Elsevier

Computer Networks

Volume 52, Issue 12, 22 August 2008, Pages 2292-2330
Computer Networks

Wireless sensor network survey

https://doi.org/10.1016/j.comnet.2008.04.002Get rights and content

Abstract

A wireless sensor network (WSN) has important applications such as remote environmental monitoring and target tracking. This has been enabled by the availability, particularly in recent years, of sensors that are smaller, cheaper, and intelligent. These sensors are equipped with wireless interfaces with which they can communicate with one another to form a network. The design of a WSN depends significantly on the application, and it must consider factors such as the environment, the application’s design objectives, cost, hardware, and system constraints. The goal of our survey is to present a comprehensive review of the recent literature since the publication of [I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, A survey on sensor networks, IEEE Communications Magazine, 2002]. Following a top-down approach, we give an overview of several new applications and then review the literature on various aspects of WSNs. We classify the problems into three different categories: (1) internal platform and underlying operating system, (2) communication protocol stack, and (3) network services, provisioning, and deployment. We review the major development in these three categories and outline new challenges.

Introduction

Wireless sensor networks (WSNs) have gained worldwide attention in recent years, particularly with the proliferation in Micro-Electro-Mechanical Systems (MEMS) technology which has facilitated the development of smart sensors. These sensors are small, with limited processing and computing resources, and they are inexpensive compared to traditional sensors. These sensor nodes can sense, measure, and gather information from the environment and, based on some local decision process, they can transmit the sensed data to the user.

Smart sensor nodes are low power devices equipped with one or more sensors, a processor, memory, a power supply, a radio, and an actuator.1 A variety of mechanical, thermal, biological, chemical, optical, and magnetic sensors may be attached to the sensor node to measure properties of the environment. Since the sensor nodes have limited memory and are typically deployed in difficult-to-access locations, a radio is implemented for wireless communication to transfer the data to a base station (e.g., a laptop, a personal handheld device, or an access point to a fixed infrastructure). Battery is the main power source in a sensor node. Secondary power supply that harvests power from the environment such as solar panels may be added to the node depending on the appropriateness of the environment where the sensor will be deployed. Depending on the application and the type of sensors used, actuators may be incorporated in the sensors.

A WSN typically has little or no infrastructure. It consists of a number of sensor nodes (few tens to thousands) working together to monitor a region to obtain data about the environment. There are two types of WSNs: structured and unstructured. An unstructured WSN is one that contains a dense collection of sensor nodes. Sensor nodes may be deployed in an ad hoc manner2 into the field. Once deployed, the network is left unattended to perform monitoring and reporting functions. In an unstructured WSN, network maintenance such as managing connectivity and detecting failures is difficult since there are so many nodes. In a structured WSN, all or some of the sensor nodes are deployed in a pre-planned manner.3 The advantage of a structured network is that fewer nodes can be deployed with lower network maintenance and management cost. Fewer nodes can be deployed now since nodes are placed at specific locations to provide coverage while ad hoc deployment can have uncovered regions.

WSNs have great potential for many applications in scenarios such as military target tracking and surveillance [2], [3], natural disaster relief [4], biomedical health monitoring [5], [6], and hazardous environment exploration and seismic sensing [7]. In military target tracking and surveillance, a WSN can assist in intrusion detection and identification. Specific examples include spatially-correlated and coordinated troop and tank movements. With natural disasters, sensor nodes can sense and detect the environment to forecast disasters before they occur. In biomedical applications, surgical implants of sensors can help monitor a patient’s health. For seismic sensing, ad hoc deployment of sensors along the volcanic area can detect the development of earthquakes and eruptions.

Unlike traditional networks, a WSN has its own design and resource constraints. Resource constraints include a limited amount of energy, short communication range, low bandwidth, and limited processing and storage in each node. Design constraints are application dependent and are based on the monitored environment. The environment plays a key role in determining the size of the network, the deployment scheme, and the network topology. The size of the network varies with the monitored environment. For indoor environments, fewer nodes are required to form a network in a limited space whereas outdoor environments may require more nodes to cover a larger area. An ad hoc deployment is preferred over pre-planned deployment when the environment is inaccessible by humans or when the network is composed of hundreds to thousands of nodes. Obstructions in the environment can also limit communication between nodes, which in turn affects the network connectivity (or topology).

Research in WSNs aims to meet the above constraints by introducing new design concepts, creating or improving existing protocols, building new applications, and developing new algorithms. In this study, we present a top-down approach to survey different protocols and algorithms proposed in recent years. Our work differs from other surveys as follows:

  • While our survey is similar to [1], our focus has been to survey the more recent literature.

  • We address the issues in a WSN both at the individual sensor node level as well as a group level.

  • We survey the current provisioning, management and control issues in WSNs. These include issues such as localization, coverage, synchronization, network security, and data aggregation and compression.

  • We compare and contrast the various types of wireless sensor networks.

  • Finally, we provide a summary of the current sensor technologies.

The remainder of this paper is organized as follows: Section 2 gives an overview of the key issues in a WSN. Section 3 compares the different types of sensor networks. Section 4 discusses several applications of WSNs. Section 5 presents issues in operating system support, supporting standards, storage, and physical testbed. Section 6 summarizes the control and management issues. Section 7 classifies and compares the proposed physical layer, data-link layer, network layer, and transport layer protocols. Section 8 concludes this paper. Appendix A compares the existing types of WSNs. Appendix B summarizes the sensor technologies. Appendix C compares sensor applications with the protocol stack.

Section snippets

Overview of key issues

Current state-of-the-art sensor technology provides a solution to design and develop many types of wireless sensor applications. A summary of existing sensor technologies is provided in Appendix A. Available sensors in the market include generic (multi-purpose) nodes and gateway (bridge) nodes. A generic (multi-purpose) sensor node’s task is to take measurements from the monitored environment. It may be equipped with a variety of devices which can measure various physical attributes such as

Types of sensor networks

Current WSNs are deployed on land, underground, and underwater. Depending on the environment, a sensor network faces different challenges and constraints. There are five types of WSNs: terrestrial WSN, underground WSN, underwater WSN, multi-media WSN, and mobile WSN (see Appendix B).

Terrestrial WSNs [1] typically consist of hundreds to thousands of inexpensive wireless sensor nodes deployed in a given area, either in an ad hoc or in a pre-planned manner. In ad hoc deployment, sensor nodes can

Applications

WSN applications can be classified into two categories: monitoring and tracking (see Fig. 2). Monitoring applications include indoor/outdoor environmental monitoring, health and wellness monitoring, power monitoring, inventory location monitoring, factory and process automation, and seismic and structural monitoring. Tracking applications include tracking objects, animals, humans, and vehicles. While there are many different applications, below we describe a few example applications that have

Internal sensor system

For a sensor to operate in a wireless sensor network, there are several internal system issues that need to be addressed through the system platform and operating system (OS) support. In addition, supporting standards, storage, and physical testbeds are reviewed in the following subsections.

Network services

Sensor provisioning, management, and control services are developed to coordinate and manage sensor nodes. They enhance the overall performance of the network in terms of power, task distribution, and resource usage. Provisioning properly allocates resources such as power and bandwidth to maximize utilization. In provisioning, there is coverage and localization. Coverage in a WSN needs to guarantee that the monitored region is completely covered with a high degree of reliability. Coverage is

Communication protocol

The development of a reliable and energy-efficient protocol stack is important for supporting various WSN applications. Depending on the application, a network may consist of hundreds to thousands of nodes. Each sensor node uses the protocol stack to communicate with one another and to the sink. Hence, the protocol stack must be energy efficient in terms of communication and be able to work efficiently across multiple sensor nodes. We review the various energy-efficient protocols proposed for

Conclusion

Unlike other networks, WSNs are designed for specific applications. Applications include, but are not limited to, environmental monitoring, industrial machine monitoring, surveillance systems, and military target tracking (see Fig. 2). Each application differs in features and requirements. To support this diversity of applications, the development of new communication protocols, algorithms, designs, and services are needed.

We have surveyed in this paper issues on three different categories: (1)

Acknowledgement

We gratefully acknowledge the helpful comments from the reviewers, which have improved the paper very significantly.

Jennifer Yick received the BS Degree in Computer Science and Engineering from the University of California, Davis, in 2001, and the MS Degree in Computer Science from the University of California, Davis, in 2004. She is currently a PhD candidate in the Department of Computer Science at University of California, Davis. Her current research interests include energy conservation, localization, clustering, target tracking and network survivability in wireless sensor networks.

References (123)

  • I.F. Akyildiz et al.

    Wireless underground sensor networks: research challenges

    Ad-Hoc Networks

    (2006)
  • I.F. Akyildiz et al.

    A survey on wireless multimedia sensor networks

    Computer Networks Elsevier

    (2007)
  • B. Sundararaman et al.

    Clock synchronization for wireless sensor network: a survey

    Ad-Hoc Networks

    (2005)
  • I.F. Akyildiz et al.

    A survey on sensor networks

    IEEE Communications Magazine

    (2002)
  • G. Simon, M. Maroti, A. Ledeczi, G. Balogh, B. Kusy, A. Nadas, G. Pap, J. Sallai, K. Frampton, Sensor network-based...
  • J. Yick, B. Mukherjee, D. Ghosal, Analysis of a Prediction-based Mobility Adaptive Tracking Algorithm, in: Proceedings...
  • M. Castillo-Effen, D.H. Quintela, R. Jordan, W. Westhoff, W. Moreno, Wireless sensor networks for flash-flood alerting,...
  • T. Gao, D. Greenspan, M. Welsh, R.R. Juang, A. Alm, Vital signs monitoring and patient tracking over a wireless...
  • K. Lorincz, D. Malan, T.R.F. Fulford-Jones, A. Nawoj, A. Clavel, V. Shnayder, G. Mainland, M. Welsh, S. Moulton, Sensor...
  • G. Wener-Allen, K. Lorincz, M. Ruiz, O. Marcillo, J. Johnson, J. Lees, M. Walsh, Deploying a wireless sensor network on...
  • V. Raghunathan, A. Kansai, J. Hse, J. Friedman, M. Srivastava, Design considerations for solar energy harvesting...
  • P. Zhang, C.M. Sadler, S.A. Lyon, M. Martonosi, Hardware design experiences in ZebraNet, in: Proceedings of the...
  • S. Roundy et al.

    Energy Scavenging for Wireless Sensor Networks

    (2004)
  • M. Rahimi, H. Shah, G.S. Sukhatme, J. Heideman, D. Estrin, Studying the feasibility of energy harvesting in mobile...
  • A. Kansai, M.B. Srivastava, An environmental energy harvesting framework for sensor networks, in: Proceedings of the...
  • S. Toumpis et al.

    Optimal deployment of large wireless sensor networks

    IEEE Transactions on Information Theory

    (2006)
  • J. Yick et al.

    Placement of network services in sensor networks

    Self-Organization Routing and Information, Integration in Wireless Sensor Networks (Special Issue) in International Journal of Wireless and Mobile Computing (IJWMC)

    (2006)
  • D. Pompili, T. Melodia, I.F. Akyildiz, Deployment analysis in underwater acoustic wireless sensor networks, in: WUWNet,...
  • M. Li, Y. Liu, Underground structure monitoring with wireless sensor networks, in: Proceedings of the IPSN, Cambridge,...
  • I.F. Akyildiz et al.

    Challenges for efficient communication in underwater acoustic sensor networks

    ACM Sigbed Review

    (2004)
  • J. Heidemann, Y. Li, A. Syed, J. Wills, W. Ye, Underwater sensor networking: research challenges and potential...
  • D. Gay, P. Levis, R.v. Behren, The nesC language: a holistic approach to networked embedded systems, in: Proceedings of...
  • G. Tolle, J. Polastre, R. Szewczyk, D. Culler, N. Turner, K. Tu, S. Burgess, T. Dawson, P. Buonadonna, D. Gay, W. Hong,...
  • L. Krishnamurthy, R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, N. Kushalmager, L. Nachman, M. Yarvis, Design and...
  • I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin, P. Corke, Data collection, storage, retrieval with an underwater sensor...
  • K.K. Yap, V. Srinivasan, M. Motani, MAX: Human-centric search of the physical world, in: Proceedings of the Third...
  • J.H. Huang, S. Amjad, S. Mishra, CenWits: A sensor-based loosely coupled search and rescue system using witnesses, in:...
  • M. Rahimi, R. Baer, O.I. Iroezi, J.C. Garcia, J. Warrior, D. Estrin, M. Srivastava, Cyclops: in situ image sensing and...
  • I. Johnstone, J. Nicholson, B. Shehazad, J. Slipp, Experiences from a wireless sensor network deployment in a petroleum...
  • Moteiv,...
  • SOHOware Inc.,...
  • Technologic Systems,...
  • G. Werner-Allen et al.

    Deploying a wireless sensor network on an active volcano

    IEEE Internet Computing

    (2006)
  • C.R. Baker, K. Armijo, S. Belka, M. Benhabib, V. Bhargava, N. Burkhart, A.D. Minassians, G. Dervisoglu, L. Gutnik, M.B....
  • M. Leopold, M.B. Dydensborg, P. Bonnet, Bluetooth and sensor networks: a reality check, in: Proceedings of the...
  • L. Gu, D. Jia, P. Vicaire, T. Yan, L. Luo, A. Tirumala, Q. Cao, T. he, J.A. Stankovic, T. Abdelzaher, B.H. Krogh,...
  • S.Y. Cheung, S.C. Ergen, P. Varaiya, Traffic surveillance with wireless magnetic sensors, in: Proceedings of the 12th...
  • I. Howitt et al.

    IEEE802.15.4 low rate-wireless personal area network coexistence issues

    Wireless Communications and Networking

    (2003)
  • ZigBee: wireless control that simply works,...
  • ZigBee Standards Overview,...
  • HART – The Logical Wireless Solution,...
  • Draft standard: What’s in the April’07 WirelessHART specification,...
  • ISA100.11a,...
  • 6LoWPAN,...
  • G. Mulligan, L.W. Group, The 6LoWPAN architecture, in: Proceedings of the EmNets, Cork, Ireland,...
  • G. Montenegro et al.

    Transmission of IPv6 packets over IEEE 802.15.4 networks

    RFC

    (2007)
  • IEEE Standard 802.15.3, Wireless medium access control (MAC) and physical layer (PHY) specifications for high rate...
  • Wibree,...
  • J. Newsome, D. Song, GEM: Graph EMbedding for routing and data-centric storage in sensor networks without geographic...
  • P. Desnoyers, D. Ganesan, P. Shenoy, TSAR: a two tier sensor storage architecture using interval skip graphs, in:...
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    Jennifer Yick received the BS Degree in Computer Science and Engineering from the University of California, Davis, in 2001, and the MS Degree in Computer Science from the University of California, Davis, in 2004. She is currently a PhD candidate in the Department of Computer Science at University of California, Davis. Her current research interests include energy conservation, localization, clustering, target tracking and network survivability in wireless sensor networks.

    Biswanath Mukherjee (S′82–M′87) received the BTech (Hons) Degree from Indian Institute of Technology, Kharagpur, India in 1980 and the PhD Degree from University of Washington, Seattle in June 1987. At Washington, he held a GTE Teaching Fellowship and a General Electric Foundation Fellowship. In July 1987, he joined the University of California, Davis, where he has been Professor of Computer Science since July 1995 (and currently holds the Child Family Endowed Chair Professorship), and served as Chairman of the Department of Computer Science during from September 1997 to June 2000. He is winner of the 2004 Distinguished Graduate Mentoring Award at UC Davis. Two PhD Dissertations (by Dr. Laxman Sahasrabuddhe and Dr. Keyao Zhu), which were supervised by Professor Mukherjee, were winners of the 2000 and 2004 UC Davis College of Engineering Distinguished Dissertation Awards. To date, he has graduated nearly 25 PhD students, with almost the same number of MS students. Currently, he supervises the research of nearly 20 scholars, mainly PhD students and including visiting research scientists in his laboratory. He is Co-winner of paper awards presented at the 1991 and the 1994 National Computer Security Conferences. He serves or has served on the editorial boards of the IEEE/ACM Transactions on Networking, IEEE Network, ACM/Baltzer Wireless Information Networks (WINET), Journal of High Speed Networks, Photonic Network Communications, Optical Network Magazine, and Optical Switching and Networking. He served as Editor-at-Large for optical Networking and Communications for the IEEE Communications Society; as the Technical Program Chair of the IEEE INFOCOM’96 conference; and as Chairman of the IEEE Communication Society’s Optical Networking Technical Committee (ONTC) during 2003–2005. He is Author of the textbook ‘Optical WDM Networks’ published by Springer in January 2006. Earlier, he Authored the textbook ‘Optical Communication Networks’ published by McGraw-Hill in 1997, a book which received the Association of American Publishers, Inc.’s 1997 Honorable Mention in Computer Science. He is a Member of the Board of Directors of IPLocks, Inc., a Silicon Valley startup company. He has consulted for and served on the Technical Advisory Board (TAB) of a number of startup companies in optical networking. His current TAB appointments include: Teknovus, Intelligent Fiber Optic Systems, and LookAhead Decisions, Inc. (LDI). His research interests include lightwave networks, network security, and wireless networks.

    Dipak Ghosal received the BTech Degree in Electrical Engineering from Indian Institute of Technology, Kanpur (India), in 1983, and MS Degree in Computer Science and Automation from Indian Institute of Science, Bangalore, India, in 1985. He received his PhD Degree in Computer Science from University of Louisiana, in 1988. He is currently a Professor in the Department of Computer Science at the University of California, Davis. His primary research interests are in the areas of high speed and wireless networks with particular emphasis on the impact of new technologies on the network and higher layer protocols and applications. He is also interested in the application of parallel architectures for protocol processing in high speed networks and in the application of distributed computing principles in the design of next generation network architectures and server technologies.

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