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15 Νοε 2013 (πριν από 4 χρόνια και 8 μήνες)

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EECE 621 Talk 7:


Systems for WSNs

Prof. Sunggu Lee



This talk addresses general topics of mobility and use
of “swarm intelligence” techniques in WSNs

Mobility in WSNs

Introducing the possibility of mobile wireless sensor nodes increases
the range of issues, research problems, applications, etc., considered
with respect to WSNs

E.g., New problem of inserting

mobile sensors into a field of stationary
sensors in order to increase the sensing coverage to a specific desired level

Combines robot technology with sensor, wireless communication, and
microcomputer technology

There is a problem with energy conservation (mobile nodes will use a
lot more energy)

Applications may be limited, but such applications are still possible

In the future, miniature low
power robots may become feasible

thus, it
may still make sense to discuss mobility in WSNs as part of future


Swarm Intelligence

Defn. and explanation of term

refer to wikipedia

The emergence of complex, global behavior from
interactions among many simple agents

Most commonly used examples

Bees in a beehive

Ants in an ant colony

An extremely interesting research topic, actively
studied in universities and other research institutions

Can be considered as a form of “biomimetics”

Also know as “biomimicry”

“… application of biological

and systems found in

to the study and design of

systems and


Implementation Considerations

Most hardware implementations of swarm intelligence
ideas use a small number of mobile nodes as part of
a “prototype system”

Due mainly to cost considerations

There may also be programming/control difficulties if
extremely large numbers of mobile nodes are used

Behavior of natural systems do not need to followed

Natural systems can serve as simply a guide or a source of
ideas regarding methods for solving certain problems

Engineering considerations may require changes to the basic


Bot Systems [text]

Ch. 6 of [text] describes a project involving the use
of a small number of “ant
bots” used to demonstrate
cooperative intelligence concepts

Prototype system consists of a PCB board (with an
Atmega128L microcontroller and a CC2420 ZigBee
radio chip) attached to a programmable toy car

Refer to Figures 6.1 and 6.2 of [text]

Focus is not on the mechanical aspects of mobile sensor
nodes, but the design and implementation of communication
methods, positioning and cooperative behavior in such


Cooperative Localization

Localization algorithm used here is different
from methods typically used in such systems
(to be discussed in next talk)

Coordinate systems used for robot systems

Absolute coordinates: each robot calculates its
coordinates with respect to an external common
coordinate system

Typically uses GPS or pre
established landmarks

Relative coordinates: each robot determines its
coordinates with respect to a reference point
within the operating environment


Relative Coordinate Localization

Initial phase

A selected coordinator moves around the circumference of a
circle and broadcasts a sequence of beacons

Each beacon packet contains coordinate of selected
coordinator, coordinator’s ID, and the transmitted power level

Each ant
bot within the transmission range of coordinator
can determine its own coordinates if it receives three
different position beacons

Based on triangulation or trilateration (refer to next talk)

Iterative phase

Suppose there exist “red” ant
bots (nodes that have not
received three separate position beacons)

Each ant
bot with known coordinates can repeat initial
phase with itself as the coordinator


Other Implementation Issues

Avoiding collisions among robots

bot uses the received signal strength indication (RSSI)
as main tool for avoiding collisions

RSSI can

also be used for distance measurements

Also uses information about the mutual orientations of ant

Authors also claim to have developed a distributed approach
for determining dynamic routes for each ant

Demo implementation

Text/graphics arrangement game

robots move to form
specific letters or shapes

Example: Refer to Figure 6.14 of [text]


Coordinator Election

A set of independently behaving nodes must send messages
back and forth in order to elect a unique coordinator node

Method used in this chapter

Sink node broadcasts Coordinator Election message

Each ant
bot backs off for a short period based on the RSSI (the
farther the distance, the shorter the backoff period)

If backoff time expires, ant
bot separately broadcasts a Coordinator
Election message

If Coordinator Election message is received before backoff timer
expires, the message is received and then a new backoff period based
on RSSI is


An ant
bot that receives two Coordinator Election messages
compute a backoff period based on RSSI (the farther …)

When backoff timer expires, ant
bot broadcasts Coordinator

If Coordinator message is received, an ACK Coordinator message is
sent and then a Stop Electing message is broadcast



[Figure 6.5 of [text]]

Position Measurement

If GPS is not available (low
cost or indoor
environment), then an indoor position
estimation method must be used

Most existing localization methods make use of
range measurements based on RSSI, time of
arrival (ToA) of a communication signal, time
difference of arrival (TDoA) or angle of arrival

RSSI is most commonly used because of its

however, it is not very accurate

Distance estimate based on measurement of the strength
of received radio signal versus initial radio signal strength


Direction Measurement

Each ant
bot is equipped with an
electronic compass

The ant
bot knows which direction it is facing

bot can be programmed to turn in any
direction by giving desired angle and current

Once target’s coordinates are known, each
bot must plan a route to the target

Compute angle and distance of target

Equations given in Section 6.4.3 (pp. 175


Minimap Integration

A fixed 8 x 8 minimap model is used to represent the
environmental data for an ant
bot in its coverage area

bot uses infrared or ultrasound sensors to determine positions
of obtacles

Based on approximate distance measurements to obstacles

Any time fixed parameter values are used (such as 8 x 8), the
selection of those parameter values must be justified, preferably
by analytical techniques

In this case, 8 x 8 minimap was used because of engineering

Wanted to use 64
bit (8 x 8) fixed packet sizes

Larger maps are created by combining the minimap
information provided by several adjacent ant

Coordinator creates this combined map

e.g., Fig. 6.9 of [text]



[Fig. 6.9 of [text]]

Collaborative Path Planning

Proposed collaborative path planning
algorithm is a heuristic method based on
locations of obstacles and angle and
distance measurements

Actions of individual ant
bots must be controlled
determined such that collisions are avoided

Priority order of direction to be followed
determined based on assigned direction and
current location of ant

Refer to Figure 6.10 of [text]

Refer to [text] for more details



[Fig. 6.10 of [text]]


[Fig. 6.11 of [text]]