FARM: A Feedback based Adaptive Resource

Managementfor Autonomous Hot-Spot

Convergence System

S. Swaminathan & G. ManimaranDept. of Electrical & Computer

EngineeringIowa State University

{swamis,gmani}@iastate.edu{swamis,gmani}@iastate.edu

Problem Overview NASA – Earth Science Enterprise

To understand Earth system Employs Earth Observing Satellites to collect data

about atmosphere, oceans, continents Information used to solve scientific mysteries,

society problems One such problem: Hotspot

What? – Any abnormal natural/man made event E.g., Volcano, Tornado or Nuclear explosion

Problem: Hot-spot detection and location Solutions called for Collaborative Problem Collaborative Problem

SolvingSolving

Today

Today:Today:

Large space-based Observatories

Tomorrow

Sensor WebSensor Web

- Web of satellites with on-board computing power

Today and Tomorrow NASA - transition from large

observatories to light space-based instruments

Instruments with on-board computing and communication power On-board computing - must enable hot spot

detection, location, and monitoring Enable autonomous problem solving

Instruments placed at different orbits for different levels of accuracy Work as a web of satellites – Sensor WebSensor Web

Sensor Web

Sensor Web Constellation of Earth observing satellites Coordination for distributed monitoring,

processing, and decision making Can be considered as an internet of

satellites End user must be able to interact with

sensor web to get information about hotspots

Easy deployment of technology and scalability

Sensor Web - Schematic

System Components

Satellites: Orbit around the earth at different orbits

low earth orbit (small satellites), geostationary (geostationary satellites), and L1 and L2 orbits (sentinel satellites).

Spot beam (coverage area) Data accuracy – depends on orbit level Smaller the spot beam, higher the accuracy

System Components (contd..)

Satellite - sensors and instruments for measurement

Satellite on-board data processing capabilities on-board communication capabilities

Capable of reacting to changes in the spot beam

Earth Control Center: Controls/monitors the sensor web

End user: Queries the sensor web

System Model

Application Scenario

Scenario - handling of a hot-spot Auto detection or External trigger

On-board processors analyze data communicate directly or through other

satellites different data rates for different information

Autonomous satellites detect hot-spots Establish contact with control center

If external triggered - instruments adjusted

Application Scenario (contd..)

Scientist becomes aware of hotspot knowledge of location - not required

Triggers sensor web (nearby satellite) Perform collaborative problem solving

specific satellite queries relevant satellites detect hotspot and information to control center control center can adjust other satellites (if

reqd.) Control center/end user can query any

satellite about a hotspot

Sensor Web - Challenges

Information Technology Resource management mechanism - handling uncertain

workload Algorithms and techniques - data aggregation, compression

and image processing. Reconfigurable architectures and algorithms for various on-

board data processing. Energy-efficient architectures and algorithms for on-board

computing and communication. Satellite Technology

Dynamic control and reconfiguration of satellite instruments. Satellite computing, communication, and instrumentation

technologies. Global real-time onboard navigation capability for earth science

remote sensing.

Challenges in building a Sensor Web (contd..)

Domain Specific Technology e.g., water-level monitoring algorithm in Polar Ice

caps cloud contamination detection with atmospheric

correction

Issue Addressed - Resource ManagementResource Management Management of computing and communication

resources Reliability, availability, performance and security

requirements Dynamic re-configuration of sensor web

Issues in Autonomous Hot-Spot Convergence Autonomous Hot-Spot Convergence

Hotspot Identification Identification of satellite(s) to cover the hot-

spot for required quality Allocation of resources - computing and

communication Reconfiguration of instrumentation

resources Reliable communication with Earth Control

Center/ End User.

Issues in Autonomous Hot-Spot Convergence (contd..)

Requirements drive the need for Load balancing among the satellites Distributed Coordination Schemes

for minimizing redundancy in the coverage area Quality-aware distributed scheduling, as the quality

of image perceived by one satellite might be higher than another

Further, there is a need for continuous monitoring of topology and resources

Topology Monitoring - knowledge of spot beam Resource Monitoring – for resource allocation

Workload Characteristics

Computational Workload

Static Dynamic

E.g., Default Spot beam coverage

Periodic Aperiodic

Fixed hotspot monitoring e.g, vulcano

dynamic hotspot monitoring e.g., tornado

Periodic computation and communication

Continuous handoffReconfiguration of sensors

Workload Characteristics (contd..)

Communication Workload

Inter-satellite - periodic and aperiodic

satellite -> control center - periodic and aperiodic

satellite -> end-user - aperiodic

Uncertainty - Computational and Uncertainty - Computational and Communication Communication

Workload !!Workload !! Need for Adaptive Resource Management!!Need for Adaptive Resource Management!!

FARM: A New Resource Management Methodology

FARM - Feedback-based Adaptive Resource Management Methodology

Path-based Scheduling coarse level timing requirements easier to model application

Value-based Scheduling Graceful degradation paths offer value/benefit to the system

Feedback scheduling Handles uncertainty in workload Robust and graceful performance

Path-based Scheduling Scheduling based on application semantics

Easiness to provide timing requirements Scheduling a path (group of related tasks)

Paths – Data/Event source, Data Stream, Data/Event Consumer

Transient – initiated by event and ends in an event Continuous

Data source, stream and consumer Cycle deadline – deadline for processing

Quasi-continuous Continuous path activated and deactivated by events Cycle and deactivation deadline

Functional Modules

Adds track

information

Analyzes hotspot

Trigger hotspot

identifier

Reconfigures

instruments

Process user queries

Handles Overload

Interacts with

control center

Communicates with other

satellites

Updates load and topology

Functional Modules (contd..)

Hotspot, Track

Modules Functions Tables

Read Write

SRM

HIM

HSI

HSM

OH

RR

QP

GC-I

GC-II

Sensor Reading and configuration

Enduser/Control Center Interface

Track Track

Track Track

Identification and creation of monitor

Track Hotspot

Analysis of hotspot, Overload Handling and Resource Reconfiguration

Hotspot Hotspot

Overload Handling, Migration Hotspot LTT, MT

Sensor Reconfiguration - -

Query Processing, data compressionCommn. With other satellites

Commn. for load and topology updation

LTT

Hotspot

Track

-

-

-

Hotspot

Track

Path-level Diagram

Paths

Paths Path Type

Track Analysis

Hotspot Identification

Hotspot Monitor

Continuos

Query Processor

Sensor Reconfig.

Load and Topology UpdationOverload Handler

Earth Center Interaction

Quasi-Continuos

Quasi-Continuos

Transient

Transient

Continuos

Transient

Transient

Source Streams Consumer

Sensor Track table HSI

Track table Table entries HSA

Table entries Hotspot table

End User

Query Result

HIS, HIM tasks

Reconfiguration

LTM task

HS-Sel task

LT table

Overload detection Migratio

nCommn. From Control Center

Trigger HSI or RR task

-

-

-

-

Value-based Scheduling Real-Time Systems

Primary Objective: Meet all deadlines Underload situation – can meet deadlines Overloads – schedule critical tasks, degrade

gracefully !! Value-based Scheduling

Scheduling paradigm aims at maximizing the value of system

Allows graceful degradation of system Examples of Value

Criticality based Value Performance Index (Schedulability-Reliability tradeoff

value) function

Closed Loop Scheduling

Controller Actuators

Sensors

Plant

Feedback

Set points System

Controlled variable: the quantity of the output that is measured and controlled.

Set point: represents the correct value of the controlled variable.Manipulated variable: is the quantity that is varied by the Actuators so as to affect the value of the controlled variable.

• The system periodically monitors and compares the controlled variable to the set point to determine the error.

• The controller computes the required control based on the error.

• The actuators change the value of the manipulated variable to control

the system.

FARM: Architecture

Workload arrives at path queue

Admits/rejects paths

Adjusts path qualitySchedules

accepted paths

•Calculates CPU1 and CPU2

•Instructs other controllers

• Observes value, rejection ratio

•Computes Error

FARM: Architecture (contd..) Computation time adjustment

Hotspot monitor path can be adjusted without violating the minimum computational quality.

Query processing and overload handling not amenable for quality adaptation.

The controlled variables are observed and periodically fed back to the PID controller.

No. of hotspots/queries rejected fed-back by the path admission controller

Controller obtains the average hotspot value by periodically reading the hot-spot table (updated by hot-spot analyzer).

Satellite Coordination and Load Balancing Need for coordination

Spot beam overlaps Migration of hot-spots from one sate. to

another Hotspot monitor selection

Quality-based Coordination select based on quality required

Load-based Coordination During overload, select least loaded satellite

No potential satellites Initiate a reconfiguration request to a satellite

(consulting the topology table).

Global Policies for Distributed Real-Time System

Policy Suggested ApproachInformation Periodic policy

Transfer

Selection

Location

Threshold policy

Value-based policy

Sender Initiated

Information Policy – information exchange timings

Transfer Policy – determines need for migration

Selection Policy – determines load to migrate

Location Policy – finds suitable receiver

Survivability

Potential threats Hardware/Software faults Malicious attacks from individual users

(remember throwing a sensor internet is extremely dangerous)

Technology and service like deficiencies Secure, reliable and dependable

architecture amidst threats

Survivability (contd..) Infrastructure protectionInfrastructure protection

Hardware redundancy techniques Firewall technology

Secure and fault-tolerant Secure and fault-tolerant communicationcommunication Encryption of Inter-satellite communication Authentication to protect against malicious

activities Fault-tolerant path executionFault-tolerant path execution

Critical paths need to be identified Scheduled with multiple versions

Survivability (contd..)Fault-Tolerant Policy

Path NamesN-Version Programming

Load and Topology UpdatesRecovery Block

Imprecise Computation

Sensor Reconfiguration, Overload Handler, QP, ECITrack Analysis, Hotspot Identifier, Hotspot Monitor

Fault-tolerant scheduling techniques Tradeoff between schedulability and reliability Use a value-based performability index to capture

this tradeoff Path-based fault-tolerant scheduler

Determines redundancy level for each path to maximize overall performability

Security Security - important as satellites can be

accessed by users over the Internet. Adopted [SWARM] Integrated security

framework Network Intrusion Detection System Network Intrusion Detection System and Resource Resource

ManagerManager Network Intrusion Detection System Network Intrusion Detection System

Intrusion and anomaly detection Resource Manager

Intrusion detected - take resource action Drop suspicious paths

FARM: Summary

Our solution to AHSCS System Modeling and Workload

Characterization FARM

New resource management methodology Graceful Degradation Coarse level timing requirements Robust performance under uncertain workload

Survivability and Security strategies Fault-tolerant techniques Adopted Security Strategy