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  Detailed progress since last meeting  Short term issues encountered (if any)  New directions, emphases

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

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)

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

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

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

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

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

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

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

Supplementary: Development Platform ucLinux 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 "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: 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 "Still in pre-mature stage "Limited Extensibility " limited # of I/O pins " No Standard AddrBus or DataBus

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