28-01-2012, 04:52 PM
Mobility Management Algorithms and Applications for Mobile Sensor Networks
[attachment=16819]
INTRODUCTION
The development of wireless technologies and microsensing
MEMS has triggered the success of wireless sensor
networks (WSNs). A WSN is composed of one or multiple
remote sinks and many tiny, low-power sensors, each
equipped with actuators, sensing devices, and wireless
transceivers [1]. These sensors are massively deployed
in a region of interest (ROI) to continuously collect and
report surrounding data. WSNs offer a convenient way
to monitor physical environments. Many applications such
as object tracking, health monitoring, security surveillance,
and intelligent transportation [2]–[5] have been proposed.
Voronoi-based (VOR) method: A sensor should move
toward the farthest vertex of its current polygon. Fig. 2(b)
gives an example, where the dotted polygon is sensor si’s
current polygon and u is the farthest vertex. Sensor si will
move along the direction ¡! siu and stop at v1, where juv1j =
rs.
Minimax method: A sensor should move to the minimax
point of its current polygon, where the minimax point of a
polygon is the center of the circle with the minimum radius
that can cover the whole polygon (refer to [13] for details
about finding the circle). Fig. 2© gives an example, where
v2 is the minimax point of si’s current polygon.
MOBILITY MANAGEMENT OF MOBILE
SENSORS
2.1 Solutions to Deploying Mobile Sensors
Sensor deployment is a basic issue since it decides a WSN’s
detection ability. A good deployment should satisfy both
coverage and connectivity [8], [9]. Coverage requires that
each location in the ROI be monitored by sensors, and
connectivity requires that the network remain not partitioned.
With mobile sensors, the deployment job becomes
‘automatic’. We introduce three deployment methods: The
force-based deployment images that virtual forces will drive
sensors to move. The graph-based deployment identifies uncovered
holes and moves sensors to cover them. The
assignment-based deployment computes the locations to be
placed with sensors and then dispatches them in an energyefficient
way.
Solutions to Enhancing Coverage andConnectivity of a WSN
After deploying a WSN, some sensors may be broken
or may exhaust their energy. These failed sensors may
disconnect the network or cause uncovered holes. One can
move some mobile sensors to relieve this problem. We
introduce two such solutions for enhancing connectivity
and coverage of a WSN.
[attachment=16819]
INTRODUCTION
The development of wireless technologies and microsensing
MEMS has triggered the success of wireless sensor
networks (WSNs). A WSN is composed of one or multiple
remote sinks and many tiny, low-power sensors, each
equipped with actuators, sensing devices, and wireless
transceivers [1]. These sensors are massively deployed
in a region of interest (ROI) to continuously collect and
report surrounding data. WSNs offer a convenient way
to monitor physical environments. Many applications such
as object tracking, health monitoring, security surveillance,
and intelligent transportation [2]–[5] have been proposed.
Voronoi-based (VOR) method: A sensor should move
toward the farthest vertex of its current polygon. Fig. 2(b)
gives an example, where the dotted polygon is sensor si’s
current polygon and u is the farthest vertex. Sensor si will
move along the direction ¡! siu and stop at v1, where juv1j =
rs.
Minimax method: A sensor should move to the minimax
point of its current polygon, where the minimax point of a
polygon is the center of the circle with the minimum radius
that can cover the whole polygon (refer to [13] for details
about finding the circle). Fig. 2© gives an example, where
v2 is the minimax point of si’s current polygon.
MOBILITY MANAGEMENT OF MOBILE
SENSORS
2.1 Solutions to Deploying Mobile Sensors
Sensor deployment is a basic issue since it decides a WSN’s
detection ability. A good deployment should satisfy both
coverage and connectivity [8], [9]. Coverage requires that
each location in the ROI be monitored by sensors, and
connectivity requires that the network remain not partitioned.
With mobile sensors, the deployment job becomes
‘automatic’. We introduce three deployment methods: The
force-based deployment images that virtual forces will drive
sensors to move. The graph-based deployment identifies uncovered
holes and moves sensors to cover them. The
assignment-based deployment computes the locations to be
placed with sensors and then dispatches them in an energyefficient
way.
Solutions to Enhancing Coverage andConnectivity of a WSN
After deploying a WSN, some sensors may be broken
or may exhaust their energy. These failed sensors may
disconnect the network or cause uncovered holes. One can
move some mobile sensors to relieve this problem. We
introduce two such solutions for enhancing connectivity
and coverage of a WSN.