ENGINEERING SENSOR NETWORKS FOR LONG- TERM ENVIRONMENTAL MONITORING. Guest lecturer: Doug Carlson

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1 ENGINEERING SENSOR NETWORKS FOR LONG- TERM ENVIRONMENTAL MONITORING Guest lecturer: Doug Carlson

2 2 Hi. Who are you? I m Doug Carlson, one of Dr. Terzis s PhD students. I have been doing research on wireless sensing systems and communication protocols at JHU here since You guys are going to be discussing my paper on Thursday.

3 3 What are you doing here? Dr. Chang is out of town this week.

4 4 What are we doing here? Learning stuff? More specifically, answering the question: How can we build efficient and scalable systems for long-term environmental monitoring (LTEM)?

5 5 The Plan Discuss the LTEM application area and some usage scenarios we have encountered. Talk about the inherent challenges of this application. Discuss potential HW/networking approaches to tackle them. Present the solutions that me and my collaborators have developed in this area.

6 Background 6 BACKGROUND Background. Hardware. Networking.

7 Background 7 What are we working with? Limited hardware budget, favors mote-class devices Battery powered Radio range of 10 s to 100 s of meters Tends to be largest contributor to power budget Local data buffering in flash Some fixed number of ADC inputs

8 Background 8 LTEM Application Requirements Sample periodically (~O(minutes)) Collect data wirelessly Loose latency requirements (hours or days) High yield requirements (>99%) Survive on batteries for months or years (Actually clusters of 4-32 analog sensors)

9 Background 9 What challenges do you foresee? (Actually clusters of 2-8 sensors)

10 Background 10 Hardware Challenges 1. Necessary radio communication ranges vary widely across the network. 2. Some deployments favor uniform sensor coverage, some favor dense clusters. 3. In a large deployment, how do you keep track of what goes where?

11 Background 11 Networking Challenges 1. Coordinating a large, patchy network. 2. Low power disconnected operation. 3. Link state collection and routing.

12 Hardware 12 HARDWARE Background. Hardware. Networking.

13 Hardware 13 HW problem 1: Variable Communication Range Requirements 1. What options do we have? 2. What are the costs/benefits of adding a second communication channel (wifi, cell modem, etc)? 3. How might each of these options impact our energy budget? (Actually clusters of 4-32 analog sensors)

14 Hardware 14 Our Solution: modular RF front-end Leaf configuration +10 dbm output power -90 dbm RX threshold ~3 db gain with PCB antenna Router configuration- PA/LNA, external antenna. +26 dbm output -98 dbm RX threshold Free-space range of 700m 24km

15 Hardware 15 Problem 2: Sensor Allocation MCU has a fixed number of ADC inputs. How can you effectively support both sparse and dense sensor needs? 20 Telos motes, most within ~5 m groups Node Relay Uplink

16 Hardware 16 Our solution: digital, chainable MUX board Connects up to 8 analog sensors to each slave MCU. I2C digital communication Automatic device discovery

17 Hardware 17 HW Problem 3: Sensor metadata and provenance How do you interpret raw voltage measurements? How do you keep track of sensor calibrations? How do you associate data streams with physical locations?

18 Hardware 18 Our Solution: Store types/ids on MCU s Barcode ALL THE THINGS Reflect this information in flash. Send this information back with sensor samples Android app to scan barcodes and record their physical locations

19 Networking 19 NETWORKING Background. Hardware. Networking.

20 Networking 20 Networking Problem 1: Coordinating large, patchy networks. Given the hardware we ve discussed, how might you structure your network? Your collection protocol? How does the addition of a new node affect the duty cycle of the rest of the network?

21 Networking 21 Larger Networks: More Data Forwarding

22 Networking 22 Larger Networks: More Data Forwarding

23 Networking 23 Larger Networks: More Data Forwarding

24 Networking 24 Our solution: separate router tier from leaf tier Leaves buffer data in flash. Leaves push outstanding data to router when woken up. Routers buffer leaf data in flash. Routers push outstanding data to base station when woken up. Separate channel for each patch. Separate channel for routers.

25 Networking 25 Networking Problem 2: Disconnected Operation What should leaf nodes do when their router disappears? What should routers do when the base station disappears? How can you re-associate nodes to the network?

26 Networking 26 Low Power Probing You guys talked about this, right? RX TX 1 TX TX RX RX TX RX TX 2 TX TX RX RX TX 3 TX TX RX Why don t 1 and 2 collide?

27 Networking 27 How can we get the most out of this? What factors dictate the selection of a probe interval? How do probe interval and wakeup frequency affect duty cycle? When should a node send probes? When shouldn t it? How would you adapt LPP to support multiple channels? Baseline Radio Duty Cycle [0, 1.0] Wakeups per day None Weekly Daily 12/day 1/hour Probe Interval (s)

28 Networking 28 Networking Problem 3: Link state collection and routing What information do you need to figure out where to send data? How does the idle radio behavior impact collecting this data? What factors may lead to a mismatch between link quality and route reliability? What impact does bad routing information have on the network?

29 Impact of link quality assessment on the bottom line Cub Hill Duty Cycle and Contacts Batteries Replaced Download Script Replaced Networking 29 Duty Cycle (0 1) Estimated DC: 1.67% 01 May Jun Aug Oct Dec Feb 11 # of Nodes Reached 26 Apr 11 Hard-to-capture effects present Figure 1 Link quality freshness matters

30 Networking 30 Impact of instability on route selection Failed Connections [0 1] Routes using "Healthy" motes Routes using "Rebooting" motes 0 10/28 10/31 11/03 11/06 11/09 11/12 11/15 11/18 11/21 11/24 11/27 11/30 Period of Network : 10/28/2009 to 11/30/2009

31 Networking 31 How can we deal with poor link quality assessment? Plan B is to make Plan A work Moar data? What is the minimum amount of link quality information that we can get by with?

32 Networking 32 Do we even need link quality information? How would you get data from a leaf to a router without knowing local LQ or distances? What are the issues associated with this? Can we do better, perhaps by using some trickery?

33 Networking 33 Networking approach: Non-destructive Concurrent Transmissions Recall the LPP example! This worked because hardware-generated acks are very deterministic and interfere non-destructively.

34 Networking

35 Networking 35 How can we do the same with data packets? Careful timing We have access to a 26 MHz crystal We can use a timer capture module to record the time that the packet preamble is sent or received Modify packet contents deterministically OK to increment hop-count, decrement TTL, compute checksums, and apply forward error correction.

36 Networking 36 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

37 Networking 37 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

38 Networking 38 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

39 Networking 39 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

40 Networking 40 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

41 Networking 41 Solution 1: Try ALL paths at the same time Related: Ferrari et al, 2012, Lu and Whitehouse, 2009

42 Networking 42 Can we do better than flooding? NO! jk yeah

43 Networking 43 Which of these nodes are actually useful? E F B S A D C G

44 Networking 44 Solution 2: Identify Useful Forwarders with CXFS w is on some shortest path from S to D if d(s,w) + d(w,d) = d(s,d) To me To Dest End-to-end Burst Setup S Floods D measures d(s,d) w measures d(s,w) DESTINATION Setup Acknowledgement D Floods D tells d(s,d) to w, S. w measures d(d,w) w assumes d(w,d) SOURCE Data Forwarding S Floods w forwards if d(s,w) + d(w,d) <= d(s,d) OTHERWISE w sleeps.

45 Networking 45 Distance Metrics: "You go to war with the army you have" Must Fit Multi-TX Context What does RSSI mean? How do you get local information? Why not use hop count? Obeys triangle inequality (on a given flood) Low-State (one number per node) Mostly-Symmetric Augment with "boundary zone," optionally smooth it. Thursday s paper has details and evaluation.

46 Networking 46 Our Testbed Red: Forwards more frequently Close Source

47 Networking 47 Our Testbed Red: Forwards more frequently Distant Source

48 Networking 48 Implementation Details Each node gets a "slot for their data. Each slot is broken into frames where data may be sent.

49 Networking 49 What else is left? Somewhere for the data to go Recovery for lost packets Tools to configure nodes Tools for end users (setup, download, monitoring)

50 Questions/comments? 50

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