Download - FARM: A Feedback based Adaptive Resource Management for Autonomous Hot-Spot Convergence System
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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
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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
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Today
Today:Today:
Large space-based Observatories
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Tomorrow
Sensor WebSensor Web
- Web of satellites with on-board computing power
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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
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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
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Sensor Web - Schematic
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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
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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
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System Model
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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
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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
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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.
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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
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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.
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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
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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
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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!!
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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
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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
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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
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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
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Path-level Diagram
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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
-
-
-
-
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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
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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.
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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
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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).
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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).
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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
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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
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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
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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
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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
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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