12-04-2012, 11:50 AM
Differentiated Coverage Based Key Management Scheme for Heterogeneous Sensor Networks
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Abstract
previous research on sensor network security mainly considers homogeneous sensor networks, where all sensor nodes have the same capabilities. Research has shown that homogeneous ad hoc networks have poor performance and scalability. The many-to-one traffic pattern dominates in sensor networks, and hence a sensor may only communicate with a small portion of its neighbors. Key management is a fundamental security operation. Most existing key management schemes try to establish shared keys for all pairs of neighbor sensors, no matter whether these nodes communicate with each other or not, and this causes large overhead. In this paper, we adopt a heterogeneous sensor network model to overcome these problems.
Introduction
Wireless sensor networks have applications in many areas, such as military, homeland security, health care, environment, agriculture, manufacturing, and so on. In the past several years, sensor networks have been a very active research area.
ECDH Key Management Scheme
One possible key management scheme is to permit every
LN-sensor (lower end sensor node) set up shared keys
with each of its neighbours by using the ECDH key
exchange scheme. In many existing reliable sensor
networks, nodes are obtusely deployed in the field. One
sensor node could have as many as 40 or more neighbours
in the network. Although ECC public-key cryptography is
executable for small sensor nodes, a 160-bit ECC point
multiplication still takes about less than one second. It
would need too much computational time and energy for
LN-sensor to run ECC with each of its 30 neighbours. In
this section, an efficient key distribution management
scheme requires only a small number of ECC
computations in each LN-sensor.
RELATEDWORKS
Sensing coverage in sensor networks has been well
studied. Several algorithms aim to find close-to-optimal
solution based on global information. In a linear
programming technique is applied to select the minimal
set of active nodes for maintaining coverage. In sensor
deployment strategies were investigated to provide
sufficient coverage for distributed detection.
The Energy-Efficient Differentiated Coverage Algorithm
In this section, we present our differentiated coverage (DC) algorithm for heterogeneous sensor networks. We consider a heterogeneous sensor network (HSN) consisting of two types of nodes: a small number of powerful high-end sensors (Hsensors) and a large number of low-end sensors (L-sensors). One can build a heterogeneous sensor network by distributing H-sensors and L-sensors at the same time, or by adding a small number of H-sensors into an existing homogeneous sensor network.
The differentiated coverage algorithm
The above sensing coverage scheme can be easily
extended to provide differentiated coverage for sensor
networks. If we want to adjust the sensing coverage
degree of a certain area to an arbitrary degree c, the cluster
head will correspondingly increase or decrease the work
time for each L-sensor in the area. For a grid point
covered by k sensor nodes, the work time for each sensor
node is T/k (in each round T) to provide degree-1
coverage. For degree-c coverage, the work time for each
sensor node is cT/k.
Conclusion
In this paper, we adopted a heterogeneous sensor network model to overcome the poor scalability and performance bottleneck of homogeneous sensor networks. A small number of high-end sensors are mixed together with a large number of low-end sensors to form a heterogeneous sensor network. We proposed the Differentiated coverage (DC) algorithm for heterogeneous sensor networks, which can provide different coverage degrees for different areas. In DC, cluster heads integrate sensor’s work time for covering multiple grid points and dramatically reduce the total active time for each sensor.