Agilla/Agimone: Middleware for Sensor Networks

Transcription

1 Agilla/Agimone: Middleware for Sensor Networks Motivation Existing sensor network software lacks flexibility Entire network runs just one application Cannot adapt to changes in the environment the network user requirements Chenyang Lu Department of Computer Science and Engineering 2 Example: Forrest Three applications: 1) Environmental Monitoring, 2) Fire Detection, 3) Fire Tracking Agilla: A Flexible Middleware for Sensor Networks Sensor network as a shared computing resource Flexible application deployment Env. monitoring agent Fire detection agent Fire tracking agent 3 4 Example: Cargo Tracking Agilla s System Architecture 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 (1,1) Agents migrate Agents (2,1) Change in security levels Change in security policies Change in tracking technologies Neighbor List remote access Neighbor List Agilla: support rapid and flexible deployment of software in wireless sensor networks Middleware Services Agilla Middleware TinyOS Middleware Services Agilla Middleware TinyOS 5 6 1

2 Agilla s Computational Model Tuple Space-Based Coordination PC Stack Condition Codes Heap Code Clone or Migrate Two variants of each: 1) Strong (code + state) 2) Weak (code only) Content-addressable shared memory Tuple A set of data fields Template A pattern that matches particular tuples Provides spatiotemporal decoupling in unreliable networks rout in out in 7 8 Agilla Tuple Space API Remotely accessible localized tuple spaces out Stores context information Facilitates inter-agent communication out: in: rd: inp: rdp: regrxn: deregrxn: Local insert remove read probing remove probing read register reaction deregister reaction Remote in rout: insert rinp: probing remove rrdp: probing read rrdpg: probing group read (1-hop) Location-Base Addressing Nodes are addressed by location (3,1) (3,2) clone to (3,1) (1,1) (2,2) Fire Detection Agent (3,3) clone to (3,3) (1,3) 9 10 Implementation on TinyOS 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 Our Test Bed 6x9 Mica2 Mote Test Bed Multi-hop Grid One base station

3 Performance Evaluation: migration vs. remote tuple space access Agilla Instruction Execution Times Migration instructions are more reliable because of hop-by-hop acknowledgements Local Operations but remote tuplespace operations have less overhead Remote Operations Initial Experiences Fire Tracking Video 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 Video available at: Roadmap Query Sensor Net Assisted Navigation in Dynamic Environments 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

4 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 Agimone Integration of Sensor and IP Networks Current sensor networks are isolated, applicationspecific, 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 Example Application: Cargo Tracking Solution: Integrate Two Middlewares Ship Train Node (1,1) Agents migrate Agents Node (2,1) Neighbors Tuple Space remote access Tuple Space Neighbors Agilla Middleware TinyOS MICA2 Mote Agilla Middleware TinyOS MICA2 Mote Agilla: Sensor Network Middleware Limone: IP Network Middleware Shipping Yard Customer, Shipper, DHS, CBP Truck Mobile Agents Host-level reactive tuple spaces Host-level neighbor list Severe resource limitations Mobile Agents Agent-level reactive tuple spaces Agent-level neighbor list Resource Rich (written in Java) Agimone Network Architecture System Components 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

5 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 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 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 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 Thank you! Agilla: Source Code Documentation Tutorials Experience Reports More Applications Habitat monitoring Surveillance Medical care Structural monitoring Great Duck Island Habitat Monitoring Goals Usage patterns of burrows Burrow and environmental changes Differences between nesting areas and others

6 Great Duck Island Tiered Architecture Great Duck Island Requirements Low power (9-month season) Low duty cycle Management from remote health monitoring Handle hash environment verification network Retasking/reconfiguratio mobile code 31 Non-real-time, low data rate 5-10 min: entry/leave 2-4 hr: environmental differential Data streaming, no in-network processing 32 Surveillance Goals Power efficiency Better sensing coverage Real-time Low cost Reliability 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 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 WINS Requirements 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

7 M22 M19 M20 M21 M23 M18 M24 M25 M6 M4 M5 M17 M26 M2 M3 M16 M27 M7 M8 M1 M9 I6A I6B I6F I6E M13 M10 M11 M14 M12 M15 I71 I66 I6D I72 I6C I70 I73 I74 I69 I68 I64 I65 I67 CodeBlue Emergency Medical Care CodeBlue Requirements Security and Privacy Reliability Mobility: doctors, patients, equipments Real-time and prioritization: sudden change in patient status Wisden Structural Monitoring Intel: Condition-Based Maintenance Data collection for structural analysis Future: autonomous health monitoring, warning, and even actuation Backbone link Sensor net link Gateway Mote Intel EF PC Feet Structural Health Monitoring 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 Diverse Requirements Requirements are highly application-dependent Need to tailor design for specific applications Habitat Monitoring Surveillance Real-time None Yes Security None Reliability None Energy Very Low Low Medical Yes Low Structural Monitoring Yes? Low

8 Summary 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 43 8