Transcript The California Institute for Telecommunications and
OptIPuter System Software
Andrew A. Chien SAIC Chair Professor, Computer Science and Engineering, UCSD Director, Center for Networked Systems September 2003 System Software
OptIPuter System Software Team
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Challenge
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~20 Lead Researchers, Many More in Entire Team
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Diverse Researcher Backgrounds and Focus Broad Research Agenda, Abstract Shared Perspective Process
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Innumerable Phone Calls and 1-on-1 Meetings, Fall 2002-Spring 2003 Team Meeting with UCSD and UCI Teams (October 4, 2002) Straw Man OptIPuter System Software Architecture (January 2003)
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Goals, Context, Organization, Relationship of Efforts
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OptIPuter All Hands Meeting, February 6-7, 2003
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First Presentation to Entire Team Feedback, Revision, Improvement, Deeper Understanding, Shared Perspective
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Optical Signalling and Network Management Meeting (May 22, 2003)
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Mambretti Organized
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OptIPuter Software Architecture Version 1.0 (July 2003)
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Structure Stabilized, interfaces Becoming Concrete System Software
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’s Transform Distributed Systems
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Key Technology Changes
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Massive Bandwidth
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100-1000x Increases Wide-Area Systems
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“End To End”
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-Connections
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Private Networks, Guaranteed Bandwidth
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Endpoints are Parallel Clusters
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Large-Scale Network-Attached
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Storage
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Instruments Displays Other Peripherals Challenge is Abstractions, Technologies, and Protocols (SOFTWARE!)
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Grids and Flexible Wide-Area Sharing to Deliver these Opportunities
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Communication Capabilities to Applications
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Tight Wide-area Resource Coupling Simpler Distributed Applications Proactive Computing and Communication System Software
Towards Middleware for
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-Networked Systems
Globus Architecture
Application DUROC, GARA, Replica Catalogs, Metadata Servers, Brokers, Workflow GRAM, GridFTP, GRIS, Co allocation Globus_IO/XIO & GSI Collective Resource Connectivity Resource Access and Control: Computers, Storage, Networks Fabric • •
Leverage Investment and Capabilities (e.g. Globus 2.2 and 3.0)
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Carl Kesselman OptIPuter Participant Ian Foster, OptIPuter Frontier Advisory Board Explore What Must Change
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New Software/Protocols for Managing Lambdas Simplify, Deliver Higher Performance and New Capabilities System Software
OptIPuter Software Architecture for Distributed Virtual Computers v1.1
DVC/ Middleware DVC #1 OptIPuter Applications DVC #2 Visualization DVC #3 Higher Level Grid Services Security Models Data Services: DWTP Real-Time Layer 5: SABUL, RBUDP, Fast, GTP Transport Grid and Web Middleware – (Globus/OGSA/WebServices/J2EE) Optical Node Operating Systems Layer 4: XCP Signaling/Mgmt
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-configuration, Net Management Physical Resources System Software
OptIPuter Links Three Major Sets of Technology Activities
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Distributed Virtual Computers
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Provide a Simple Abstractions
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Aggregate Component Technology Capabilities Surface Novel Capabilities High speed Transport Protocols [Bannister’s Talk]
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Long Thread of High Bandwidth-Delay Product Network Protocols
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Span The Range “Reach” For Dedicated Optical Connections
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Complete Integration with IP Network Management Hybrid – to Local Packet-Switched Networks Separate – End-to-end Optical Network Signaling and Management [Mambretti’s Talk]
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Single Domain and Inter-Domain Hybrid Circuit and Packet-Switched Networks Planning and Execution System Software
Distributed Virtual Computers
System Software
Exploiting
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’s for an Application
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Network View: Ad Hoc connections
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Applications Request
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-Connections
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Network Recognizes High BW flows and Configures
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System View: Enclave of Resources and Connections
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a Distributed Virtual Computer (a SYSTEM)
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How to Specify, Implement, and Exploit?
System Software
SDSC
DVC Examples
UCI or UIC UCSD CSE SIO/NCMIR
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Virtual Cluster (Hide Complexity of Grid; Resource Flexibility)
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Shared Single Domain (Spans Multiple)
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Private Connections; Simple Network Naming Simple Resource Discovery and Access Uniform Performance Characteristics Direct Access to Everything (Storage, Displays, etc.)
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Real-Time Virtual Cluster for Distributed Collaborative Visualization
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Grid Resources + Real-Time (TMO)
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Collaborative Visualization Cluster
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Grid Resources + Photonic Multicast or LambdaRAM (Leigh) System Software
Realizing Distributed Virtual Computers
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Research Challenges
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Application-driven Definition of Abstractions
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Useful Collections which Match Application Paradigms and Needs
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Incorporates New Collective Models
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DVC Description
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Namespaces, Communication, Performance, Real Time, …
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Standard Specifications; Most Applications Parameterize
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Integration Of Component Technologies Executing the DVC on a Grid
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Planner That Identifies Resources
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Selects from Virtual Grid Resources
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Negotiates with Resource Managers and Brokers
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Executor and Monitor for DVC
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Acquires and Configures
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Monitors for Failures and Performance Adapts and Reconfigures System Software
OptIPuter Component Technologies
System Software
Current Storage Views
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Network-attached Storage (NAS)
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Filesystem protocols; Integrated Access-Control and Security
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Low performance; Little Aggregation and Parallelism
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Grid View: High-Level Storage Federation
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GridFTP (Distributed File Sharing) GSI-based Access/Authentication Put/Get, Third-Party Transfers, Whole File and Segments
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Single-System view: Lower-level storage federation
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Secure Single System View SAN – Block Level Disk and Controller Protocols High Performance, Efficient sharing
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Research Areas
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Network-Attached Secure Disk Direct Access File Systems System Software
We Need a Distributed Storage Solution for e-Science Distributed Data Generators
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BIRN: Distributed Data, Intensive Analysis
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100GB Data Elements; Petabyte Data Sets Comparative and Collective Analysis across Data Elements Visualization of Multi-Scale Data Objects System Software
Storage Research Directions
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From Performance to Performability
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Manage and Exploit Multi-Latency Performance Parallel Performance, Stability, and Isolation Integration of Device, Network, Site Reliability Concerns
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OptIPuter Storage Directions
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Application-Driven Design
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Needs, Performance, Device/Site/Network Flexibility, Coding and Selection Integrate Dynamic
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’s and SAN Networks
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Peering, Protocol Interfacing, Performance
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Performance Robust Storage
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Erasure/Other Redundancy; Large-Scale Parallelism; Statistical Approaches to Performance Isolation
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Secure Shared Storage: Threshold Cryptography Approach System Software
OptIPuter Security Considerations
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OptIPuter as a Computing Platform
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Information Assurance and Security Needed for Applications
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Current Plan: use Globus Security Infrastructure
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OptIPuter as a Research Platform
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Current Efforts
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Distributed Security Services (Goodrich & Tamassia) Incremental IP Trace-Back via Packet Marking for DOS Defense (Goodrich)
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Enhanced Forensic Analysis By Design (Karin & Peisert)
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Planned Efforts
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Minimum Round Trip Latency Control (Goodrich) Hardening Against Attacks by Multi-Path Routing (Goodrich, Karin) End-to-End Application and Session Security Through Dedicated Lambdas (Karin) System Software Source: Karin, UCSD and Goodrich, UCI
Multi-Lambda Security Opportunities
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Security Frequently Defined Through Three Measures:
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Integrity, Confidentiality, And Reliability (“Uptime”)
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Can These Measures be Enhanced by Employing Multiple Lambdas?
Can Confidentiality be Improved by Dividing the Transmission Over Multiple Lambdas?
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Fundamentally or Using “Cheap” Encryption?
Can Integrity be Ensured or Reliability Improved by Exploiting Redundancy?
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Source Coding and Performance Adaptive Techniques System Software Source: Goodrich, Karin
Vision – Real-Time Tightly Coupled Wide-Area Distributed Computing
Real Time Object network
Dynamically formed
Distributed Virtual Computer Goals
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High-precision Timings of Critical Actions
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Tight Bounds on Response Times
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Ease of Programming
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High-Level Prog
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Top-Down Design
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Ease of Timing Analysis Source: Kim, UCI System Software
Real-Time: from LAN to WAN
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Time-Triggered Message-Triggered Object ( TMO ) Middleware Subsystem Model that can be Easily Implemented on Both Windows and Linux Platforms
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Developed a Global Time-Based Coordination for use in Fair and
Compo nents of a C++ object
Efficient Distributed On-Line Game Systems and LAN Feasibility Demonstration
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a Step towards Distributed OptIPuter Environment Demonstration
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Paper will be Presented at IDPT 2003 Conference, December 2003
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var AAC AAC
TT Method 1 TT Method 2
Service Method 1 Service Method 2
Deadlines
No thread, No priority High-level Programming Style Source: Kim, UCI System Software
TMO and OptIPuter Software
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TMO will be Integrated into the Overall OptIPuter Software Architecture Begin Design TMO Programming Framework for the OptIPuter Prototype Implementation TMO Support on Linux Platforms, Including OptIPuter Visualization Cluster (UIC – Leigh, UCI -- Jenks)
" Let us start a chorus at 2pm " data " e-Science " data data
Middleware
FT Support TMOSM Kernel
Middleware
FT Support TMOSM Kernel Lambda mux / demux
Source: Kim, UCI
Lambda mux / demux •
An API Wrapping the Services of the RT Middleware Enables High-Level RT Programming Without a new Compiler System Software
Prophesy: Application Performance Modeling
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Performance Modeling of Applications on OptIPuter Cross Platform Comparison (vs. Traditional Grid & Parallel) Yr1: Completed Data Analysis Module Profiling & Instrumentation Yr2: Work with Applications and High Speed Transport Protocols Target applications include:
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SIO Geophysical Data Visualization
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Actual Execution NCMIR/BIRN Neuroscience Applications DATA COLLECTION Web-based GUI Template Database Performance Database Systems Database DATABASES Model Builder Symbolic Predictor DATA ANALYSIS System Software Source: Taylor, TAMU
Summary
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OptIPuter System Software Team Organization
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Development of a Concrete, Shared Perspective
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Organization into Tightly-Coupled Teams OptIPuter Software Architecture 1.0 (July 2003)
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Provides Focus on Key Problems, Clusters Related Activities Framework for Integrating Diverse Capabilities, Identifying Gaps, Integrating and Delivering Solutions Research Activity Clusters
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Distributed Virtual Computers
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Including Real-Time, Security, Storage, Performance Modeling
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High Speed Transport Protocols Optical Signaling and Network Management System Software