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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

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

overview
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

common real time engineering approaches
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

how to react in response to environmental changes
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

service levels and utility function approach
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

our approach
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

definition of the system model
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

definition of the system model8
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

definition of the system model9
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

definition of extrinsic attributes
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

definition of service attributes
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

utility functions
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

optimization objective
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

service table
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

simple example
Simple Example

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5

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3

2

1

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2

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4

5

6

WPDRTS, April 26, 2004

hierarchical architecture of an adaptive resource manager
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

hierarchicalarchitecture of an adaptive resource manager
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

generic resource management architecture
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

corba resource management architecture
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

integration of approach in qarma
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

contribution of this paper
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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