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This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 1

Energy-Efcient Wireless MAC Protocols for Railway Monitoring ApplicationsG. M. Shaullah, Member, IEEE, Salahuddin A. Azad, and A. B. M. Shawkat Ali, Senior Member, IEEEAbstractRecent advances in wireless sensor networking (WSN) techniques have encouraged interest in the development of vehicle health monitoring (VHM) systems. These have the potential for use in the monitoring of railway signaling systems and rail tracks. Energy efciency is one of the most important design factors for the WSNs as the typical sensor nodes are equipped with limited power batteries. In earlier research, an energy-efcient cluster-based adaptive time-division multipleaccess (TDMA) medium-access-control (MAC) protocol, named EA-TDMA, has been developed by the authors for the purpose of communication between the sensors placed in a railway wagon. This paper proposes another new protocol, named E-BMA, which achieves even better energy efciency for low and medium trafc by minimizing the idle time during the contention period. In addition to railway applications, the EA-TDMA and E-BMA protocols are suitable for generic wireless data communication purposes. Both analytical and simulation results for the energy consumption of TDMA, EA-TDMA, BMA, and E-BMA have been presented in this paper to demonstrate the superiority of the EA-TDMA and E-BMA protocols. Index TermsEnergy efciency, medium access control (MAC) protocol, railway wagon, vehicle health monitoring (VHM), wireless sensor network (WSN).

Fig. 1. Typical scenario for railway-wagon health monitoring system.

I. I NTRODUCTION ITH the increased demand for railway services, railway monitoring systems continue to advance at a remarkable pace to maintain reliable, safe, and secure operation. The lack of safety and security monitoring of railway infrastructure runs the risk of train collision, train derailment, terrorist threats, failures in the train wagons, etc. The performance of rail vehicles running on tracks is limited by the lateral instability inherent to the design of the wagons steering and the response of the railway wagon to individual or combined track irregularities. Railway track irregularities need to be kept within safe operating margins by undertaking appropriate maintenance programs. Track geometry inspection and monitoring enhances train-operating safety and reduced vehicle and track dynamic interaction. MonManuscript received March 15, 2012; revised August 15, 2012 and October 15, 2012; accepted October 20, 2012. This work was supported in part by Prof. P. Wolfs and in part by Prof. C. Cole, both from the Center for Railway Engineering, Central Queensland University. The Associate Editor for this paper was B. Ning. G. M. Shaullah and S. A. Azad are with the Power Engineering Research Group, School of Engineering and Built Environment, Central Queensland University, Rockhampton, Qld. 4702, Australia (e-mail: g.shaullah@cqu.edu.au; s.azad@cqu.edu.au). A. B. M. S. Ali is with the School of Information and Communication Technology, Central Queensland University, Rockhampton, Qld. 4702, Australia (e-mail: s.ali@cqu.edu.au). Color versions of one or more of the gures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identier 10.1109/TITS.2012.2227315

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itoring vehicle characteristics in real time from track measurement data has been addressed by various research organizations [2][7]. Wireless sensor networks (WSNs) are widely used to monitor railway tracks and irregularities, detect abandoned objects in railway stations, develop intrusion detection systems, secure railway operations, and monitor tunnels [8][10]. Seifert envisioned [8] that a network of smart sensors could be utilized to monitor public spaces for potential invasion to alert the operators at a control center about the event. In addition, a WSN can be deployed to monitor large areas with greater efcacy in video-based intrusion detection systems. Aboelela et al. [9] proposed a new approach to reduce the accident rate and increase the efciency of railroad maintenance activities. The protocol adopts a multilayered multipath routing architecture in which each sensor transmits the sensed data to the two nearest cluster heads (CHs). Each CH aggregates the data using a fuzzy logic technique and transfers it to the sink node. Cheekiralla [10] designed a wireless sensor unit for the surveillance of a train tunnel, which measures the vertical displacements along the critical zone of the tunnel during adjacent construction activity. The potential of WSN technology to monitor the railwaywagon health condition and the vertical displacement of railway wagons due to track irregularities has yet to be fully explored. The limited lifetime of the batteries that power the sensor nodes makes the energy efciency a major design issue for WSNs [11]. This paper concentrates on developing an energy-efcient WSN MAC protocol to collect data from sensor nodes that are placed inside the railway wagons and send the data to the locomotive for further precautionary actions to prevent any future disastrous events. A prototype of the proposed railwaywagon health monitoring system is given in Fig. 1. Although the proposed energy-efcient protocol is designed with the railway applications in mind, it is applicable to generic wireless data communication purposes. Analytical and simulation models have been developed for the existing and proposed protocols to compare their performances in terms of energy consumption.

1524-9050/$31.00 2012 IEEE

This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination.2 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS

II. BACKGROUND OF THE S TUDY Central Queensland University, in collaboration with the Center for Railway Engineering [4], has been working on an autonomous health card device for online analysis of car body motion to perceive track condition and monitor derailment. The health card devices use an accelerometer and angular rate sensors with a coordinate transform to analyze the car body motions into six degrees of freedom [12], [13]. These health card devices inspect every wagon in the eet using low-cost smart devices [4], [12]. An algorithm was developed, which analyzes signals coming from accelerometers mounted on the wagon body to measure the dynamic interaction between the track and the rail vehicle. The algorithm was validated using collected eld data, e.g., accelerations measured at strategic points on the wagon body and the bogies. Each prototype health card incorporates a 27-MHz microcontroller with 256 kB of onboard RAM, four dual-axis accelerometers, a Global Positioning Satellite receiver, two low-power radios, lithium-ion batteries, and a solar panel. A Rabbit 3000 processor is used, which requires 200 mW of power at 40 MHz. The rst generation of the health card consumes a total of 400 mW or energy requirement of 9.6 Wh daily. An 80-Wh lithium battery is built into the health card that can provide energy for up to eight days. Data were collected from a ballast wagon in which dual-axis accelerometers were tted to each corner of the body and each side frame. A personalcomputer-based data acquisition system was used to store data. The main purpose of the data acquisition was to provide real data that are represented to the health card device. Data have been used to validate and demonstrate the effectiveness of signal analysis techniques and, nally, to develop a model to monitor typical dynamic behavior and track irregularities [12], [13]. Both the vertical and lateral conditions of the railway wagon have been measured by each accelerometer. The aim of the sensing arrangement was to capture roll, pitch, yaw, vertical, and lateral accelerations of the wagon body. The ADXL202/ADXL210 [14] dual-axis low-power low-cost acceleration sensor measured 16 channel acceleration data in g units, with eight channels for the wagon body and eight for the wagon side frame. Four sensor nodes were placed in each wagon body, and the locations of the sensors were front-left body, front-right body, rear-left body, and rear-right body. Similarly, four sensor nodes were placed in each wagons side fame [4]. Sensor locations and naming convention are illustrated in Fig. 2. The sampling rate of the accelerometer can be set from 0.01 Hz to 5 KHz through adjustable capacitors, and the clock speed of this health card device was set to 100 Hz. Data were continuously collected from a ballast wagon, which was a conventional three-piece bogie spaced lb = 10.97 m apart. The accelerometers were spaced l = 14.4 m apart. The test run was a normal ballast lying operation, starting with a full load of ballast, traveling to the maintenance site, dropping the ballast on the track, and returning empty via the same route. This research work is an extension of the existing health card system development endeavor, aiming at improving the energy efciency of the railway-wagon health monitoring system. In the proposed system, there are ve sensor nodes placed inside

Fig. 2.

Accelerometer locations and axis naming convention [4].

each wagon, instead of four in the existing system. One sensor node is used as a CH that collects data from other nodes and sends data to the central control room or base station (BS). In this system, an accelerometer has been placed in each corner of the wagon and one accelerometer at the center of the wagon, which acts as a CH. The BS is placed in the middle of the train for optimal signal transmission range. If there are W wagons in the train, then the BS is positioned between wagons W/2 and W/2 + 1. This fea

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