MISE-PIPE: Magnetic induction-based wireless sensor networks for underground pipeline monitoring
Introduction
Nowadays, millions of kilometers of pipelines are deployed all over the world to transport vast volumes of fresh water, fuels, crude oil and natural gas. In mid-east countries, those pipelines are even regarded as the lifelines of the national economy. Among all the pipelines used for oil or water transportation, pipeline structures, which are buried underground, are generally preferred due to their advantages in terms of safety and concealment. For example, the water supply of Riyadh City, the capital of Saudi Arabia, depends on hundreds of kilometers of underground pipelines that connect the city with the Arabian Gulf and remote water wells through the desert [23], [42]. Moreover, during 2007, Russia exported almost 1.3 million barrels of crude oil per day via pipelines (most are underground pipelines) to Belarus, Ukraine, Germany, Poland, and other destinations in Central and Eastern Europe [44].
Although the underground pipelines constitute the safest way to transport large amounts of fluid through long distances, the pipelines are exposed to multiple hostile environmental factors, such as extreme soil conditions, corrosion, and human malicious attacks, which may cause leakage on the pipelines. According to statistical analysis, the large pipelines will experience at least one obvious leakage every year [15]. Pipeline leakages may lead to large economic loss, combined with environmental pollution, or risk of personnel injuries. Thus, the security and maintenance of the pipeline infrastructure is one of the major concerns [26].
Traditional pipeline leakage detection methods depend on the periodical inspection conducted by the maintenance personnel [10], [43], which requires intensive human involvement. Moreover, the periodical inspection does not provide real-time monitoring of the pipelines. Consequently, a leakage may not be detected in time and may cause much larger economic loss and environmental pollution. Real-time pipeline monitoring systems based on wired or wireless sensors have been developed in [8], [14], [31]. The wire-based techniques connect the sensors along the pipelines with wires. Measurements from each sensor are transmitted to the remote monitoring center through these wires. However, the wire-based monitoring systems suffer from damages within any part of the network and the deployment in underground settings is highly costly. Wireless sensor networks [2], on the other hand, are much more robust and efficient to monitor the aboveground pipelines. However, terrestrial wireless sensor networks cannot be used to monitor the underground pipelines, since the traditional electromagnetic (EM) wave-based signal propagation techniques encounter problems of high path loss and dynamic channel condition in the underground environments [3], [4], [20], [27], [28], [29], [35], [39]. To the best of our knowledge, a robust and efficient solution for underground pipeline monitoring has yet to be realized.
In this paper, we introduce MISE-PIPE: Magnetic induction (MI)-based wireless sensor network for underground pipeline monitoring, which provides a low-cost solution for effective real-time leakage detection and localization of underground pipelines. MISE-PIPE consists of two types of sensors based on their deployment, i.e. inside or outside the pipeline.
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Sensors, which are inside the pipelines, measure the pressure and the velocity of the oil/water flow, as well as the acoustic vibrations caused by the leakages. Since the inside sensors are deployed at the checkpoints or pump stations of the pipelines, they are resource-rich, high-power devices with higher processing capabilities. Therefore, the inside sensors also act as local processing hubs of MISE-PIPE.
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Sensors, which are outside the pipelines, measure the temperature, humidity, and properties of the soil around the underground pipelines. The outside sensors are densely buried underground along the pipelines hence can provide high granularity for leakage detection and localization.
The inside and the outside sensors have different detection/localization accuracy, system lifetime, and cost, while their measurements are complementary to each other. By coordinating these two types of sensors, MISE-PIPE provides both accurate real-time leakage detection/localization results and long system operation lifetime with low-cost for underground pipelines.
The measurements taken by the outside sensors along the pipelines are transmitted wirelessly using the MI waveguide technique to closeby processing hubs for in-network processing. Then the detection and localization results are transmitted through aboveground wireless communication techniques (such as sittlight communications) to a remote administrator center. The MI waveguide technique provides efficient and reliable communication in underground environments [32], [33]. Since the MI channel is not affected by the properties of the soil medium, the channel conditions remain constant for MISE-PIPE. Moreover, by tuning the relay coils of the MI waveguide, the MI waveguide system achieves very low path loss in soil medium in long term operation. The details of the MI waveguide system are introduced in Section 4.
In the following, the system architecture and operational framework of MISE-PIPE is described. Based on the architecture and framework, the research challenges and open research issues are discussed. In particular, the remainder of this paper is organized as follows: The existing pipeline leakage detection techniques are summarized in Section 2. The system architecture and operational framework for the MISE-PIPE system are presented in Section 3. Then, in Section 4, the signal propagation techniques based on MI waveguide and corresponding deployment strategies are described. The research challenges are discussed in Section 5. Finally, the paper is concluded in Section 6.
Section snippets
Existing pipeline monitoring techniques
Existing pipeline monitoring techniques can be divided into two categories based on the positions of the sensors, i.e., inside or outside the pipeline.
System architecture and operational framework for MISE-PIPE
As discussed in Section 2, current leakage detection techniques have different detection accuracies, applicable environments, and costs. However, none of these techniques, alone, can provide accurate detection/localization and system longevity with low-cost for underground pipelines. Moreover, transmitting measurements from underground sensors to remote administration centers in a reliable and efficient way is still an open research issue. As introduced in Section 1, MISE-PIPE utilize sensors
Magnetic Induction-Based Underground Communication for MISE-PIPE
According to the system architecture and operational framework described in Section 3, the functionality of the MISE-PIPE highly depends on two types of wireless communication needs: the communication between soil property sensors and the processing hubs, and the communication between the processing hubs and the remote administration center. The communication between the processing hubs and the remote administration center can be established through existing wireless communication techniques,
Research challenges
Based on the system architecture and operational framework of MISE-PIPE, the following research thrusts need to be investigated.
Conclusion
In this paper, we introduce a magnetic induction-based wireless sensor network architecture for underground pipeline monitoring (MISE-PIPE) for detecting and localizing leakages in underground pipelines. MISE-PIPE utilize sensors both inside and outside the pipelines, including the pressure sensors, the acoustic sensors, and soil property sensors. Those sensors cooperatively detect and localize the leakage on the underground pipelines. The new magnetic induction technique is utilized to provide
Zhi Sun received the B.S. degree in communication engineering from Beijing University of Posts and Telecommunications (BUPT), and the M.S. degree in electronic engineering from Tsinghua University, Beijing, China in 2004 and 2007, respectively. Currently, he is a graduate research assistant in Broadband Wireless Networking Laboratory (BWN Lab), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA. He is pursuing Ph.D. degree under the supervision of Prof.
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Zhi Sun received the B.S. degree in communication engineering from Beijing University of Posts and Telecommunications (BUPT), and the M.S. degree in electronic engineering from Tsinghua University, Beijing, China in 2004 and 2007, respectively. Currently, he is a graduate research assistant in Broadband Wireless Networking Laboratory (BWN Lab), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA. He is pursuing Ph.D. degree under the supervision of Prof. Ian F. Akyildiz. His current research interests are in wireless underground networks, mobile ad-hoc networks, and wireless sensor networks. He received the Best Paper Award in IEEE GLOBECOM 2010.
Pu Wang received the B.S. degree in electrical engineering from the Beijing Institute of Technology, Beijing, China, in 2003 and the M.Eng. degree in computer engineering from the Memorial University of Newfoundland, St. John’s, NL, Canada, in 2008. Currently, he is a graduate research assistant in Broadband Wireless Networking Laboratory (BWN Lab), School of Electrical and Computer Engineering, Georgia Institute of Technology. He is currently working toward the Ph.D. degree in electrical engineering under the supervision of Prof. Ian F. Akyildiz. His research interests include wireless sensor networks and mobile ad-hoc networks, with emphasis on traffic modeling, node clustering, data aggregation, and network coding.
Mehmet C. Vuran received his B.Sc. degree in electrical and electronics engineering from Bilkent University, Ankara, Turkey, in 2002. He received his M.S. and Ph.D. degrees in electrical and computer engineering from Broadband Wireless Networking Laboratory, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, under the supervision of Prof. Ian F. Akyildiz in 2004 and 2007, respectively.
Currently, he is an Assistant Professor in the Department of Computer Science and Engineering at the University of Nebraska-Lincoln and director of Cyber-Physical Networking Laboratory. Dr. Vuran received the NSF CAREER award in 2010. He has received numerous academic honors, including the 2010 Maude Hammond Fling Faculty Interdisciplinary Research Fellowship from the UNL Research Council and the 2007 ECE Graduate Research Assistant Excellence Award from Georgia Tech’s School of Electrical and Computer Engineering. He is an associate editor of Computer Networks Journal and Journal of Sensors. He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and the IEEE Communication Society. His current research interests include cross-layer design and analysis, wireless sensor networks, underground sensor networks, cognitive radio networks, and deep space communication networks.
Mznah Al-Rodhaan has received BS in Computer Applications (Hon) and MS in Computer Science both from King Saud University, in 1999 and 2003 respectively. In 2009, she received her Ph.D. in Computer Science from the University of Glasgow in Scotland. She is currently working as Assistant Professor in the College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. Moreover, she has participated in several international conferences and chaired some technical sessions. She is currently on the editorial board of the Ad Hoc Networks Journal (Elsevier). Her current research interest includes: Mobile Ad Hoc Networks, Wireless Sensor Networks, Cognitive Networks, Network Security, and High Performance Computing. The photo of the author is not available.
Abdullah M. Al-Dhelaan has received B.S. in Statistics (Hon) from King Saud University, in 1982, and the MS and Ph.D. in Computer Science from Oregon State University on 1986 and 1989 respectively. He is currently Associate Professor of Computer Science, Chairman of the join Ph.D. program, and Director General for the Center for International Collaboration and Visiting Professors, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia. He has guest edited several special issues for the Telecommunication Journal (Springer) , and the International Journal for Computers and their applications. Moreover, he is currently on the editorial boards for several journals such and Computer Network (Elsevier) and The International Journal of Computers and their applications. His current research interest includes: Mobile Ad Hoc Networks, Sensor Networks, Cognitive Networks, Network Security, and High Performance Computing.
Ian F. Akyildiz received the B.S., M.S., and Ph.D. degrees in Computer Engineering from the University of Erlangen-Nurnberg, Germany, in 1978, 1981 and 1984, respectively. Currently, he is the Ken Byers Distinguished Chair Professor with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, the Director of Broadband Wireless Networking Laboratory and Chair of the Telecommunication Group at Georgia Tech. His current research interests are in nanonetworks, cognitive radio networks and wireless sensor networks.
He is an Honorary Professor with the School of Electrical Engineering at Universitat Politecnica de Catalunya (UPC), Barcelona, Spain, since June 2008. Since March 2009, he is an Honorary Professor with the Department of Electrical, Electronic and Computer Engineering at the University of Pretoria, South Africa. He is also a Visiting Professor at the King Saud University in Riyadh, Saudi Arabia, since January 2010.
He is the Editor-in-Chief of Computer Networks (Elsevier) Journal, and the founding Editor-in-Chief of the Ad Hoc Networks (Elsevier) Journal, the Physical Communication (Elsevier) Journal and the Nano Communication Networks (Elsevier) Journal. Dr. Akyildiz serves on the advisory boards of several research centers, journals, conferences and publication companies.
He is an IEEE FELLOW (1996) and an ACM FELLOW (1997). He has received numerous awards from IEEE and ACM. He received the “Don Federico Santa Maria Medal” for his services to the Universidad of Federico Santa Maria, in 1986. From 1989 to 1998, he served as a National Lecturer for ACM and received the ACM Outstanding Distinguished Lecturer Award in 1994. He received the 1997 IEEE Leonard G. Abraham Prize Award (IEEE Communications Society) for his paper entitled “Multimedia Group Synchronization Protocols for Integrated Services Architectures” published in the IEEE JOURNAL OF SELECTED AREAS IN COMMUNICATIONS (JSAC) in January 1996. He received the 2002 IEEE Harry M. Goode Memorial Award (IEEE Computer Society) with the citation “for significant and pioneering contributions to advanced architectures and protocols for wireless and satellite networking.” He received the 2003 IEEE Best Tutorial Award (IEEE Communication Society) for his paper entitled “A Survey on Sensor Networks,” published in IEEE COMMUNICATIONS MAGAZINE, in August 2002. He received the 2003 ACM Sigmobile Outstanding Contribution Award with the citation “for pioneering contributions in the area of mobility and resource management for wireless communication networks”. In 2010, he received the IEEE Communications Society Ad Hoc and Sensor Networks Technical Committee (AHSN TC) Technical Recognition Award with the citation “for pioneering contributions to wireless sensor networks and wireless mesh networks.” He also supervised and co-authored papers that received the Best Paper Award in IEEE ICC 2009 and IEEE GLOBECOM 2010, respectively.
He received the 2004 Georgia Tech Faculty Research Author Award for his “outstanding record of publications of papers between 1999 and 2003”. He received the 2005 Distinguished Faculty Achievement Award from School of ECE, Georgia Tech. In 2009, he received the Georgia Tech Outstanding Doctoral Thesis Advisor Award for his 20+ years service and dedication to Georgia Tech and producing outstanding Ph.D. students. He also received the 2009 ECE Distinguished Mentor Award from the School of Electrical and Computer Engineering Faculty Honors Committee, Georgia Tech.