A Survey of Routing Protocols for Structural Health Monitoring

Page 1

Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

A Survey of Routing Protocols for Structural Health Monitoring 1

Kirandeep Kaur, 2Amol 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.



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.

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 III. ROUTING PROTOCOLS FOR SHM BASED WSNs tracking structural integrity and assessing the nature of Energy efficiency is a critical issue in WSNs. To minimize damage in a structure is often referred to as health energy consumption, most of the device components, monitoring. Ideally, health monitoring of civil including the radio, should be switched off most of the infrastructure consists of determining, by measured time. The main design goal of WSNs is not only to parameters, the location and severity of damage in transmit data from a source to a destination, but also to buildings or bridges as they happen[1]. increase the lifetime of the network. This can be achieved Wireless monitoring has emerged in recent years as a by employing energy efficient routing protocols[3]. The promising technology that could greatly impact the field of existing energy-efficient routing protocols often use structural monitoring. Sensing devices are becoming residual energy, transmission power, or link distance as smaller, less expensive, more robust, and highly precise, metrics to select an optimal path. In recent years a lot of allowing collection of high-fidelity data with dense attention is given for developing energy efficient and instrumentation employing multi-metric sensors. Wireless reliable routing protocols for WSNs dedicated to SHM. sensor networks (WSNs) leverage these advances to offer The use of these type of protocols can significantly the potential for dramatic improvements in the capability increase the network lifetime. Different routing protocols to capture structural dynamic behavior and evaluate the used for SHM are discussed in this paper. 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.

195

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 NITTTR, Chandigarh

EDIT-2015


Int. Journal of Electrical & Electronics Engg.

Vol. 2, Spl. Issue 1 (2015)

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. LempelZiv-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 ARARX 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 NITTTR, Chandigarh

EDIT -2015

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

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]

[2]

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. 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.

196


Int. Journal of Electrical & Electronics Engg. [3]

[4]

[5]

[6]

Vol. 2, Spl. Issue 1 (2015)

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. 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. 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. S.Prabu, R. Maheswari., “Improving Wireless Sensor Network Lifespan By Efficient Routing Algorithm And LZW Compression,” ICICES, pp. 0–4, 2014.

197

[7]

[8]

[9]

e-ISSN: 1694-2310 | p-ISSN: 1694-2426

P. Nie and B. Li, “A cluster-based data aggregation architecture in WSN for Structural Health Monitoring,” IWCMC, pp. 546–552, 2011. 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. T. Kuroiwa, M. Suzuki, Y. Yamashita, S. Saruwatari, T. Nagayama, H. Morikawa, “A multichannel bulk data collection for structural health monitoring using wireless sensor networks,”APCC, pp. 295–299, 2012.

NITTTR, Chandigarh

EDIT-2015


Turn static files into dynamic content formats.

Create a flipbook
Issuu converts static files into: digital portfolios, online yearbooks, online catalogs, digital photo albums and more. Sign up and create your flipbook.