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An Intelligent and Adaptable Grid-Based Flood Monitoring
and Warning SystemPhil Greenwood
The Problem Flooding is becoming a more common
occurrence Climate change Land use
Cost of damage correlates with Rate of flow Depth of water Warning time given
To cope with this problem initiatives taken to:
Improve flood defences Raise public awareness Improve flood warning systems
Traditional Approaches
Deploy sensors at flood prone sites Collect data manually or transmitted
using GSM technology Data then processed using spatial or
point-based prediction algorithms The results from these algorithms
can be used to issue flood warnings
Limitations Rigid separation between on-site sensor
network and off-site computation Grid Tends to be bottleneck
The sensors used are computationally dumb They simply record and store/transmit data Data holds valuable information on how the
sensors should behave No variation in the sensor behaviour
possible Turn device off when un-interesting events
occurring Increase frequency of measurements made No dissemination of warnings
Proposed Approach Increase local computational power of
sensors Allow the local execution of flood
prediction algorithms i.e. light-weight Grid Adaptation of the wireless sensor network
Support a wider range of hardware Novel techniques for flood prediction and
analysis Timely distribution of flood warnings
Proactive and passive warnings SMS/Audio-Visual/Web
The GridStix Platform
Consists of a variety of hardware and software: Gumstix hardware platform Lancaster’s GridKit middleware
platform Various networking technologies Flood prediction algorithms
Gumstix (1)
Gumstix (2) Specs
400Mhz Intel XScale processor 64Mb RAM 16Mb Flash Memory
Variety of I/O Mechanism Standard Ethernet port Compact Flash slot
• Storage• 802.11b Networking • GPRS
GPIO Lines for sensor connectivity On-board Bluetooth Radio
Power Consumption
Significantly higher power consumption than devices used in traditional sensor networks Berkley Motes typically use 54mW Gumstix use 1W
Can be powered using a combination of batteries and solar panels One 15cm2 solar panel output of 1.9W 6v 10AH battery Aggressive power management
GridKit (1) Provides key functionality to implement
Grid behaviour Service Binding Resource Discovery Resource Management Security
Based on the OpenCOM component model Rich support Stripped-down deployments
Overlay support Used to implement networking service not
provided by the underlying network type
Overlay (1)
CONTROL
…CREATE
JOIN
LEAVE
DELIVER…
FORWARD
…ROUTE
SEND
RECEIVE…
STATE
IForward
I{Overlay}State
IDeliver IForward IForward
IDeliver
IForward
Overlay (2)
CONTROL
JOIN
LEAVE
FORWARD
ROUTE
SEND
STATE
LEAF SET
NEIGHBOUR SET
ROUTING TABLE
CONTROL
PING
PONG
FORWARD
QUERY
PUSH
STATE
NEIGHBOURS
Gnutella CF
Pastry CF
ISearch
IForward
IForward IForward
IDeliver
IControl
Supported Adaptations
CPU Adaptation Throttle CPU frequency
Overlay Adaptations Swap overlay components to alter
topology Physical Network Adaptations
Switch network types
Adaptation Scenario 1
Changes in Criticality Need to conserve power in normal
operating conditions Operate at lowest CPU frequency Poll sensor infrequently
Potential Flooding Detected GridStix can increase CPU frequency to
execute prediction algorithms quicker Data can also be collected more
frequently to improve the accuracy of the predictions
Adaptation Scenario 2
Adapting to Node Failure Need to increase the robustness of
network when flooding is predicted Do this without changing network
type Switch overlay types
Shortest path trees consume less power
Fewest hop trees are more robust
Adaptation Scenario 2 cont.
Root
Node B Node C
Edg
e x E
dge x
Node D
Edg
e x
Node E
Edge x
Node F
Edg
e x
Root
Node B Node DNode C
Node FNode E
Shortest Path Fewest Hops
Trigger: Flooding predicted by a Gumstix.
• Bluetooth used by default due to lower power requirements.
•Shortest-Path tree overlay used due to its power conservation characteristics.
• Bluetooth continues to be used.
• Fewest Hop tree overlay applied to increase the robustness of the tree.
Adaptation Scenario 3
Node Submersion Likely that nodes will become submerged
during flooding Want nodes to remain connected for as
long as possible Switch network types when
submersion is predicted Bluetooth -> Wifi or Wifi -> GPRS High power consumption and increased
range
Adaptation Scenario 3 cont.
Root
Node B Node DNode C
Node FNode E
Fewest Hops
Trigger: Submersion predicted by a Gumstix.
• Switch from Bluetooth to Wifi
• Same overlay type used.
• However, the different characteristics of Wifi causes a new topology to be created.
Root
Node B Node FNode D Node ENode C
Fewest Hops
Current Status Small test-bed of nodes currently deployed:
Three Gumstix Nodes Depth Sensors Image-based Flow Sensors
Additional nodes are being added, to initial deployment size of 13 nodes.
Performance of network hardware, solar panels and other hardware is being tested in the field.
Future Work Development of a simulator to test
deployment approaches with past and predicted flood events.
Bringing in more highly embedded hardware running the RUNES GridKit implementation.
Integration with Lancaster’s main NW Grid Deployment.
Summary Proposes a more automatic and
sophisticated mechanism for collecting and processing flood data
Convergence of Grid and Wireless Sensor Network functionality
Uses this sophisticated mechanisms for performing adaptations
Can customise the configuration and behaviour of sensors to the current environmental conditions