Sushanta Mohan Rakshit

CHALLENGES IN CURRENT WIRELESS SENSOR TECHNOLOGY FOR RAILCAR STATUS MONITORING FOR NORTH AMERICA'S FREIGHT RAILROAD INDUSTRY

Ensuring rail safety is a priority for the Federal Railroad Administration (FRA) and the railroad industry in North America. One such endeavor is to leverage Wireless Sensor Networks (WSN) to monitor and report in real-time the status of mechanical and electrical components for each railcar, and in conjunction with other railroad subsystems, ensure the safety, security and integrity of transported goods.The envisioned solution utilizes sensors installed on each railcar to form a train-based wireless network and collect real-time (or near real-time) information on different elements of a train and transmit aggregated information to the locomotive, dispatch centers or regional offices for early fault detection and accident prevention. The railroads have been interested in using a standards-based low-cost communication protocol for this purpose, such as IEEE 802.15.4, often referred to as ZigBee.Our results show, however, that ZigBee was designed for smaller wireless networks, such as a single railcar. It exhibits several critical problems associated with the unique network topology found on a freight train and the size of such a network. In essence, the network would take the shape of a very long chain of nodes. Some of the problems stemming from this topology are excessively long synchronization delays for establishing the network along the entire train, severe problems with route discovery and maintenance necessary for selecting the next relay node along the chain, aggregation of data errors and a resulting unacceptable packet loss rate, the lack of a traffic prioritization mechanism to protect important packets such as those containing critical alarms of equipment failure, and many more.In this paper, we describe our findings and experiences in our evaluation of ZigBee for railcar monitoring onboard freight trains, a detailed analysis of the identified problems and their impact on the envisioned railcar monitoring as well as discuss potential solutions to these problems.Copyright

Hybrid Technology Networking: A Novel Wireless Networking Approach for Real-Time Railcar Status Monitoring

The North American freight railroad industry continuously strives towards improvements in the safety and security of freight transportation. One key effort focuses on the use of Wireless Sensor Networks (WSN) technologies to monitor and report mechanical and electrical component status for each railcar in real-time, as well as the status of the transported goods themselves. This allows real-time monitoring of railcar components such as air pressure, wheel bearing temperature, brake failure, wiring integrity, refrigeration unit failure, boxcar door opening, the detection of radioactive materials, dangerous substance leaks, and much more. The aggregated sensor data is transmitted to the locomotive, dispatch centers or regional offices for early fault detection and accident prevention.Our previous work [1] has shown that ZigBee technology based on the IEEE 802.15.4 faces numerous obstacles when applied to freight railcar monitoring. To address these problems our team proposed an alternate approach called Hybrid Technology Networking (HTN), which combines the benefits of ZigBee for low-power short-range communication and WiFi for high-performance long-distance communication between HTN sensor clusters.In this paper, we present our simulation results using our HTN protocol. We compare and discuss the performance of the ZigBee-only network environment with the proposed HTN and demonstrate the advantages offered by HTN. We also discuss our prototype sensor hardware platform using the HTN protocol and provide an outlook of the future work planned for HTN.© 2012 ASME

Detecting covert timing channels using non-parametric statistical approaches

Extensive availability and development of Internet applications and services open up the opportunity for abusing network and Internet resources to distribute malicious data and leak sensitive information. One of the prevalent information-hiding approaches suitable for such activities is known as Covert Timing Channel (CTC), which utilizes the modulation of Inter-Packet Delays (IPDs) to embed secret data and transfers that to designated receivers. In this paper, we propose two different non-parametric statistical tests that can be employed to detect this type of covert communication activities over a network. The new detection metrics are evaluated and verified against four different and highly recognized CTC algorithms. The experimental results show that the proposed detection metrics can reliably and effectively distinguish between the covert and overt traffic flows, thus significantly supporting our research toward an accurate blind and comprehensive CTC detection. This is a capability vital to cyber security in todays information society.

Automated Covert Channel Modeling over a real network platform

In this paper we introduce a new approach for modeling covert channel algorithms utilizing automated code generation and evaluation in real network environments. Our proposed framework is called Automated Covert Channel Modeling over Networks (ACCM-Net), which allows the user to convert any general description of a covert channel algorithm into executable code using an automated process. The resulting code can be executed on virtual or physical hardware utilizing actual network links to evaluate the behavior of the covert channel algorithm and observe diverse characteristics and features of its covert communication. We have tested our proposed ACCM-Net framework with several well-known covert channel algorithms with positive results. Here, we present the implementation, and analysis of the widely adopted On/Off covert channel algorithm utilizing our proposed ACCM-Net. Based on our results, the implemented On/Off algorithm is functioning precisely and accurately.

Performance Evaluation of Hybrid Technology Networking for Real-Time Monitoring in Freight Railroad Operations

Traditional Wireless Sensor Network (WSN) solutions have been deemed insufficient to address the requirements of freight railroad companies to implement real-time monitoring and control of their trains, tracks and wayside equipment. With only ZigBee-based elements, the transmission capabilities of WSN devices are limited in terms of coverage range and throughput. This leads to severe delay and congestion in the network, particularly in railroad scenarios that usually require the nodes to be arranged in linear chain-like topology. In such a multi-hop topology to communicate from one end of a train to the locomotive — and due to ZigBee’s limited communication range — data needs to be transmitted using a very high number of hops and thus generates long delays and congestion problems.To overcome this drawback, we have proposed a heterogeneous multi-hop networking approach called “Hybrid Technology Networking” (HTN). In HTN we combined Wireless Local Area Network (WLAN) technologies like WiFi, which provide improved communication range and higher data rates, with low-power communication technologies like ZigBee. This significantly reduces the number of hops required to deliver data across the network and hence solves the issues of delay and congestion, while also achieving superior enery efficiency and network lifetime. The sensor nodes are logically divided into clusters and each cluster has a WiFi “gateway”. All intra-cluster communication is achieved via IEEE 802.15.4 and ZigBee protocols, while all inter-cluster communication utilizes WiFi protocol standards.To implement our proposed technology in railroad networks, we are designing hardware prototypes and simulation models to evaluate the functionality and performance of our HTN solution, which is designed around a dual network stack design governed by the HTN protocol. This ensures full compliance with IEEE and industry communication protocols for interoperability. Since no simulation tools that seamlessly combine both WSN and WLAN technologies in a single module exist, we wrote our own simulation environment using OPNET. In this paper, we have provided information of implementing the HTN protocol in OPNET and the simulation results for different scenarios relevant to railroad operations. These results will demonstrate the efficacy of our proposed system as well as provide the baseline data for testing the hardware devices in live networks. Under simulated traffic and channel conditions and device configurations, we observed a decrease of 77.27% in end-to-end delay and an increase of 69.70% in received data volume when using HTN compared to ZigBee-only multi-hop networks, simulated over 14 railcars in railroad-relevant scenarios.Copyright

Study of a dual radio sensor platform for effective on-board real-time monitoring of freight trains

The advent of the Internet of Things (IoT) has proliferated the use of connected sensors to observe and control the world around us. Wireless Sensor Networks (WSN) are becoming ubiquitous tools that monitor their surroundings and also oftentimes provide actuation to affect the state of their environment. One of the key application domains for real-time monitoring and control is the freight railroad sector in North America. North Americas freight railroad industry is responsible for transporting nearly 40% of goods, making it an inseparable aspect of national economic well-being. The current stationary wayside methodology of monitoring freight trains and the goods they transport is not effective and cannot provide the breadth of capabilities required to ensure safe and efficient operations. The use of otherwise popular existing communication technologies like ZigBee for this scenario were found to perform insufficiently due to the unique network topology imposed by the freight train. The Hybrid Technology Networking (HTN) protocol has been proposed to alleviate these issues. In this work a custom hardware platform is presented to optimally implement and deploy networks of sensors using the HTN protocol. A model for predicting network performance metrics using this platform along with performance test results are presented.

A novel Covert Timing Channel detection approach for online network traffic

In this paper, we propose a novel Covert Timing Channel (CTC) detection method that leverages computationally low-cost statistical measures to precisely detect covert communication, using only minimum network traffic knowledge. The proposed detection approach utilizes three different non-parametric statistical tests to classify overt and covert inter-packet delays.

Energy Analysis in Deploying Wireless Sensor Networks for On-Board Real-Time Railcar Status Monitoring

Wireless Sensor Networks have been a focus of research in the North American freight railroad industry to enable on-board real-time sensing of critical railcar parameters. Important railcar aspects like wheel bearing temperature, air pressure, brake failure, and the integrity of transported goods can then be monitored closely and reliably. This enables immediate preventive actions in case of impending failures and also enables trend analysis that can be used to fine-tune maintenance efforts on railcars. These measures increase the safety, efficiency, and dependability of freight railroad operations.In our previous work [1–3] we have presented our Hybrid Technology Networking (HTN) protocol. This protocol provides optimal network performance for railcar monitoring applications. We have also presented HTNMote, a hardware prototyping platform that implements HTN. A deployment of HTNMotes was conducted and evaluated at the TTCI facility in Pueblo, Colorado in the US. The results from our field tests confirm that this approach is an order of magnitude better in performance compared to solutions based on ZigBee alone.In such an application, energy considerations represent a key challenge. These sensors have no readily available continuous energy source, but are expected to operate for years in harsh conditions. Energy harvesting — from vibrations, temperature differences, or solar radiation — may provide a potential solution to the energy scarcity. This also mandates that the HTNMote hardware and HTN protocol both be as energy efficient as possible.In this paper we present detailed measurements of the energy consumed by the HTNMote in various operational situations that are encountered during their operation onboard freight railcars. We introduce an energy consumption model based on our analysis of the measurements. This model demonstrates the energy-efficiency of the HTNMote implementation.© 2015 ASME

Analysis of Energy Usage in Adaptive Sensor Networks

Currently, a rapidly increasing numbers of sensors are being used on vehicles and in surface transportation and this trend is expected to continue. In support of these sensor networks several energy management schemes, including hierarchical clustering methods, have been proposed in the literature to reduce energy usage. However, the operating conditions for wireless sensors in vehicular environments change continuously. Sensor networks must thus be able to adapt to the environment to maximize performance and reliability. In this paper, we discuss the necessity for splitting a cluster. In particular, we explore the changes in the energy usage profile when a cluster is split. Even though our algorithm is designed for specific applications relevant to automation and control of railroad operations we believe that our discussions on energy consumption is a universal issue relevant to any form of clustered networks in vehicular environments.

HTNMote: A Hardware Platform for Wireless Real-Time Railcar Monitoring and its Performance Analysis

Real-time monitoring of various components of a railcar such as wheel bearing temperature, brake line status, integrity of transported goods and many more has become a key focus area of research for the North American freight railroad industry. The ability for timely detection of abnormalities and impending failures prevents costly accidents, the potential loss of life and damage to the environment. Monitoring also increases overall operational efficiency, reliability and safety of freight railroads.Wireless Sensor Networks (WSN) are an obvious choice for implementing such a monitoring scheme. The accumulated data from various sensors distributed throughout each railcar along the length of the train is transmitted wirelessly using multi-hop transmissions to the locomotive for alerting and monitoring. From there, this information is also transmitted to dispatch centers for further analysis and recording. ZigBee technology based on the IEEE 802.15.4 standard is a popular choice among WSN communication protocols, owing to its low cost and low power requirements. ZigBee performance degrades severely in the long chain-like topology characteristic of the railroad application environment. This effectively disqualifies ZigBee as a candidate technology for such railcar monitoring deployments.To overcome these issues with ZigBee deployments for freight train monitoring we developed our Hybrid Technology Networking (HTN) approach [5–7]. HTN leverages both ZigBee and Wi-Fi communication to achieve reliable communication along an entire freight train. Railcar monitoring nodes are grouped into smaller clusters, within which we utilize ZigBee for its low-power operation and report to each cluster’s gateway node. The gateway nodes of all the clusters on a train communicate using Wi-Fi, to benefit from the high throughput and long communication range. This tiered architecture also results in a drastic reduction in overall hop count for end-to-end communication.In this paper we present HTNMote, a hardware platform that we are developing and employing for real-world evaluation of the HTN protocol. We also present results from our field tests of the HTNMotes at the Transportation Technology Center (TTCI) facility in Pueblo, Colorado, operated by the US Association of American Railroads (AAR). The results show that the use of HTN improves performance of the network by at least an order of magnitude compared to a ZigBee-only network. This paper details the design of our HTNMote platform, present the test setup and results, as well as conduct an in-depth analysis of the obtained results as they relate to railroad operations.© 2014 ASME