A Novel Confident Information Coverage Hole
Detection Algorithm in Sensor Networks
Zenghui Zou, Xianjun Deng
∗
, Lingzhi Yi, Zujun Tang, Minghua Wang, Xueyu Gong
The Department of Communications Engineering, University of South China(USC), Hengyang, China
*: Corresponding Author, Email: dengxj615@gmail.com
Abstract—The emergence and existence of coverage holes in
WSNs will dramatically degrade the network coverage perfor-
mance and quality of service. To diminish the negative effects
of coverage holes, this paper studies the confident information
coverage hole detection problem(CICHD) based on the proposed
novel confident information coverage model(CIC). For solving
the CICHD problem, we design an effective heuristic CIC hole
detection algorithm. In the proposed algorithm, the sensing field
is firstly partitioned into a series of reconstruction grids based
on the spatial correlation and correlation range. Then each
reconstruction grid will be scanned and detected based on the
CIC model to be judged whether it is a coverage hole or not.
After obtaining the coverage status of each reconstruction grid,
the coverage hole boundary will be extracted by image processing
method. Simulation results show that the proposed scheme
can efficiently detect the emerged coverage holes including the
locations and the number.
Index Terms—Confident Information Coverage, Coverage Hole
Detection, Wireless Sensor Networks
I. INTRODUCTION
Wireless sensor networks(WSNs) recently have been de-
ployed for a wide range of crucial applications with strin-
gent accuracy requirements[1][2]. Many of the sensing and
monitoring environment of these applications is hazardous and
unfriendly, it is hardly to deterministically deploy the sensors,
so the sensors can only be randomly scattered around the
sensing field.
The random deployment of sensor nodes will lead to
some uncovered blank subregions which are called coverage
holes[3] in the sensing field. In addition to the randomness
feature, the limited energy of the battery powered nodes, the
depletion of the nodes due to the unbalanced energy con-
sumption also unavoidably cause the coverage holes[4], which
would seriously impact the network coverage performance.
Coverage, as a critical factor for the success of a WSN, re-
flects how well a field is sensed and monitored[5]. The WSN-
based applications nearly always have stringent requirements
on the network coverage performance and quality of service.
However, these coverage requirements would not always be
satisfied because of the emerged and existed coverage holes,
thus it extremely needs to detect and localize the coverage
holes, which we refer to as the coverage hole detection
problem.
In order to solve the coverage hole detection problem, a
wide range of efforts have been done[8]-[9]. However, most
of the current studies on the coverage hole detection are based
on the disk coverage model, which defines a disk centered at
the sensor with the radius of its sensing range [5][6][7]. The
disk coverage model is too simple and idealistic to be applied
in many practical applications, especially in the WSN-based
applications with rigid accuracy and error requirements.
To overcome the deficiencies of the disk model based hole-
detection schemes, in this paper, we study how to efficiently
detect the coverage holes of a WSN utilizing the confident
information coverage model(shorted as CIC or Φ-coverage)
which is a novel coverage model proposed in our previous
study[10]. We first address and model the Confident Infor-
mation Coverage Hole Detection(CICHD) problem with the
goal of finding all the locations and number of the confident
information coverage holes.
For solving the CICHD problem, we design an effective
heuristic confident information coverage hole detection al-
gorithm named CHD, which takes the Root Mean Square
Error(RMSE) as the evaluation indicator to judge a subregion
whether is a CIC coverage hole or not. The main idea of the
CHD scheme is to firstly partition the hole-detection required
sensing field into a series of reconstruction grids based on the
spatial correlation of the monitored physical attribute, and then
calculate the RMSE using the confident information coverage
model and compare it with the given RMSE threshold to
judge each grid whether is a hole. Once the RMSE of a
reconstruction grid is greater than the given threshold which
means the grid is a confident information coverage hole, the
CHD will extract the boundary of the CIC hole by using the
image processing methods. After achieving the coverage status
of each reconstruction grid, the CHD could obtain the two-
dimensional black-and-white image of the sensor network by
binarization, and suppress the image noise by using open and
close loop operations so that the shape features are maintained
and the irrelevant structures are removed. After that, the
boundary of the confident information coverage holes can be
successfully extracted.
The rest of this paper is organized as follows. Section II
reviews some coverage hole detection work studied in WSNs.
Section III presents the formal definition of the confident
information coverage hole detection problem. The proposed
heuristic algorithm is shown in Section IV and evaluated via
simulations in Section V. We conclude the paper in Section VI.
II. R
ELATED WORK
The emerged coverage holes will break the running of a
WSN and eventually lead to the failure of a specific WSN-
2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom)
and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
978-1-5090-5880-8/16 $31.00 © 2016 IEEE
DOI 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.57
199
2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom)
and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
978-1-5090-5880-8/16 $31.00 © 2016 IEEE
DOI 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.57
199
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