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Utility-Function based Resource Allocation for Adaptable Applications in Dynamic, Distributed Real-Time Systems PowerPoint PPT Presentation


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Utility-Function based Resource Allocation for Adaptable Applications in Dynamic, Distributed Real-Time Systems. Presenter: David Fleeman { [email protected] } F. Drews, L. Welch, D. Juedes and D. Fleeman Center for Intelligent, Distributed & Dependable Systems Ohio University Athens, OH

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Utility-Function based Resource Allocation for Adaptable Applications in Dynamic, Distributed Real-Time Systems

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Utility-Function based Resource Allocation for Adaptable Applications in Dynamic, Distributed Real-Time Systems

Presenter: David Fleeman { [email protected] }

F. Drews, L. Welch, D. Juedes and D. Fleeman

Center for Intelligent, Distributed & Dependable Systems

Ohio University

Athens, OH

WPDRTS 2004

April 26, 2004


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Overview

  • Simplistic model for resource (re)-allocation algorithms.

  • Formalization of a multi-criterion optimization problem.

    • Service Attributes

    • Extrinsic Attributes

  • Simple hierarchical architecture that supports the algorithm.

  • How it would fit into the QARMA architecture.

WPDRTS, April 26, 2004


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Common real-time engineering approaches

  • Use “worst-case” execution times to characterize workloads a priori.

  • Allocate computing and network resources to processes at design time.

    Problems:

  • Limits the functionality and flexibility of applications to adapt to new situations.

  • Limits the options to handle overloading of system resources.

  • May lead to poor resource utilization.

  • Inappropriate for applications that must execute in highly dynamic environments.

WPDRTS, April 26, 2004


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How to react in response toenvironmental changes?

1. Reallocation approach

  • Dynamically reconfiguring the way in which computing and network resources are allocated to processes

    2. Service level and utility approach

  • Simple strategy: assigning fewer resources by slowing applications down (first few versions of BBN UAV OEP).

  • More advanced strategy: utility function and service levels

WPDRTS, April 26, 2004


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Service levels and Utility function Approach

Utility function:

  • Defined as the “user perceived benefit by performing a certain action with a particular fidelity within the given time constraints”.

  • Function that describes the quality of the output of an application depending on the service level.

  • Specified by the user.

WPDRTS, April 26, 2004


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Our approach

  • Most existing approaches are based on either reallocation of resources or adaptation of service levels in response to dynamic changes in the environment without a notion of system utility.

  • Our approach combines the dynamic reallocation and the service level with the goal of optimizing system utility.

  • Similar work

    • Q-RAM from CMU

    • Dr. Jensen’s work in TUF and UA

WPDRTS, April 26, 2004


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Definition of the System Model

Hardware components

  • Set of hosts: Each host specified by

    • memory size, SPEC rates, etc.

  • Interconnection Network

WPDRTS, April 26, 2004


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Definition of the System Model

Software components:

Application software system:

  • Logical view that distinguishes several layers of abstraction:

    • Highest level: Total system

    • Next lower level: Collection of subsystems

    • A subsystem is a collection of paths, each with a given period or maximum event-rate

    • Path consists of a set of tasks (or applications) and data-depedencies between tasks

WPDRTS, April 26, 2004


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Definition of the System Model

Software components

Set of tasks:

Each task specified by

  • execution time profiles and memory profiles:

    • depending on the processor is assigned to

    • depending on certain operational conditions set by the environment (“extrinsic attributes”)

    • depending on certain parameters that can be changed at runtime (“ service level attributes”)

  • periodic applications: period

  • event-driven applications: maximum event rate modelled by

WPDRTS, April 26, 2004


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Definition of Extrinsic Attributes

  • Express functional conditions or requirements

    • Determined by environmental conditions

    • Determined by status of system components.

  • Set by external conditions and cannot be changed by the system

  • Examples:

    • event-rate of event-driven tasks

    • workload

WPDRTS, April 26, 2004


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Definition of Service Attributes

  • Can be changed at any time by resource manager

  • If external conditions change, appropriate settings of the service attributes allow adaptation to the new conditions

  • Examples:

    • Compression algorithm or type

    • Pixel processing parameters

WPDRTS, April 26, 2004


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Utility Functions

For local optimization, each subsystem is provided a local utility function that measures the contribution of subsystem to the overall system utility

  • represents the maximum manageable extrinsic attibutes

    The (overall) system utility function can be computed from the subsystem utilities by means of some aggregation function:

    Example:

WPDRTS, April 26, 2004


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Optimization Objective

Find an allocation of applications to hosts

and settings of service attributes and settings of maximum

manageable extrinsic attributes such that

  • The allocation is feasible (i.e., runtime conditions and memory limitations on the hosts are satisfied. That is, all the applications meet their deadlines)

  • The overall system utility is maximum

  • The values of the maximum manageable extrinsic attributes are as high as possible

WPDRTS, April 26, 2004


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Service Table

Ideas:

  • Using a table look-up technique for the resource manager.

  • Restrict the problem to discrete grid points.

  • RM is provided with a table containing “good candidate solutions”,i.e., allocations along with service attribute settings and (maximum) manageable extrinsic attributes that are computed during a pre-runtime analysis.

  • Service table:

WPDRTS, April 26, 2004


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Simple Example

6

5

4

3

2

1

1

2

3

4

5

6

WPDRTS, April 26, 2004


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Hierarchical Architecture of anAdaptive Resource Manager

Main Objectives:

  • Reflect the logical decomposition into subsystems, paths, and applications

  • Scalability: Remove or reduce the bottleneck of a central resource manager

    Main Assumption:

  • Task migration is more expensive than modification of service level parameters

WPDRTS, April 26, 2004


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HierarchicalArchitecture of anAdaptive Resource Manager

Dynamic Reallocation

Chooses allocation from ST

Overall System Utility Optimization

Receive sub-table from AM

Local Utility Optimization by means of Service Level Modification

WPDRTS, April 26, 2004


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Generic Resource Management Architecture

Configuration

Files

Detectors

Decision-Maker

Monitors

Information

Repository

Enactors

Environment

Resource Instrumentation

Software Instrumentation

Resource and Software

Management Commands

Computing Environment &

User Applications

WPDRTS, April 26, 2004


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CORBA Resource Management Architecture

Resource Management Architecture

QARMA Components

Specification

Tool

Configuration

Files

System Repository Service

Resource Management Service

Enactor

Service

Replaceable Components

Host and Network

Monitor / Detector

Software Performance Monitor / Detector

Enactor

(Quality Connector)

Hosts/Networks

Host and Network

Monitor / Detector

Software Performance Monitor / Detector

Enactor

(Quality Connector)

Host and Network

Monitor / Detector

Software Performance Monitor / Detector

Enactor

(Quality Connector)

Resource Management Service Goal

  • Each chain of applications achieves a “benefit” based on it’s service attribute settings (e.g., frame rate) and extrinsic attribute settings (e.g., importance).

  • The Resource Management Service changes service attributes in order to optimize total benefit, subject to the constraint that all tasks meet their real-time requirements.

UAV Video

ATR

Tracking

Application Layer (independent of QoS mechanism)

WPDRTS, April 26, 2004


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Integration of Approach in QARMA

Resource Management Architecture

QARMA Components

Specification

Tool

Configuration

Files

System Repository Service

Allocation

Manager

Enactor

Service

Replaceable Components

Global Service Optimizer

Host and Network

Monitor / Detector

Enactor

(Quality Connector)

Hosts/Networks

Host and Network

Monitor / Detector

Enactor

(Quality Connector)

Host and Network

Monitor / Detector

Enactor

(Quality Connector)

Local Service Optimizer 1

Local Service Optimizer 1

Local Service Optimizer 1

UAV Video

ATR

Tracking

Application Layer (independent of QoS mechanism)

WPDRTS, April 26, 2004


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Contribution of this paper

  • Lays the basis for further work on online and offline resource allocation algorithms.

  • Provides a general optimization model and an architecture for dynamic, distributed real-time systems.

  • Introduces hierarchical decision-making architecture.

  • Shows how it can (will) be implemented in a real resource management system.

WPDRTS, April 26, 2004


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