Wireless sensor networks have emerged in recent years as a promising technology that can impact the field of structural monitoring and infrastructure asset management. Various routing protocols are used to define communication among sensor nodes of the wireless sensor network for purpose of disseminating information. These routing protocols can be designed to improve the network performance in terms of energy consumption, delay and security issues. This paper discusses the requirements of routing protocol for Structural health monitoring and presents summary of various routing protocols used for WSNs for Structural health monitoring.

1. Int. Journal of Electrical & Electronics Engg. Vol. 2, Spl. Issue 1 (2015) e-ISSN: 1694-2310 | p-ISSN: 1694-2426
195 NITTTR, Chandigarh EDIT-2015
A Survey of Routing Protocols for Structural
Health Monitoring
1
Kirandeep Kaur, 2
Amol P. Bhondekar
1
ME Scholar, Department of Electronics, NITTTR, Chandigarh, India
2
Principal Scientist, CSIR-CSIO, Chandigarh, India
kiran.saini90@gmail.com
Abstract: Wireless sensor networks have emerged in recent
years as a promising technology that can impact the field of
structural monitoring and infrastructure asset management.
Various routing protocols are used to define communication
among sensor nodes of the wireless sensor network for
purpose of disseminating information. These routing
protocols can be designed to improve the network
performance in terms of energy consumption, delay and
security issues. This paper discusses the requirements of
routing protocol for Structural health monitoring and
presents summary of various routing protocols used for
WSNs for Structural health monitoring.
Keywords: Wireless Sensor Networks, Structural Health
Monitoring, Routing protocols.
I. INTRODUCTION
Civil infrastructure, which includes bridges and buildings,
begin to deteriorate once they are built and used. Knowing
the integrity of the structure in terms of its age and usage,
and its level of safety to withstand infrequent high forces,
is important and necessary. The process of determining and
tracking structural integrity and assessing the nature of
damage in a structure is often referred to as health
monitoring. Ideally, health monitoring of civil
infrastructure consists of determining, by measured
parameters, the location and severity of damage in
buildings or bridges as they happen[1].
Wireless monitoring has emerged in recent years as a
promising technology that could greatly impact the field of
structural monitoring. Sensing devices are becoming
smaller, less expensive, more robust, and highly precise,
allowing collection of high-fidelity data with dense
instrumentation employing multi-metric sensors. Wireless
sensor networks (WSNs) leverage these advances to offer
the potential for dramatic improvements in the capability
to capture structural dynamic behavior and evaluate the
condition of structures.
II. REQUIREMENTS OF WSN FOR SHM
There are two categories of SHM techniques, local and
global. The local techniques detect the small defects in a
structure, whereas global techniques detect the significant
damages which can have large impact on the integrity of
the entire structure. Most global health monitoring
methods are centered on either finding shifts in resonant
frequencies or changes in structural mode shapes[1].
The structural health monitoring techniques poses a unique
set of requirements for the WSNs.
 Firstly, the association of sensor readings from large
number of sensor nodes which may be heterogeneous
or homogeneous.
 Secondly, reliable transmission of data is another
major requirement of SHM systems. These systems
need the data from all the sensors to calculate the
entire system response and hence are less tolerant to
the data loss[2].
 Thirdly, low powered sensor nodes are used for SHM,
so it is necessary to conserve the energy of the node.
The use of data compression, cluster based topologies
at network and node level processing can significantly
reduce the power consumption of the network.
Apart from above mentioned issues latency and security of
communication, fair access to the medium and scalability
of the network are a few other requirements that should be
taken care of.
III. ROUTING PROTOCOLS FOR SHM BASED WSNs
Energy efficiency is a critical issue in WSNs. To minimize
energy consumption, most of the device components,
including the radio, should be switched off most of the
time. The main design goal of WSNs is not only to
transmit data from a source to a destination, but also to
increase the lifetime of the network. This can be achieved
by employing energy efficient routing protocols[3]. The
existing energy-efficient routing protocols often use
residual energy, transmission power, or link distance as
metrics to select an optimal path. In recent years a lot of
attention is given for developing energy efficient and
reliable routing protocols for WSNs dedicated to SHM.
The use of these type of protocols can significantly
increase the network lifetime. Different routing protocols
used for SHM are discussed in this paper.
MHop-CL: A novel energy-efficient clustering routing
protocol was proposed for WSN on the ZhengDian
Viaduct Bridge for strain data and structural acceleration
monitoring[4].MHop-CL uses the cluster head rotation
metric to select cluster head and group nodes into cluster
based on the nodes deployment information. Three timers
are used in MHop-CL protocol. The timer1 is used for
sending the message regarding the energy information
among the intra-cluster nodes. The nodes in the same
cluster level update the intra-cluster neighbor table and
record the energy value of the intra-cluster nodes, on
receiving this message. The timer 2 is used for initiating
new round for cluster head selection and the timer 3 is used
for triggering the sample data event. In MHop-CL, the

2. Int. Journal of Electrical & Electronics Engg. Vol. 2, Spl. Issue 1 (2015) e-ISSN: 1694-2310 | p-ISSN: 1694-2426
NITTTR, Chandigarh EDIT -2015 196
network is connected and nodes in each span take the role
as cluster head every three. The energy consumption
among the nodes is well-distributed.
EGAF: Energy-Saving Geographic Adaptive Fidelity
(EGAF) is a wireless routing protocol developed for bridge
monitoring [5]. Every node in network broadcasts to a
fixed radius. Each node will receive the broadcast
messages of others and get a view of the node density in its
neighborhood. The network is divided into adjacent cells
with equal size according to the actual demand. Each node
sends information regarding node density, its ID and
residual energy to the Base station. Based on this
information base station calculates minimum and
maximum node density, minimum, maximum and average
residual energy of the network. This information is
broadcasted to all nodes which help in cluster head
selection. For Cluster Head (CH) selection each node
broadcasts a message in a fixed radius with a delay
depending upon the probability of the node to become CH.
The probability depends upon the node density and
residual energy of the node. After CH selection the nodes
join the CH with the strongest signal. The cluster head
distributes the TDMA time slot to its member nodes. They
transfer the data to the cluster head in their TDMA time
slot directly.
GDWC: Grade diffusion algorithm with LZW
Compression is designed for WSNs used for applications
such as structural health monitoring for bridges and
tunnels, border surveillance, road condition monitoring[6].
The given algorithm improves the lifetime of the wireless
sensor network by efficient routing algorithm with
compression. The grade diffusion algorithm is used to
select the efficient routing path. GD algorithm creates
routing for each sensor node and identifies its neighbor to
reduce transmission load. Each sensor node can select a
sensor node from the set of neighbor nodes when its grade
table lacks a node which is unable to transmit .The GD
algorithm update the grade value, neighbor nodes for each
sensor node using the grade diffusion algorithm. Lempel-
Ziv-Welch (LZW) compression is a dictionary based
algorithm that replaces strings of characters with single
codes in the dictionary. The algorithm sequentially reads in
characters and finds the longest string that can be
recognized by the dictionary. Then it encodes s using the
corresponding codeword in the dictionary and adds string
s+c in the dictionary, where c is the character following
string s. This process continues until all characters are
encoded. GDWC requires replacing fewer sensor nodes
and the increasing the WSN lifetime.
CLUSTER BASED DAMAGE DETECTION:
The damage detection system is based on Auto Regressive
and Auto Regressive with eXogenous input [AR-ARX]
model[7]. Data compression is employed at each node to
reduce the transmitted data. Data from multiple nodes is
gathered in cluster head where principle component
analysis (PCA) is implemented to process data before AR-
ARX A clustering strategy is designed to forward data
form nodes to base station. Each CH calculates its trigger
points and broadcasts them to its member nodes as
reference data. All the nodes in the cluster perform the
averaging procedure by using their own data and the
reference data. An optimal clustering strategy is used to
minimize the system’s energy consumption which uses
genetic algorithm as its basis. Genetic algorithm is first
carried out in base station, and the wireless sensor nodes
are disjointed through the result.
ENERGY EFFICIENT CLUSTERING: In Energy Efficient
Clustering for WSN- based SHM, uses two centralized and
one distributed algorithm for optimal clustering. The
whole network is partitioned into a number of single-hop
clusters. A cluster head (CH) is selected in each cluster to
perform intra-cluster modal analysis using traditional
modal identification algorithms. The collected data in each
cluster is then assembled together to obtain the modal
parameters for the whole structure. Compared with the
centralized approach, the cluster based modal analysis
limits the number of sensor nodes and hop count in each
cluster, thus can be more energy efficient and scalable.
Compared with the distributed approach, classic modal
parameter identification techniques which use data-level
fusion can be used in each cluster to obtain more reliable
and accurate results. This cluster-based approach is
therefore suitable for WSN-based SHM systems[8].
MSFCP: Maximum Subtree First Collection Protocol is
designed for SHM which requires high throughput, bulk
data collection. MSFCP uses multichannel block transfer
and adopts Maximum Subtree First (MSF) scheduling to
reduce interference and enhance overall throughput.
MSFCP adopts MSF scheduling, which is unsynchronized
distributed scheduling based on node's own transmission
buffer information. The key idea is to schedule
transmission in parallel along multiple branches of the tree,
and to keep the sink as busy receiving as possible. The
nodes are aware of the number of nodes in each subtree.
The subtree of a node is defined as a tree that has the child
of the node as its root. All source nodes wait for their
parent’s request if their buffer is full. The sink chooses
subtrees whose roots have a full buffer, that is, subtrees
other than the subtree whose root previously sent a block
to the sink. This strategy can keep the sink as busy as
possible and enhance the overall throughput[10].
IV. CONCLUSION
Recent years have seen growing interest in SHM based on
wireless sensor networks (WSNs) due to their low
installation and maintenance expenses. WSNs permit a
dense deployment of measurement points on an existing
structure. But the centralized SHM system suffers from
large energy consumption and latencies. This paper
surveyed various routing protocols which are dedicated to
increase the overall lifetime and accuracy of the system.
The discussed protocols use multi-hop, compression,
clustering and geographic adaptive techniques to increase
the throughput of the system and lifecycle of the network.
REFERENCES
[1] P. C. Chang, A. Flatau, and S. C. Liu, “Review Paper: Health
Monitoring of Civil Infrastructure,” Structural Health Monitoring,
vol. 2, pp. 257–267, 2003.
[2] S. Wijetunge, U. Gunawardana, and R. Liyanapathirana, “Wireless
Sensor Networks for Structural Health Monitoring : Considerations
for Communication Protocol Design,” IEEE International
Conference on Telecommunications, pp. 694–699, 2010.

3. Int. Journal of Electrical & Electronics Engg. Vol. 2, Spl. Issue 1 (2015) e-ISSN: 1694-2310 | p-ISSN: 1694-2426
197 NITTTR, Chandigarh EDIT-2015
[3] S. Yessad, N. Tazarart, L. Bakli, L. Medjkoune-Bouallouche, and D.
Aissani, “Balanced energy efficient routing protocol for WSN,”
International Conference on Communications and Information
Technology, pp. 326–330, 2012.
[4] B. Wang, “MHop-CL : A Clustering Protocol for Bridge Structure
Health Monitoring System,” International Symposium on Computer
Network and Multimedia Technology, pp. 1–4, 2009.
[5] Weidong Zhang, Jun Wan, Bin Yang, Xiwen Zhang, “An
Energy Efficient Routing Protocol in Wireless Sensor
Network for Health Monitoring,” IEEE Symposium on
Electrical & Electronics Engineering, pp. 247–250,
2012.
[6] S.Prabu, R. Maheswari., “Improving Wireless Sensor Network
Lifespan By Efficient Routing Algorithm And LZW
Compression,” ICICES, pp. 0–4, 2014.
[7] P. Nie and B. Li, “A cluster-based data aggregation architecture
in WSN for Structural Health Monitoring,” IWCMC, pp.
546–552, 2011.
[8] X. Liu, J. Cao, S. Lai, C. Yang, H. Wu, and Y. L. Xu, “Energy
efficient clustering for WSN-based structural health
monitoring,” INFOCOM, Proceedings of IEEE pp.
2768–2776, 2011.
[9] T. Kuroiwa, M. Suzuki, Y. Yamashita, S. Saruwatari, T.
Nagayama, H. Morikawa, “A multi- channel bulk data
collection for structural health monitoring using
wireless sensor networks,”APCC, pp. 295–299,
2012.