A Survey of Routing Protocols for Structural Health Monitoring

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 StructuralHealth Monitoring

1Kirandeep Kaur, 2Amol P. Bhondekar1ME Scholar, Department of Electronics, NITTTR, Chandigarh, India

2Principal Scientist, CSIR-CSIO, Chandigarh, [email protected]

Abstract: Wireless sensor networks have emerged in recentyears as a promising technology that can impact the field ofstructural monitoring and infrastructure asset management.Various routing protocols are used to define communicationamong sensor nodes of the wireless sensor network forpurpose of disseminating information. These routingprotocols can be designed to improve the networkperformance in terms of energy consumption, delay andsecurity issues. This paper discusses the requirements ofrouting protocol for Structural health monitoring andpresents summary of various routing protocols used forWSNs for Structural health monitoring.

Keywords: Wireless Sensor Networks, Structural HealthMonitoring, Routing protocols.

I. INTRODUCTIONCivil infrastructure, which includes bridges and buildings,begin to deteriorate once they are built and used. Knowingthe 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 andtracking structural integrity and assessing the nature ofdamage in a structure is often referred to as healthmonitoring. Ideally, health monitoring of civilinfrastructure consists of determining, by measuredparameters, the location and severity of damage inbuildings or bridges as they happen[1].Wireless monitoring has emerged in recent years as apromising technology that could greatly impact the field ofstructural monitoring. Sensing devices are becomingsmaller, less expensive, more robust, and highly precise,allowing collection of high-fidelity data with denseinstrumentation employing multi-metric sensors. Wirelesssensor networks (WSNs) leverage these advances to offerthe potential for dramatic improvements in the capabilityto capture structural dynamic behavior and evaluate thecondition of structures.

II. REQUIREMENTS OF WSN FOR SHMThere are two categories of SHM techniques, local andglobal. The local techniques detect the small defects in astructure, whereas global techniques detect the significantdamages which can have large impact on the integrity ofthe entire structure. Most global health monitoringmethods are centered on either finding shifts in resonantfrequencies or changes in structural mode shapes[1].

The structural health monitoring techniques poses a uniqueset of requirements for the WSNs.

Firstly, the association of sensor readings from largenumber of sensor nodes which may be heterogeneousor homogeneous.

Secondly, reliable transmission of data is anothermajor requirement of SHM systems. These systemsneed the data from all the sensors to calculate theentire system response and hence are less tolerant tothe 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 topologiesat network and node level processing can significantlyreduce the power consumption of the network.

Apart from above mentioned issues latency and security ofcommunication, fair access to the medium and scalabilityof the network are a few other requirements that should betaken care of.

III. ROUTING PROTOCOLS FOR SHM BASED WSNsEnergy efficiency is a critical issue in WSNs. To minimizeenergy consumption, most of the device components,including the radio, should be switched off most of thetime. The main design goal of WSNs is not only totransmit data from a source to a destination, but also toincrease the lifetime of the network. This can be achievedby employing energy efficient routing protocols[3]. Theexisting energy-efficient routing protocols often useresidual energy, transmission power, or link distance asmetrics to select an optimal path. In recent years a lot ofattention is given for developing energy efficient andreliable routing protocols for WSNs dedicated to SHM.The use of these type of protocols can significantlyincrease the network lifetime. Different routing protocolsused for SHM are discussed in this paper.

MHop-CL: A novel energy-efficient clustering routingprotocol was proposed for WSN on the ZhengDianViaduct Bridge for strain data and structural accelerationmonitoring[4].MHop-CL uses the cluster head rotationmetric to select cluster head and group nodes into clusterbased on the nodes deployment information. Three timersare used in MHop-CL protocol. The timer1 is used forsending the message regarding the energy informationamong the intra-cluster nodes. The nodes in the samecluster level update the intra-cluster neighbor table andrecord the energy value of the intra-cluster nodes, onreceiving this message. The timer 2 is used for initiatingnew round for cluster head selection and the timer 3 is usedfor triggering the sample data event. In MHop-CL, the


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network is connected and nodes in each span take the roleas cluster head every three. The energy consumptionamong the nodes is well-distributed.

EGAF: Energy-Saving Geographic Adaptive Fidelity(EGAF) is a wireless routing protocol developed for bridgemonitoring [5]. Every node in network broadcasts to afixed radius. Each node will receive the broadcastmessages of others and get a view of the node density in itsneighborhood. The network is divided into adjacent cellswith equal size according to the actual demand. Each nodesends information regarding node density, its ID andresidual energy to the Base station. Based on thisinformation base station calculates minimum andmaximum node density, minimum, maximum and averageresidual energy of the network. This information isbroadcasted to all nodes which help in cluster headselection. For Cluster Head (CH) selection each nodebroadcasts a message in a fixed radius with a delaydepending upon the probability of the node to become CH.The probability depends upon the node density andresidual energy of the node. After CH selection the nodesjoin the CH with the strongest signal. The cluster headdistributes the TDMA time slot to its member nodes. Theytransfer the data to the cluster head in their TDMA timeslot directly.

GDWC: Grade diffusion algorithm with LZWCompression is designed for WSNs used for applicationssuch as structural health monitoring for bridges andtunnels, border surveillance, road condition monitoring[6].The given algorithm improves the lifetime of the wirelesssensor network by efficient routing algorithm withcompression. The grade diffusion algorithm is used toselect the efficient routing path. GD algorithm createsrouting for each sensor node and identifies its neighbor toreduce transmission load. Each sensor node can select asensor node from the set of neighbor nodes when its gradetable lacks a node which is unable to transmit .The GDalgorithm update the grade value, neighbor nodes for eachsensor node using the grade diffusion algorithm. Lempel-Ziv-Welch (LZW) compression is a dictionary basedalgorithm that replaces strings of characters with singlecodes in the dictionary. The algorithm sequentially reads incharacters and finds the longest string that can berecognized by the dictionary. Then it encodes s using thecorresponding codeword in the dictionary and adds strings+c in the dictionary, where c is the character followingstring s. This process continues until all characters areencoded. GDWC requires replacing fewer sensor nodesand the increasing the WSN lifetime.

CLUSTER BASED DAMAGE DETECTION:The damage detection system is based on Auto Regressiveand Auto Regressive with eXogenous input [AR-ARX]model[7]. Data compression is employed at each node toreduce the transmitted data. Data from multiple nodes isgathered in cluster head where principle componentanalysis (PCA) is implemented to process data before AR-ARX A clustering strategy is designed to forward dataform nodes to base station. Each CH calculates its triggerpoints and broadcasts them to its member nodes asreference data. All the nodes in the cluster perform theaveraging procedure by using their own data and the

reference data. An optimal clustering strategy is used tominimize the system’s energy consumption which usesgenetic algorithm as its basis. Genetic algorithm is firstcarried out in base station, and the wireless sensor nodesare disjointed through the result.

ENERGY EFFICIENT CLUSTERING: In Energy EfficientClustering for WSN- based SHM, uses two centralized andone distributed algorithm for optimal clustering. Thewhole network is partitioned into a number of single-hopclusters. A cluster head (CH) is selected in each cluster toperform intra-cluster modal analysis using traditionalmodal identification algorithms. The collected data in eachcluster is then assembled together to obtain the modalparameters for the whole structure. Compared with thecentralized approach, the cluster based modal analysislimits the number of sensor nodes and hop count in eachcluster, thus can be more energy efficient and scalable.Compared with the distributed approach, classic modalparameter identification techniques which use data-levelfusion can be used in each cluster to obtain more reliableand accurate results. This cluster-based approach istherefore suitable for WSN-based SHM systems[8].

MSFCP: Maximum Subtree First Collection Protocol isdesigned for SHM which requires high throughput, bulkdata collection. MSFCP uses multichannel block transferand adopts Maximum Subtree First (MSF) scheduling toreduce interference and enhance overall throughput.MSFCP adopts MSF scheduling, which is unsynchronizeddistributed scheduling based on node's own transmissionbuffer information. The key idea is to scheduletransmission in parallel along multiple branches of the tree,and to keep the sink as busy receiving as possible. Thenodes are aware of the number of nodes in each subtree.The subtree of a node is defined as a tree that has the childof the node as its root. All source nodes wait for theirparent’s request if their buffer is full. The sink choosessubtrees whose roots have a full buffer, that is, subtreesother than the subtree whose root previously sent a blockto the sink. This strategy can keep the sink as busy aspossible and enhance the overall throughput[10].

IV. CONCLUSIONRecent years have seen growing interest in SHM based onwireless sensor networks (WSNs) due to their lowinstallation and maintenance expenses. WSNs permit adense deployment of measurement points on an existingstructure. But the centralized SHM system suffers fromlarge energy consumption and latencies. This papersurveyed various routing protocols which are dedicated toincrease the overall lifetime and accuracy of the system.The discussed protocols use multi-hop, compression,clustering and geographic adaptive techniques to increasethe 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, “WirelessSensor Networks for Structural Health Monitoring : Considerationsfor Communication Protocol Design,” IEEE InternationalConference on Telecommunications, pp. 694–699, 2010.


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[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 InformationTechnology, pp. 326–330, 2012.

[4] B. Wang, “MHop-CL : A Clustering Protocol for Bridge StructureHealth Monitoring System,” International Symposium on ComputerNetwork and Multimedia Technology, pp. 1–4, 2009.

[5] Weidong Zhang, Jun Wan, Bin Yang, Xiwen Zhang, “AnEnergy Efficient Routing Protocol in Wireless SensorNetwork for Health Monitoring,” IEEE Symposium on

Electrical & Electronics Engineering, pp. 247–250,2012.

[6] S.Prabu, R. Maheswari., “Improving Wireless Sensor NetworkLifespan By Efficient Routing Algorithm And LZWCompression,” ICICES, pp. 0–4, 2014.

[7] P. Nie and B. Li, “A cluster-based data aggregation architecturein 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, “Energyefficient clustering for WSN-based structural healthmonitoring,” INFOCOM, Proceedings of IEEE pp.2768–2776, 2011.

[9] T. Kuroiwa, M. Suzuki, Y. Yamashita, S. Saruwatari, T.Nagayama, H. Morikawa, “A multichannel bulk data

collection for structural health monitoring usingwireless sensor networks,”APCC, pp. 295–299,

2012.