By Ryan Berger

What are sensor networks? Network consisting of spatially distributed

autonomous devices using sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants, at different locations.

The sensors themselves can range from small passive microsensors (e.g, "smart dust") to larger scale, controllable weather-sensing platforms.

Quick Rundown They have micro-sensors, on-board

processing, wireless interfaces feasible at very small scale

Can monitor phenomena “up close” Enables spatially and temporally

dense environmental monitoring

Who uses Sensor Networks? The development of wireless sensor

networks was originally motivated by military applications such as battlefield surveillance.

Sensor networks are now used in many civilian application areas, including environment and habitat monitoring, healthcare applications, home automation, and traffic control.

Potential Uses High-rise buildings self-detect structural faults (e.g., weld

cracks) Schools detect airborn toxins at low concentrations, trace

contaminant transport to source Buoys alert swimmers to dangerous bacterial levels Earthquake-rubbled building infiltrated with robots and

sensors: locate survivors, evaluate structural damage Ecosystems infused with chemical, physical, acoustic,

image sensors to track global change parameters Battlefield sprinkled with sensors that identify track

friendly/foe air, ground vehicles, personnel Parking lots or garages keep track of which spots are

occupied and which aren’t

Seismic Structure response Ecosystems, Biocomplexity

Possible Scenario May 1st, 2003 Two days before the

collapse of the Old Man in the Mountain

Could this have been prevented by using sensors?

Possible Scenario May 2nd, 2003 Movement in the rock

structure detected Data archiving begins Models generate

predictions, provided to local emergency managers for planning

Possible Scenario May 3rd, 2003 Because instability

was detected early, a team is sent in to brace the structure to prevent further movement

Team begins renovations on structure

Local residents and tourists are evacuated to prevent possible injury

Possible Scenario May 24th, 2003 The old man lives! Renovations are

complete Sensors have reported

that the rocks are structurally sound (for now)

Citizens are welcomed back into their homes

This use of sensors is known as area monitoring

Another Application

Invaluable Fire Fighting Tool

FIRE Eye

Receiver Hardware Types ZigBee

Other Hardware Types

Wibree 6lowpan

Programming Languages Implemented c@t (Computation at a point in space

(@) Time ) DCL (Distributed Compositional

Language) galsC nesC Protothreads SNACK SQTL

Generally Runs Using…

TinyOS

An Example of an Interface (MonSense)

Characteristics of Each Sensor

Types of Sensors

Passive elements: seismic, acoustic, infrared,

strain, salinity, humidity, temperature, etc.

Passive arrays: imagers (visible, IR), biochemical

Active sensors: radar, sonar

High energy, in contrast to passive elements

Desired Designs Self-configuring systems that adapt to

unpredictable environment Dynamic, messy (hard to model), environments include

pre-configured behavior

Leverage data processing inside the network Collaborative signal processing Achieve desired behavior with localized algorithms

(distributed control)

Why simply adapting an IP “end-to-end” network doesn’t work Internet routes data using IP Addresses in Packets and

Lookup tables in routers Humans get data by “naming data” to a search engine Many levels of indirection between name and IP address Embedded, unattended systems can’t tolerate

communication overhead of indirection Special purpose system functions: don’t need or want

Internet general purpose functionality designed for elastic applications that may change without warning.

The Importance of Time and Location Unlike Internet, node time/space location essential

for local/collaborative detection Fine-grained localization and time synchronization

needed to detect events in space and compare detections across nodes

GPS provides solution where available GPS not always available, too “costly,” too bulky other approaches under study

Localization of sensor nodes has many uses Beamforming for localization of targets and events Geographical forwarding Geographical addressing

Coverage Measures Area coverage: fraction

of area covered by sensors

Detectability: probability sensors detect moving objects

Node coverage: fraction of sensors covered by other sensors

Control: Where to add new nodes

for max coverage How to move existing

nodes for max coverageSensor field (either known sensor locations, or spatial density)

S

D

Traditional Approach: Warehousing

Warehouse

Front-end

Sensor Nodes

Alternative Approaches

Distributed Storage Event-to-Sink Reliable Transport

Distributed Storage Data Centric Protocols, In-network Processing goal:

Network does in-network processing based on distribution of data

Queries automatically directed towards nodes that maintain relevant/matching data

Pattern-triggered data collection Multi-resolution data storage and retrieval Distributed edge/feature detection Index data for easy temporal and spatial searching (quick

access to recently recorded data)

Distributed Storage Approach

SensorDBSensor

DB

SensorDB

SensorDB Sensor

DB

SensorDB

SensorDB

SensorDB

Front-end

Sensor Nodes

Performance of Distributed Storage

High accuracy?Distance between ideal answer and actual answer differsRatio of sensors participating in answer also differs

Low latencyTime between data is generated on sensors and answer is

returned within a short period of time Limited resource usage

Energy consumption is high

Distributed Storage Issues

Need for Coordination/Distributed Resource AllocationMultiple sensors need to collaborate on tasks

○ View objects of interest from multiple angles with different types of sensors

○ Sensing time windows need to be closely alignedEnvironmental Dynamics

○ Sensor configuration changes as target moves○ Multiple target in overlapping sensor regions

Distributed Storage Issues, cont. Soft Real-time

Limited time window for sensingMust anticipate where target is moving in order to

effectively allocate sensor resourcesTime for coordination affects time for sensing

Scalability: need to be able to handle large numbers of sensor nodes

Robustness: local failures should not induce global collapseHandle uncertain information,

sensor/processor/communication failures

Soft vs. Hard Real-Time

Soft: There are not catastrophic effects if events are occasionally not interpreted correctlyIf lose sight of target for a bit, time steps and

then reacquire (generally works okay)

Hard: Computation/Sensing after the “deadline” may or may still have valueReduction in certainty of target location

Event-to-Sink Reliable Transport (ESRT) Event-to-sink reliability Self-configuration Energy awareness (low power

consumption requirement!) Congestion Control Variation in complexity at source and

sink (computation complexity)

S

ESRT Approach

SensorDBSensor

DB

SensorDB

IndexNode DB Sensor

DB

SensorDB

SensorDB

SensorDB

Front-end

Sensor Nodes

Reliability of an ESRT Reliability is measured in terms of the

number of packets received Number of received data packets in

decision interval at the sink Number of packets required for

reliable event detection Normalized reliability =

observed ÷ desired

Issues with ESRT

Information can be lost if the indexing node fails

Indexing node can become overloaded Because of this, indexing node may

need to be selective in the nodes it processes

Time taken for selection/transfer from sensors to index may result in the processing of “old” data

How to “Overcome” Shortcomings

Avoid processing overloads Avoid communication overloads Have information/processing co-located Avoid failure of network based on single

location failure Allocate sensing so that as many targets can

be tracked with reasonable success Allocate processing/sensing so that real-time

constraints can be met

Radar Parameter Display Image

Transfer with 90% losses

Radar Parameter Display Image

Transfer with no losses

Error Detection Node information is propagated through the use of

directory servicesSensors provide sector managers with their information.“Track managers” query sector managers for sensor

details.This information is cached for future use at each step

The directory held in sector manager maintains historical query informationNew data is analyzed for relevance to those queriesRelevant information is automatically propagated to the

query source

This process quickly updates each node’s data, allowing them to adapt to change

What We’ve Learned (In a Nutshell)… What sensor networks are Examples of how they might be used Overview of how they work Desired designs Coverage measures Different approaches to set-up Error detection (very brief)

Sensor Networks in the News Researchers plan to install 100 sensors

by 2011 on streetlamps throughout the city of Cambridge, MA

Distributed Traffic Light Control Microfluidics for water supply protection

In Conclusion… Sensor Networks = Incredibly useful,

perhaps vital technology There is no one best approach

Very sensitive to characteristics/capabilities of sensors, quality of sensor data, amount and type of processing required, system objectives, communication and processing capabilities, environment, etc…

This is a technology that will only become more prevalent in our everyday lives