARP-Architecture Security Architecture  T1:Unauthorized service manager  T2:Replay attack  T3:Unauthorized agent or client  T4:Site contributes faulty resources  T5:Malformed requests or claims  T7:Malicious (A) site authority (B) agent falsely advertises tickets or lease for which resources do not exist.  T8:Malicious site authority falsely rejects tickets.

SHARP-Secure Delegation Resources Sets  Abstract in a ticket  Distribution/redeem  Mapping from abstract to concrete resources Resource Claims  Globally unique claimID   Signature SHA Ki

SHARP-Secure Delegation Secure Delegation and Tickets

SHARP-Secure Delegation Secure Delegation and Tickets

SHARP-Secure Delegation Claim Tree

SHARP-Secure Delegation Tickets Conflicts and Accountability  A set of claims {c0,…,cn} is conflicting at claim p ∑ci.rset.count > p.rset.count  A set of tickets is conflicting iff their final claims are conflicting for some common ancestor p  Accountable claim

SHARP-Secure Delegation Tickets Conflicts and Accountability

SHARP-Secure Delegation Detection Algorithm – linear with chain’s length

SHARP-Secure Delegation Security Analysis and Discussion  Non-repudiation / Sybil attack  Confinement problem  Clock synchronization / monitoring

SHARP-Resources Availability and Efficiency Soft/hard reservation Key techniques  Timed claim  Oversubscribe Degree Aggressive advertisement  Latency/overhead of resource discovery  Coordination

Case Study-PanetLab Resource routing and access via pair-wise relationship

Case Study-PanetLab Evaluation - oversubscribe

Case Study-PanetLab Evaluation - oversubscribe

Case Study-PanetLab Evaluation - oversubscribe

SHARP- Conclusion Resources management Secure delegation Oversubscribe

Component Placement Challenges  Different resource needs / availability  QoS, e.g. response time  Consider runtime factors Bursty demand Failures System upgrades Goal: Efficient dynamic component placement in cluster-based online service

Component Placement Overview  Build per-component resource consumption profiles as a function of input workload characteristics CPU Network bandwidth Memory Average / peak requirements

Component Placement Overview  Placement decision Profiles Available system resources Runtime workload Centralized / distributed / dynamical

Component Placement Overview

Component Placement Building component profiles High throughput component placement Runtime component migration