Agilla/ Agim one: Middleware Existing sensor network software lacks - - PDF document

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Agilla/ Agim one: Middleware Existing sensor network software lacks - - PDF document

Nov 13, 2023 285 likes •374 views

Motivation Agilla/ Agim one: Middleware Existing sensor network software lacks flexibility Entire network runs just one application for Sensor Networks Cannot adapt to changes in the environment the network user requirements

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1 Agilla/ Agim one: Middleware for Sensor Networks

Chenyang Lu

Department of Computer Science and Engineering

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Motivation

Existing sensor network software lacks flexibility Entire network runs just one application Cannot adapt to changes in

the environment the network user requirements

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Example: Forrest

Three applications: 1) Environmental Monitoring, 2) Fire Detection, 3) Fire Tracking

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Agilla: A Flexible Middleware for Sensor Networks

  • Env. monitoring agent

Fire detection agent Fire tracking agent

Sensor network as a shared computing resource

  • Flexible application deployment

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Example: Cargo Tracking

Thousands of containers leave/join network per day Software need to be changed on the fly due to

  • Departure and arrival of containers
  • Container’s country and company
  • Change in security levels
  • Change in security policies
  • Change in tracking technologies

Agilla: support rapid and flexible deployment of software in wireless sensor networks

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Agilla’s System Architecture

TinyOS

Node @ (1,1)

Tuplespace

Agilla Middleware Agents TinyOS

Node @ (2,1)

Tuplespace

Agilla Middleware Agents

m igrate rem ote access

Neighbor List Neighbor List Middleware Services Middleware Services

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SLIDE 2

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Agilla’s Computational Model

Clone

  • r

Migrate Code Stack Heap Condition Codes PC Two variants of each: 1) Strong (code + state) 2) Weak (code only)

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Tuple Space-Based Coordination

  • Content-addressable shared memory
  • Tuple – A set of data fields
  • Template – A pattern that matches particular tuples
  • Provides spatiotemporal decoupling in unreliable networks

“out” “rout” “in”

Tuplespace Tuplespace

“in”

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Agilla Tuple Space API

Remotely accessible localized tuple spaces Stores context information Facilitates inter-agent communication

  • ut:

insert in: remove rd: read inp: probing remove rdp: probing read regrxn: register reaction deregrxn: deregister reaction rout: insert rinp: probing remove rrdp: probing read rrdpg: probing group read (1-hop) Local Remote

Tuplespace

in

  • ut

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Location-Base Addressing

Nodes are addressed by location

(3,1) (3,2) (3,3) (2,2) (1,1) (1,3)

clone to (3,3) clone to (3,1)

Fire Detection Agent

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Implementation on TinyOS 1.1.13

  • Agilla is available for Mica2 and MicaZ motes
  • 4 agents/node
  • Agent Injector
  • Written in Java
  • Remote Injection via RMI
  • Key Challenges
  • Network bandwidth
  • Compact instructions
  • Memory
  • ROM: 54.7KB of 128KB
  • RAM: 3.5KB of 4KB
  • Message loss
  • Agent-level ARQ

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Our Test Bed

  • 6x9 Mica2 Mote

Test Bed

  • Multi-hop Grid
  • One base station
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SLIDE 3

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Performance Evaluation:

migration vs. remote tuple space access

Migration instructions are more reliable because of hop-by-hop acknowledgements… … but remote tuplespace operations have less overhead

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Agilla Instruction Execution Times

Local Operations Remote Operations

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Initial Experiences

Fire Detection & Tracking

  • Presented at IPSN 2005

Intruder Detection and Tracking

  • Agents guard network perimeter and follow intruders
  • Periodically report intruder location to base station

Autonomous navigation in dynamic environments Cargo & Inventory Management

  • In collaboration with Boeing
  • Mobile agents load manifests from RFID, find items, detect

security breaches, and send alert to Internet gateways.

  • Demo at SenSys 2005

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Fire Tracking Video

Video available at: http:/ / m obilab.w ustl.edu/ projects/ agilla

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Roadmap Query

  • Sensor Net Assisted Navigation in Dynamic Environments

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Related Work

Distributing inanimate code modules

  • XNP [xbow’03], Deluge [sensys’04], MNP [icdcs’05],

SOS [mobisys’05] Contiki [emnets’04]

  • Maté/Bombilla [asplos’02]

Mobile Agent-Like Middleware

  • Sensorware [mobisys’03]
  • Weak migration only
  • Smart Messages [Kang‘04]
  • No remote interactions
  • Single thread per node
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SLIDE 4

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Agilla Summary

Mobile agent middleware simplifies application deployment & increases network flexibility Agilla middleware services

  • Agent mobility
  • Tuple space-based coordination
  • Location-centric addressing
  • Context discovery

Empirical results: deploying sensor network applications on Agilla is reliable and efficient

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Agimone

Integration of Sensor and IP Networks

Current sensor networks are isolated, application- specific, and do not interoperate

  • Future applications will involve multiple sensor networks and

IP networks.

Sensor and IP networks have vastly different characteristics and capabilities Custom application-specific software is written to connect sensor and IP networks

  • Not reusable, error prone, inflexible

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Example Application: Cargo Tracking

Shipping Yard Ship Train Truck Customer, Shipper, DHS, CBP

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Solution: Integrate Two Middlewares

TinyOS Node (1,1)

Tuple Space Neighbors Neighbors

Agilla Middleware MICA2 Mote Agents TinyOS Node (2,1)

Neighbors Neighbors

MICA2 Mote Agents

migrate remote access

Agilla Middleware

Tuple Space AQL AQL AQL AQL AQL AQL AQL AQL

Agilla: Sensor Network Middleware Lim one: I P Network Middleware

  • Mobile Agents
  • Host-level reactive tuple spaces
  • Host-level neighbor list
  • Mobile Agents
  • Agent-level reactive tuple spaces
  • Agent-level neighbor list

Severe resource lim itations Resource Rich ( w ritten in Java)

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Agimone

Network Architecture System Components

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Agimone Services

  • Sensor network discovery
  • Sensor Network

Advertisement scheme

  • Tuple space access
  • AgimoneAgent
  • serves other Limone

agents

  • performs data translation

and compatibility check

  • Agilla agents can access

base station’s tuple space

  • Inter-Network Migration
  • Agilla agent transported

within a Limone tuple

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SLIDE 5

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Cargo Tracking Revisited

Watchdog Agents

  • Monitors sensors
  • Sends alert to base station
  • Port authority’s Limone agent

reacts to it

Intrusion Search Agent

  • Watchdog agent stores alert

tuple locally

  • Intrusion search agent

searches boat before the dock

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Conclusions

Agimone integrates sensor and IP networks Inter-network tuple space accesses take ~10.5ms, and migration takes ~82.5ms

  • Inter-middleware latency negligible

Minimal overhead given increased productivity Cargo tracking application case study demonstrates Agimone’s efficacy

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References

  • C.-L. Fok, G.-C. Roman, and C. Lu, Rapid Development and

Flexible Deployment of Adaptive Wireless Sensor Network Applications, International Conference on Distributed Computing Systems (ICDCS'05), June 2005.

  • G. Hackmann, C.-L. Fok, G.-C. Roman and C. Lu, Agimone:

Middleware Support for Seamless Integration of Sensor and IP Networks, International Conference on Distributed Computing in Sensor Systems (DCOSS'06), June 2006.

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Agilla: http: / / mobilab.wustl.edu/ projects/ agilla

  • Source Code
  • Documentation
  • Tutorials
  • Experience Reports

Thank you!

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More Applications

Habitat monitoring Surveillance Medical care Structural monitoring

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Great Duck Island

Habitat Monitoring

  • Goals
  • Usage patterns of burrows
  • Burrow and environmental changes
  • Differences between nesting areas and others
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SLIDE 6

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Great Duck Island

Tiered Architecture

http://www.greatduckisland.net

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Great Duck Island

Requirem ents

  • Low power (9-month season) Low duty cycle
  • Management from remote health monitoring
  • Handle hash environment verification network
  • Retasking/reconfiguratio mobile code
  • Non-real-time, low data rate
  • 5-10 min: entry/leave
  • 2-4 hr: environmental differential
  • Data streaming, no in-network processing

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Surveillance

Goals

Power efficiency Better sensing coverage Real-time Low cost Reliability

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Wireless Integrated Networked Sensors (WINS)

Tiered Architecture

Continuous vigilance provided by low power, unreliable sensors

  • Seismic, infared, sound

Low-power devices trigger powerful devices only when necessary power efficiency & reliability Internet gateways

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WINS

Phased Execution

1. Lower power sensors 2. Powerful sensors: cameras 3. Stream data to operators Stop propagation as soon as reliability threshold is reached

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WINS

Requirem ents

Remote management health monitoring Handle hash environment verification network Real-time In-network processing Sensing coverage Lower power than traditional surveillance systems

  • Less stringent than habitat
  • Power outlet available for some nodes

More controlled environment

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SLIDE 7

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CodeBlue

Em ergency Medical Care

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CodeBlue

Requirem ents

Security and Privacy Reliability Mobility: doctors, patients, equipments Real-time and prioritization: sudden change in patient status

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Wisden

Structural Monitoring

Data collection for structural analysis Future: autonomous health monitoring, warning, and even actuation

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200 20 35 33 21 41

M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M13 M14 M15 M16 M17 M18 M19 M20 M21 M22 M23 M24 M26 M27 M25

5 Feet

I6A I6B I6F I6E I71 I66 I6D I70 I69 I68 I72 I6C I73 I74 I64 I65 I67

Intel: Condition-Based Maintenance

Intel EF PC Backbone link Sensor net link Gateway Mote

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Structural Health Monitoring

High sampling frequency and data rate

  • A Tri-axial accelerometer: 100 Hz sampling 4.8 Kbps

Reliable data transfer Data synchronization Soft real-time: due to storage limit of sensors Tiered architecture

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Diverse Requirem ents

  • Requirements are highly application-dependent
  • Need to tailor design for specific applications

? High High None Security High High High None Reliability Low Yes Structural Monitoring Low Yes Medical Low Yes Surveillance Very Low None Habitat Monitoring Energy Real-time

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SLIDE 8

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Sum m ary

Engineered, small-scale sensor networks have been deployed successfully. Tiered architecture is prevalent.

  • Sensing, communication, energy

Diverse, application-specific challenges

  • Energy, scale, robustness, real-time, reliability, security,

privacy, time synchronization, localization, retasking…