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Container Shipping Breakout Group

Container Shipping Breakout Group Participants: Cory Sharp [scribe] – UC Berkeley Thomas Sereno – SAIC Ken Traub – Connecterra Ron Kyker – Sandia National Labs Malena Mesarina – Hewlett Packard Labs Robert Szewczyk – UC Berkeley Phil Buonadonna – Intel Mike Manzo – UC Berkeley

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Container Shipping Breakout Group

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  1. Container ShippingBreakout Group Participants: Cory Sharp [scribe] – UC Berkeley Thomas Sereno – SAIC Ken Traub – Connecterra Ron Kyker – Sandia National Labs Malena Mesarina – Hewlett Packard Labs Robert Szewczyk – UC Berkeley Phil Buonadonna – Intel Mike Manzo – UC Berkeley Jae-Hyuk Oh – United Technologies NEST Retreat, June 2004, Santa Cruz, CA

  2. Deployments • Shipping container security • Intrusion detection • Adversarial, networking • Container monitoring • Report if environment out of tolerance • Take immediate action • Non-adversarial, networking • Radioactive detection • Adversarial monitoring • Pedigree • Log environment data • Report once at end, or at least infrequently • Non-adversarial, networking

  3. Value AddOver a Simple, Cheap, One-shot Sensor • Data processing • Simple, cheap sensors can only detect exceeded tolerances • Data collection • More data available • Manual collection consumes resources • Latency • Human-inspected detectors significantly increase latency

  4. Sensing Modes • Monitoring • Adversarial (security) vs. non-adverserial (environmental) • Mesh networking, low latency reports • Pedigree • Less significant networking • What kinds of sensing?

  5. Installation Options • Permanent fixture of container • Vendor product • Consumer devices

  6. Core Issues • Lifetime • 5 years is the far upper bound (upgrades) • Cost • $50/container/port total cost • Localization • Where is container 1172? (global vs. local) • Audience Note: Shipping companies know precisely what and where about every container, needed for balancing • RF Connectivity • RF leaks through non-water-tight containers • Data Logging • Interoperability between multiple vendors

  7. Core Issues 2 • Security • Compromised network (authentication, encryption, …) • Denial of service, network – spamming packets toward energy exhaustion • Denial of service, sensing – bananas and kitty litter excite radioactive detectors • Detecting events in variable environments • On a ship, temperature, pressure, and vibration changes • How do you detect normal variance versus exceptional variance? • Calibration • Logged/reported data must be meaningful

  8. Problems • Validation – how do you know you get data from all the containers? • Robustness, Reliability • What happens if you lose 10% of the nodes? • Do losses generate false positives? • Add redundancy? Cost? • Latency of data • Certain modes may want to spend a lot of energy to guarantee reports (“fire alarm”) • Data glut/trunk, energy exhaustion • 10,000 nodes reporting • Address with multiple gateways / base-stations

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