1. coverage holes of the network for unequal sensing

1.     Related Work

 

Two of the most essential and
common problems in WSN are holes area coverage and node connectivity. So many researchers
focused on maximizing coverage and enhancing connectivity across the ROI 10. Authors
in 15 presents strategies for efficient deployment in a mobile sensor
network, where the priority function is defined by a coverage priority of some proposed
points in the ROI. The coverage holes of the network for unequal sensing ranges
of the sensors is utilized by variable weighted Voronoi technique. Each sensor node
works on its Voronoi cell to detect the coverage holes, and then tries to
reduce their size by moving another direction. The weight of the vertices
inside the each Voronoi cell determines the target location of each sensor node.

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The authors in 16 propose a novel
algorithm based on algebraic objects, such as Cech complex and Rips complex to accurately
gain information about coverage hole, it depends on the ratio between
communication and sensing radius of a sensor. The authors in 17 propose two novel
algorithms to detect the coverage holes in ROI. The holes borders and their
adjacent nodes can be easily detected by the first algorithm, Distributed
Sector Cover Scanning (DSCS), while locating the coverage holes is done by the
second algorithm, Directional Walk (DW).

 

In 18
by defining a
new deep sleeping technique the authors propose an energy efficient algorithm based on
the sentinel scheme to reduce the sleeping node detection density. Network life
time and power consumption are the factors to calculate the detection rate. In
addition, the coverage holes is addressed by using triangle coverage repair
procedure to heal the coverage hole.

 

 

The authors in 19
propose a method that reduces the complexity of the relocation of the initial
deployment and coverage hole healing of mobile sensor nodes in the hybrid WSNs.
Their method finds the ways to get the shortest distance movements for the
mobile nodes in WSNs. An adaptive threshold distance is used to eliminate some
mobile nodes, which are already occupied or situated within the threshold distance
from the optimal new positions. The authors in 20 propose an optimal sensor
deployment in ROI under different nodes communication ranges to achieve the
full coverage. They introduces a novel triangle based pattern called the
Diamond to easily detect and cover the holes while the nodes are in the same
communication range.

 

The authors in 21
propose a coverage hole detection algorithms for detecting the holes boundary
in ROI, where sensor nodes can detect their points of intersection of their sensing
discs. The algorithm takes in consideration these points of intersection to
detect the boundaries of the coverage holes.

The authors in 22 propose an
algorithm based on the well-known Voronoi diagram. It can recognize the coverage
holes by comparing the size of voronoi cell to this corresponding node’s
sensing disc, and label the border nodes of coverage holes effectively by using
simple geometric calculations.