26-06-2012, 11:27 AM
Maintaining Sensing Coverage and Connectivity in Large Sensor Networks
[attachment=25527]
INTRODUCTION
Recent technological advances have led to the emergence of pervasive
networks of small, low-power devices that integrate sensors and actuators
with limited on-board processing and wireless communication capabilities.
These sensor networks open new vistas for many potential applications,
Since most of the low-power devices have limited battery life and
replacing batteries on tens of thousands of these devices is infeasible,
it is well accepted that a sensor network should be deployed with high
density (up to 20 nodes/m3 [23]) in order to prolong the network lifetime.
In such a high-density network with energy-constrained sensors, if all the
sensor nodes operate in the active mode, an excessive amount of energy
will be wasted, sensor data collected is likely to be highly correlated and
redundant, and moreover, excessive packet collision may occur as a result
of sensors intending to send packets simultaneously in the presence of
certain triggering events. Hence it is neither necessary nor desirable to have
all nodes simultaneously operate in the active mode.
RELATIONSHIP BETWEEN COVERAGE AND CONNECTIVITY
In this section we investigate the relationship between coverage and
connectivity. Specifically, we derive the necessary and sufficient condition
under which coverage implies connectivity — the radio range is at least
twice the sensing range.
Properties under the Ideal Case
With Lemmas 2–3, we are now in a position to discuss how to minimize
the overlap of sensing areas of all the sensor nodes. Our discussion is built
upon the following assumptions:
(A1) The sensor density is high enough that a sensor can be found at any
desirable point.
(A2) The region R is large enough as compared to the sensing range of
each sensor node so that the boundary effects can be ignored.
Assumption (A2) is usually valid. Although (A1) may not hold in practice,
as will be shown in Section 4, the result derived under (A1) still provides
insightful guidance in designing the distributed algorithm.
OPTIMAL GEOGRAPHICAL DENSITY CONTROL ALGORITHM
In this section, we propose a completely localized density control
algorithm, called OGDC, that makes use of the optimal conditions derived
in Section 3. Note that as it may not be possible to locate sensor nodes
in any desirable position (i.e., assumption (A1) may not hold), OGDC
attempts to select as working nodes the sensor nodes that are closest to the
optimal locations.
[attachment=25527]
INTRODUCTION
Recent technological advances have led to the emergence of pervasive
networks of small, low-power devices that integrate sensors and actuators
with limited on-board processing and wireless communication capabilities.
These sensor networks open new vistas for many potential applications,
Since most of the low-power devices have limited battery life and
replacing batteries on tens of thousands of these devices is infeasible,
it is well accepted that a sensor network should be deployed with high
density (up to 20 nodes/m3 [23]) in order to prolong the network lifetime.
In such a high-density network with energy-constrained sensors, if all the
sensor nodes operate in the active mode, an excessive amount of energy
will be wasted, sensor data collected is likely to be highly correlated and
redundant, and moreover, excessive packet collision may occur as a result
of sensors intending to send packets simultaneously in the presence of
certain triggering events. Hence it is neither necessary nor desirable to have
all nodes simultaneously operate in the active mode.
RELATIONSHIP BETWEEN COVERAGE AND CONNECTIVITY
In this section we investigate the relationship between coverage and
connectivity. Specifically, we derive the necessary and sufficient condition
under which coverage implies connectivity — the radio range is at least
twice the sensing range.
Properties under the Ideal Case
With Lemmas 2–3, we are now in a position to discuss how to minimize
the overlap of sensing areas of all the sensor nodes. Our discussion is built
upon the following assumptions:
(A1) The sensor density is high enough that a sensor can be found at any
desirable point.
(A2) The region R is large enough as compared to the sensing range of
each sensor node so that the boundary effects can be ignored.
Assumption (A2) is usually valid. Although (A1) may not hold in practice,
as will be shown in Section 4, the result derived under (A1) still provides
insightful guidance in designing the distributed algorithm.
OPTIMAL GEOGRAPHICAL DENSITY CONTROL ALGORITHM
In this section, we propose a completely localized density control
algorithm, called OGDC, that makes use of the optimal conditions derived
in Section 3. Note that as it may not be possible to locate sensor nodes
in any desirable position (i.e., assumption (A1) may not hold), OGDC
attempts to select as working nodes the sensor nodes that are closest to the
optimal locations.