Adaptive Resource Management Architecture for DRE Systems

Nishanth ShankaranNishanth Shankarannshankar@dre.vanderbilt.edunshankar@dre.vanderbilt.edu

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Motivation: Distributed Real-time & Embedded Systems

ProblemProblem• Need to operate in open & unpredictable

environments• No accurate apriori knowledge of operating

conditions, resource availability, and input workload• Effective utilization of multiple resources –

computational power and network bandwidthSolutionSolution Adaptive Resource Management

Architecture – Resource Allocation and Control Engine (RACE)

System CharacteristicsSystem Characteristics

• Operate under limited resources

• Tight real-time performance QoS constraints

• Dynamic & uncertain environments

• Loss or degradation of hardware with time

• Distribution of computation

• Multiple nodes & data centers

• Task distribution among hosts/data centers

• Integration of information

• Data collection – Radar

• Compute counter measure(s)

• Execute counter measure(s)

• Coordinated operation• E.g., NASA Earth Science Mission &

Total Ship Computing Environment

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Resource Allocation and Control Engine

• Dynamic resource management framework atop CORBA Component Model (CCM) middleware (CIAO/DAnCE)

• Allocates components to available resources

• Configure components to satisfy QoS requirements based on dynamic mission goals

• Perform run-time adaptation

• Coarse-grained mechanisms

• React to new missions, drastic changes in mission goals, or unexpected circumstances such as loss of resources

• e.g., component re-allocation or migration

• Fine-grained mechanisms

System Designer/Mission Planner

Target Platform with Varying Resource Availabilities and Capabilities

Resource Allocation & Control Engine (RACE)

Allocation Algorithms

Control Algorithms

Operational Strings with Varying Resource & QoS Requirements

Uniform Interface to Deploy and Manager

Components

CIAO/DAnCE Middleware

Deploy on Target Domain

Monitor and Adapt Resource Allocation

to Application Components

• Compensate for drift & smaller variations in resource usage

• e.g., adjustment of application parameters, such as QoS settings

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DRE System Model

Client QoS Settings

Server QoS Settings

QoS Enabled Network

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Realtime Distribution Middleware

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Client Proxy

Server Proxy

Client Server Application Parameters

Middleware QoS

Parameters

OS Priorities, Processor

Reservation Quota

Bandwidth Reservation Mechanism /

Diffserv Codepoints

Qu

alit

y o

f S

ervi

ce S

etti

ng

s

QoS Setting at the Application

Layer

QoS Setting at the Middleware

Layer

QoS Setting at the OS Layer

QoS Setting at the N/W Layer

QoS parameters are all layers need to be configured/managed to met end-to-end QoS requirements

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System Model of a CCM Based DRE System

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

RT QoS Enabled CCM Middleware (CIAO/DAnCE)

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Stub SkeletonRT CCM

Parameters

Linux RT Kernel /

Resource Kernel

Bandwidth Broker

Container

Executor

Container

Executor

RT CCM Policy

Application Parameters

Maps To

RACE

QoS Enabled Network

Qu

ali

ty

of

Se

rvic

e S

ett

ing

s

Container provides an

encapsulation for the application

QoS settings are specified at the container level

These settings are then used to

configure the middleware

RACE currently manages OS QoS parameters/knobs

to meet e-2-e QoS requirements

Bandwidth Broker determines Network

QoS settings

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System Model of a DDS Based DRE System

DDS QoS Parameters

Linux RT Kernel /

Resource Kernel

Bandwidth Broker

Application Parameters

RACE

Qu

ali

ty

of

Se

rvic

e S

ett

ing

s

Publisher QoS

Settings

Consumer QoS

Settings

QoS Enabled Network

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Data Distribution Service

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Publisher Proxy

Consumer Proxy

Publisher Consumer

RACE can manage OS & N/W QoS settings even for DDS based systems

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Concluding Remarks and Future Work

• Architecturally, both distribution middleware are similar

• Resource/QoS management architecture developed for one can be applied for the other with minor modifications

• Currently, we have applied RACE for CCM based DRE systems

• In the future, we plan to apply RACE for DDS bases DRE systems

Publisher QoS

Settings

Consumer QoS

Settings

QoS Enabled Network

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Data Distribution Service

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Publisher Proxy

Consumer Proxy

Publisher Consumer

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

RT QoS Enabled CCM Middleware (CIAO/DAnCE)

OS Kernel

RT SchedulerRT CPU Reservation

Mechanism

RT Network Subsystem

Stub Skeleton

Container

Executor

Container

Executor

QoS Enabled Network