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Sensor-Network Schemes

Sensor-Network Schemes. Presented by: Charles ‘Buck’ Krasic Slides adapted from original authors’. Paper List. C. Intanagonwiwa, R. Govindan, D. Estrin, (USC/ISI, UCLA) “Directed Diffusion: A Scalable and Robust Communications Paradigm for Sensor Networks” . MobiCOMM 2000

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Sensor-Network Schemes

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  1. Sensor-Network Schemes Presented by: Charles ‘Buck’ Krasic Slides adapted from original authors’ CSE 581 - Sensor-Network Schemes

  2. Paper List • C. Intanagonwiwa, R. Govindan, D. Estrin, (USC/ISI, UCLA) “Directed Diffusion: A Scalable and Robust Communications Paradigm for Sensor Networks”. MobiCOMM 2000 • J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, D. Ganesan, (USC/ISI,UCLA) “Building Efficient Wireless Sensor Networks with Low-Level Naming”. SOSP 2001 • J. Kulik, W. Heinzelman, H. Balakrishnan, (MIT) “Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks”. MobiCOMM 1999 CSE 581 - Sensor-Network Schemes

  3. Disaster Response Circulatory Net The long term goal Embed numerous distributed devices to monitor and interact with physical world: in work-spaces, hospitals, homes, vehicles, and “the environment” (water, soil, air…) Network these devices so that they can coordinate to perform higher-level tasks. Requires robust distributed systemsof tens of thousands of devices. CSE 581 - Sensor-Network Schemes

  4. Resource-Adaptive Protocols for Networks of Sensors J. Kulik, W. Heinzelman, H. Balakrishnan, (MIT) “Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks”. MobiCOMM 1999 CSE 581 - Sensor-Network Schemes

  5. SPIN – Sensor Protocols fro Information via Negotiation • J. Kulik, W. Heinzelman, H. Balakrishnan, (MIT) “Negotiation-based Protocols for Disseminating Information in Wireless Sensor Networks”. MobiCOMM 1999 CSE 581 - Sensor-Network Schemes

  6. Overview • Motivation and goals • Approach to sensor communication: • Meta-data exchanges • Data aggregation • “Resource-Adaptive” applications • Implementation using ns • Experiments CSE 581 - Sensor-Network Schemes

  7. Sensor Networks • New research area • Advantages: • Improved accuracy • Fault tolerance • Characteristics: • Wireless network • No high-powered central base-station • Distribution network • Energy-limited nodes CSE 581 - Sensor-Network Schemes

  8. Quality Deadline Energy System Parameters • Quality • Accuracy of result • Deadline • Time result required • Energy Goal: Setup framework for analyzing trade-offs CSE 581 - Sensor-Network Schemes

  9. Classic Network Approaches • Flooding • Redundant data transmission • Multi-hop routing • Large routing tables • Frequent updates • Complexity Question: Are there better approaches? CSE 581 - Sensor-Network Schemes

  10. Negotiation Protocol Meta-Data <=> Data Naming • ADV- advertise data • REQ- request specific data • DATA- requested data ADV A B REQ A B DATA A B CSE 581 - Sensor-Network Schemes

  11. Sensor A sends meta-data to neighbor A ADV B CSE 581 - Sensor-Network Schemes

  12. Sensor B requests data from Sensor A A B REQ CSE 581 - Sensor-Network Schemes

  13. Sensor A sends data to Sensor B A DATA B CSE 581 - Sensor-Network Schemes

  14. Sensor B aggregates data and sends meta-data for A and B to neighbors A ADV ADV B ADV ADV ADV ADV CSE 581 - Sensor-Network Schemes

  15. All but 1 neighbor request data A REQ REQ B REQ REQ REQ CSE 581 - Sensor-Network Schemes

  16. Sensor B sends requested data to neighbors A DATA DATA B DATA DATA DATA CSE 581 - Sensor-Network Schemes

  17. ns Software Architecture Resource-Adaptive Node RCApplication Meta-Data Data RCAgent Resource Manager Meta-Data Data Network Neighbor Energy Network Interface Link Link Link CSE 581 - Sensor-Network Schemes

  18. Resource-Adaptive Application • Communication protocol implementation • Internal state • ADV/REQ/DATA algorithm • Resource-adaptive decision-making • Application-specific • Computation • Communication CSE 581 - Sensor-Network Schemes

  19. Other Simulation Tools • Wireless topology generation • Radio energy models • Statistics collection • Data acquired • Energy dissipated • Redundant data received • Meta-data exchanged CSE 581 - Sensor-Network Schemes

  20. Test Algorithms • Flooding -- Each node floods new data to all of its neighbors. • Gossipping -- Each node floods all its data to one, randomly selected neighbor. • Negotiating -- nodes decide what data to send based on meta-data advertisements. • Sleeping -- Same as negotiating, except that nodes stop sending messages when energy is low. Zzz... CSE 581 - Sensor-Network Schemes

  21. 25-Node Wireless Test Network Diameter = 152 meters Node reach = 10 meters 70 meters 70 meters 59 edges Average degree = 4.7 neighbors CSE 581 - Sensor-Network Schemes

  22. Flooding Gossipping Negotiating Sleeping Limited Deadline Energy Dissipated Total Data Acquired 1 40 0.9 35 0.8 30 0.7 25 % Total Data Acquired Total Energy Dissipated (J) 0.6 20 0.5 15 0.4 10 0.3 5 0.2 0.1 0 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Time (ms) Time (ms) CSE 581 - Sensor-Network Schemes

  23. Flooding Gossipping Negotiating Sleeping Limited Energy Energy Dissipated Total Data Acquired 5 0.8 4.5 0.7 4 0.6 3.5 0.5 % Total Data Acquired Total Energy Dissipated (J) 3 2.5 0.4 2 0.3 1.5 0.2 1 0.5 0.1 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 Time (ms) Time (ms) CSE 581 - Sensor-Network Schemes

  24. Data Acquired/Energy Dissipated 0.8 Flooding 0.7 Gossipping Negotiating 0.6 Sleeping 0.5 % Total Data Acquired 0.4 0.3 0.2 0.1 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Total Energy Dissipated (Joules) CSE 581 - Sensor-Network Schemes

  25. SPIN Summary • Contribution • Sensor networks should be more data-centric (meta-data driven) • Simulation results • Advantages: Seems better than flooding • Disadvantages: communication still excessive? • Future Work: lots! CSE 581 - Sensor-Network Schemes

  26. Directed Diffusion • C. Intanagonwiwa, R. Govindan, D. Estrin, (USC/ISI, UCLA) “Directed Diffusion: A Scalable and Robust Communications Paradigm for Sensor Networks”. MobiCOMM 2000 • J. Heidemann, F. Silva, C. Intanagonwiwat, R. Govindan, D. Estrin, D. Ganesan, (USC/ISI,UCLA) “Building Efficient Wireless Sensor Networks with Low-Level Naming”. SOSP 2001 CSE 581 - Sensor-Network Schemes

  27. Directed Diffusion Concepts • Application-aware communication primitives • expressed in terms of named data (not in terms of the nodes generating or requesting data) • Consumer of data initiates interestin data with certain attributes • Nodes diffuse the interest towards producers via a sequence of local interactions CSE 581 - Sensor-Network Schemes

  28. Directed Diffusion Concepts (cont’d) • This process sets up gradients in the network which channel the delivery of data • Reinforcement and negative reinforcement used to converge to efficient distribution • Intermediate nodes opportunistically fuse interests, aggregate, correlate or cache data CSE 581 - Sensor-Network Schemes

  29. Sending data Source Sink Reinforcing stable path Source Source Sink Sink Recovering from node failure Illustrating Directed Diffusion Setting up gradients Source Sink CSE 581 - Sensor-Network Schemes

  30. 1. For propagating interests In our example, flood More sophisticated behaviors possible: e.g. based on cached information, GPS 2. For setting up gradients Highest gradient towards neighbor from whom we first heard interest Others possible: towards neighbor with highest energy 3. For data transmission Different local rules can result in single path delivery, striped multi-path delivery, single source to multiple sinks and so on. 4. For reinforcement reinforce one path, or part thereof, based on observed losses, delay variances etc. other variants: inhibit certain paths because resource levels are low Local Behavior Choices CSE 581 - Sensor-Network Schemes

  31. Compare diffusion to a)flooding, and b)centrally computed tree (“ideal”) Key metrics: total energy consumed per packet delivered (indication of network life time) average pkt delay Initial simulation studies(Intanago, Estrin, Govindan) FLOODING DIFFUSION CENTRALIZED CENTRALIZED DIFFUSION FLOODING CSE 581 - Sensor-Network Schemes

  32. Experiments on PC104 testbed • Initial experimental measurements of diffusion (e.g., for comparison with simulation) • Compare bytes sent by diffusion with and without aggregation (simple in network processing) • Measurement Setup • A 5-hop network of 14 nodes on 2 ISI floors (testbed is actually 30 nodes and growing) • Radio: 13kbps radiometrix • 1 sink and 1-4 sources (each source sends 112 bytes every 6 seconds) CSE 581 - Sensor-Network Schemes

  33. Bytes sent by diffusion per event vs. Number of sources Experimental Results Diffusion without suppression Diffusion with suppression CSE 581 - Sensor-Network Schemes

  34. Comparison to Simulation • Bytes sent by diffusion per event vs. Number of sources Diffusion without suppression Diffusion with suppression CSE 581 - Sensor-Network Schemes

  35. Differences between Simulations and Experiments • MAC differences • Modified 802.11 for simulations to represent hybrid TDMA-Contention • Radiometrix MAC for experiments • Channel differences • No obstacles used in ns-2 simulations • Note: we have added ability to include simple “terrain” but didn’t try to replicate indoor exp terrain in sims • More packet losses and collisions in experiments • Collisions in experiments act as unintentional suppression (make no suppression look better than it will with better mac) CSE 581 - Sensor-Network Schemes

  36. Edge Processing Nested Queries with In-network Processing In network processing: Nested Queries • Edge processing overwhelms power and bandwidth consumption • Nested queries where low-energy sensors trigger high-energy sensors CSE 581 - Sensor-Network Schemes

  37. Nested query 1-level query Experimental Validation: Testbed Measurements • Higher delivery ratio for nested query indicates that localizing data traffic benefits performance. • % Audio Events Successfully Delivered vs. Number of light sensors CSE 581 - Sensor-Network Schemes

  38. TinyDiffusion • Implementation of Diffusion on resource constrained UCB motes • 8bit CPU, 8K program memory, 512 bytes data memory • Subset of full system • retains only gradients, and condenses attributes to a single tag. • Entire System runs for less than 5.5 KB memory • TinyOS adds ~3.5K and 144 bytes of data. (incl. support for Radio and Photo Sensor) • Diffusion adds ~2K code and 110 bytes of data to TinyOS. CSE 581 - Sensor-Network Schemes

  39. TinyDiffusion Functionality • Resource Constraints • Limited cache size: currently 10 entries of 2bytes each • Limited ability to support multiple traffic streams. Currently supports 5 concurrently active gradients. • Tiered Deployment • PC104s running diffusion interface with mote clusters using TinyDiffusion. • Motes enable dense sensor deployment but can support limited in-network processing • Logical Header format of TinyDiffusion is compatible with the Diffusion header. CSE 581 - Sensor-Network Schemes

  40. RFM Acoustic Data Source Query Data Sink Transceiver DIFFUSION Device Driver TINYOS LINUX Photo Data Source Data Sink TinyDiffusion TINYOS Gateway Architecture MOTE ATMEL 8586 4MHz MCU 8K program memory 512 Bytes Data Memory RFM Radio 900 MHz MOTE Mote-NIC PC104 AMD Elan™SC400 66MHz CPU 16MB RAM Form Factor: 3.6"  x  3.8"  x  0.6" Serial CSE 581 - Sensor-Network Schemes

  41. Tiered Testbed • PC-104+(linux) with MoteNIC • Tags, Sensor Card • UCB Motes w/TinyOS • Yet to come: SmartDust (highly specialized nodes) PC/104 Tag UCB Mote CSE 581 - Sensor-Network Schemes

  42. “Shoebox Testbed v2” • Featuring: • PC-104+ w/Pentium 266 • Mote-NIC • Ethernet fordebugging andmeasurement • Linux 2.4.2w/glibc 2.1.3 • Plastic • shoeboxes • from local drugstore CSE 581 - Sensor-Network Schemes

  43. Directed Diffusion: Summary • Main contributions • Description of new networking paradigm • Interests, gradients, reinforcement • MobiCOMM: simulation results • SOSP: empirical results • Advantages • Benefits of in-network processing • Aggregation and nested-queries CSE 581 - Sensor-Network Schemes

  44. Directed Diffusion Summary (cont’d) • Disadvantages • Design doesn’t deal with congestion or loss • Future Work • Sensor networks today are analogous to the Internet 3 decades ago CSE 581 - Sensor-Network Schemes

  45. Sensor Card • The sensor card is a small (2”x4”) microcontroller board with several on-board sensors and emitters • Microphone • Light sensor • Accelerometer • Designed to perform simple sensing tasks at low power. • Currently it is connected to the PC-104 platform by serial. • Data is preprocessed on the sensor board and fed back to the PC-104 for analysis and communication. • The next version of the PC-104 platform will have the capability to be awakened by a peripheral such as the sensor card. CSE 581 - Sensor-Network Schemes

  46. Reinforced Aggregation • Promote In-network Data Aggregation near the Sources for Better Energy Savings • Two Approaches for Reinforced Aggregation • Greedy Tree Approach • Incremental approach -- Adds minimum number of links on the existing tree • Iterative Approach • Selects aggregation points such that energy dissipation for delivering aggregated data is approximately minimized CSE 581 - Sensor-Network Schemes

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