The ACE ORB and Distributed Resource Management - PowerPoint PPT Presentation

1 / 22
About This Presentation
Title:

The ACE ORB and Distributed Resource Management

Description:

Optimally use a pool of computing resources ... assure a comprehensive and reliable depiction of the battlespace across echelons. ... – PowerPoint PPT presentation

Number of Views:30
Avg rating:3.0/5.0
Slides: 23
Provided by: csWu4
Category:

less

Transcript and Presenter's Notes

Title: The ACE ORB and Distributed Resource Management


1
The ACE ORB and Distributed Resource Management
  • David Fleeman
  • Dr. Lonnie Welch

2nd Workshop of The ACE ORB (TAO) July 19,
2002 Arlington, VA
2
Overview
  • Introduction
  • Adaptive Resource Management (RM)
  • RM Developer Perspective
  • Advantages of using TAO
  • What is missing?
  • Conclusions
  • References

3
Introduction
  • Traditional scheduling approaches
  • Fixed allocation of software to hardware
  • Unresponsive to changes in the environment
  • Resource management approach
  • Optimally use a pool of computing resources
  • Responsive to dynamic changes in the computing
    environment

4
RM Paradigm
  • Monitor
  • Analyze
  • Control

5
Step 1 Monitor
  • Real-time performance of software systems
  • Resource usage of applications
  • Available resources

6
Step 2 Analyze
  • Will real-time requirements be violated?
  • What will cause the violation?
  • What reallocation actions can be taken to improve
    real-time performance?
  • Move an application
  • Change the QoS level of an application
  • Replicate an application

7
Step 3 Control
  • RM controls which resources (CPU, network
    bandwidth, memory, storage) that each application
    uses.
  • RM controls how much of the resources that each
    application uses.

8
Application Areas of RM
  • Shipboard computing
  • Air Defense
  • Command Control
  • Autonomous satellite constellations

9
Shipboard Computing
  • Dynamic war environment
  • Air defense paths have been modeled and placed
    under RM control

10
Theater Battlespace Command and Control (TBC2)
  • SPAWAR (Office of Naval Research (ONR) funded
    project)
  • The goal of TBC2 is to develop a network centric
    architecture modeled upon FORCEnet that allows
    information and knowledge from multiple
    heterogeneous and distributed systems to be
    assimilated across or within command echelons and
    mission areas. The architecture will enable force
    coordination and its optimization, enable
    subordinates to keep higher command informed, and
    assure a comprehensive and reliable depiction of
    the battlespace across echelons.
  • TBC2 will utilize the DeSiDeRaTa project as
    part of its Quality of Service (QoS) solution to
    interfacing C2 with Combat Systems. The plan is
    to utilize DeSiDeRaTa's Resource Manager (RM) to
    monitor the resources on each host and reallocate
    as necessary, the TBC2 applications that
    interface with the real-time combat systems.

11
Satellite Constellations
12
On-Board System Prototype
13
RM Middleware
14
RM Developer Perspective
  • At first we supported our own communication
    library. We would need to make it support
  • Heterogeneous applications
  • Location transparency
  • Communication across subnets
  • TAO CORBA can do all these things.

15
Advantages of TAO CORBA
  • Removes the need of supporting our own
    communications library
  • Naming service allows location transparency and
    the communication across subnets
  • Differences in hardware platforms solved
  • Communication between Java, C, and C
    applications solved

16
Other Advantages
  • Friendly enough to allow us to define a wrapper
    class to hide the communication details from the
    applications
  • This wrapper allows C and C applications to use
    TAO CORBA to communicate with RM easily.
  • Even though communication with RM requires TAO
    CORBA, applications are still able to use other
    communication mechanisms for their
    inter-application communication needs.

17
What Is Missing?
  • Security and intrusion tolerance
  • Fault tolerance

18
Security and Intrusion Tolerance
  • React autonomously when a network link is
    compromised
  • Removes burden from RM for detecting a subset of
    security violations

19
Fault Tolerance
  • Replica and state management
  • Active-passive model
  • N-version programming (voting)
  • When an active copy fails, then a passive copy
    automatically becomes active and continues where
    the previous active copy failed.

20
Conclusions
  • There is a growing need for adaptive resource
    management of distributed pools of computing
    resources.
  • TAO CORBA is proving to be a powerful
    communication mechanism to help meet this
    challenge.

21
References
  • S. Anwar and L. Welch, Experience With TAO for
    Development of Adaptive Resource Management
    Middleware, 1st Workshop on The ACE ORB (TAO),
    August 2001.
  • Binoy Ravindran, Lonnie R. Welch and Behrooz A.
    Shirazi, "Resource Management Middleware for
    Dynamic, Dependable Real-Time Systems," The
    Journal of Real-Time Systems, 20183-196, Kluwer
    Academic Press, 2000.
  • Toni Marinucci, Anbuselvan Neelamegam, Brett
    Tjaden, Lu Tong, Lonnie Welch, Brian Goldman,
    Greg Greer, Deepak Kaul and Barbara Pfarr,
    Sensor Web Adaptive Resource Manager, NASA
    Earth Science Technology Conference (ESTC-2001),
    August 2001.
  • S. Jain, L. R. Welch, D. M. Chelberg, Z. Tan, D.
    Fleeman, D. Parrott, B. Pfarr, M. C. Liu, C.
    Shuler, A Collaborative Problem Solving Agent
    for On-Board Real-time Systems, The 10th
    Workshop on Parallel and Distributed Real-Time
    Systems, April 2002.

22
More References
  • Lonnie R. Welch, Paul V. Werme , Larry A.
    Fontenot, Michael W. Masters, Behrooz A. Shirazi,
    Binoy Ravindran and D. Wayne Mills, Adaptive
    QoS and Resource Management Using A Posteriori
    Workload Characterizations, The IEEE Real-Time
    Technology and Applications Symposium, 266-275,
    June 1999.
  • Lonnie R. Welch, Binoy Ravindran, Robert D.
    Harrison, Leslie Madden, Michael W. Masters and
    D. Wayne Mills, Challenges in Engineering
    Distributed Shipboard Control Systems,
    Work-in-progress - The IEEE Real-Time Systems
    Symposium, 19-22, December 1996.
  • Lonnie R. Welch, Prashant Shirolkar, Shafqat
    Anwar, Terry Sargeant, Behrooz A. Shirazi and
    Binoy Ravindran, Adaptive Resource Management
    for Scalable, Dependable Real-Time Systems
    Middleware Services and Applications to Shipboard
    Computing Systems, Work-in-Progress The IEEE
    Real-Time Technology and Applications Symposium,
    3-6, June 1998.
Write a Comment
User Comments (0)
About PowerShow.com