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Networking Research Review SENSIT PI Meeting October 7-8, 1999 Marina Del Rey

Networking Research Review SENSIT PI Meeting October 7-8, 1999 Marina Del Rey. SCADDS (ISI/W) -- Estrin GRASP (UCLA/CS) -- Zhang DDNC (MIT-LL) -- Van Hook DSN (UCLA/EE-ISI/E) -- Srivastava WINS (Sensorweb) -- Kaiser. General Organization (15 minutes per project). Brief overview

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Networking Research Review SENSIT PI Meeting October 7-8, 1999 Marina Del Rey

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  1. Networking Research ReviewSENSIT PI MeetingOctober 7-8, 1999Marina Del Rey • SCADDS (ISI/W) -- Estrin • GRASP (UCLA/CS) -- Zhang • DDNC (MIT-LL) -- Van Hook • DSN (UCLA/EE-ISI/E) -- Srivastava • WINS (Sensorweb) -- Kaiser

  2. General Organization(15 minutes per project) • Brief overview • Detailed progress since last meeting • Short term issues encountered (if any) • New directions, emphases

  3. SCADDS Recent Progress(PI’s: Deborah Estrin, Ramesh Govindan, John Heidemann) • Directed diffusion v0 (Intanago) • Initial simulation results • Initial prototype implementation • Experimental platform (Elson, Girod, Kumar, Raghunath, Zhao) • Linux and short-range radios • Simple hardware assembled to support protocol experiments--rf sensors, tags (in progress), using cots radios • Scaffolding for diffusion and application

  4. SCADDS: Ongoing activities • Preparation for use of WINS ng nodes • Detailed discussions of comm API • Investigation of current and planned assembly mechanisms(FH and TDMA) • Plan to interface ucLinux nodes directly to Sensorweb hardware--run diffusion algorithms on SENSIT testbed • Algorithm development and evaluation • Directed diffusion design and evaluation (Chalermak Intanagonnowat) • Adaptive clustering (Satish Kumar) • Timing/Synchronization (Jeremy Elson, Lewis Girod) • Adaptive fidelity (Amit Kumar, Ya Xu)

  5. Directed Diffusion • Version 0.0 of directed diffusion • Multi-path delivery • Distinct information dissemination • Probabilistic forwarding • Normalized gradients • Initial experiments with one source and one sink per data type • Many other “flavors” of diffusion worth exploring

  6. Directed Diffusion Preliminary “Indications” • Overhead • Early indications that average network overhead (data, power, state) grows linearly with network size • Overhead per node is constant • Traffic dependent • Energy Dissipation • Low variance of remaining energy across nodes • Indicator of effective load balancing and long network lifetime

  7. Supplementary: Directed Diffusion Future work • Study parameter tuning of the model • Cleaner model : Generalization of reinforcement and interest • Explore additional flavors of diffusion • Redundant information dissemination • Absolute gradients • Multiple sources and multiple sinks per data type • Port to WINS ng nodes, or interface our sensor-controller platform to theirs

  8. Adaptive Clustering • Original hypothesis: Adaptive clustering allows efficient coordination of local interactions • However cluster creation and maintenance can consume significant energy that has to be amortized over gains in application function • Soft-state techniques may consume too much energy at low query rates • Hard-state techniques perform better but adaptation may be more difficult (work in progress) • Adaptation is too energy inefficient if frequency of adaptation not properly controlled

  9. Supplementary: Adaptive Clustering: TDMA Master Election • Master node assigns TDMA slots to slave nodes • Communication between sensors through master to conserve energy • Master’s radio powered on all the time and hence consumes more energy than slaves • Adapt master selection based on energy to improve network lifetime

  10. Supplementary: Adaptive Clustering: TDMA Master Election • Adaptation also has a cost: • Energy cost of the re-election process • Potential data loss during adaptation • Potential re-organization of neighbor clusters • Change in cluster membership • Re-assignment of TDMA slots

  11. Some Project Issues • Evaluation Platforms • uclinux hardware? which radio? • Better indoor propagation and power models for use in non-experimental evaluations • Interfaces and APIs • Interface to WINS ng nodes (i.e., real sensor data and real low-power radio) • Interface to applications • Interaction of diffusion and radio/mac level behaviors

  12. Features 3.5 in x 1 in x 0.25 in, 30pim SIMM 16Mhz MC68EZ328 DragonBall 8Mb RAM, 4Mb FLASHROM I/O Interfaces 18 General Purpose I/O pins Will directly drive a LCD panel 320x240 10Base-T Ethernet (CS8900A) RS-232 Serial Approx $150 per node Supplementary: Development PlatformucLinux and ucSimm • The Linux Microcontroller project uclinux is a port of the Linux 2.0 to systems without a Memory Management Unit. • Target Systems: • 3Com Palm III+TRG memory board • Other micro-controller such as MC68K series • ucSimm: specially designed simm module

  13. Still in pre-mature stage Limited Extensibility limited # of I/O pins No Standard AddrBus or DataBus Supplementary: Pros and Cons • Open Source: GNU Public Liciense • Good Portability • Potential Applications Available worldwide • Simple but Flexible I/O • Radiometrix Transceiver • A/D, D/A converter • Standard serial or 10Based wired connection • Low Power Consumption • 3.3v low voltage, 63mA - 108mA • Low Price

  14. Summary • Diffusion experiments underway on prototype testbed • Sensors are Librettos or ucSimm running linux with Radiometrics radio as rf-sensor • Tags provide data (using small form-factor, semi-programmable radio beacons) • Can be ported or interfaced to WINS ng nodes for SENSIT demo in 2000 • Other algorithmic work in design and modeling/simulation phase • Diffusion--characterization, comparisons • Neighbor identification/coordination/synchronization • Clustering • Adaptive fidelity

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