A Survey of Access Control Models in Wireless Sensor Networks

Copyright 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/)Wireless sensor networks (WSNs) have attracted considerable interest in the research community, because of their wide range of applications. However, due to the distributed nature of WSNs and their deployment in remote areas, these networks are vulnerable to numerous security threats that can adversely affect their proper functioning. Resource constraints in sensor nodes mean that security mechanisms with a large overhead of computation and communication are impractical to use in WSNs; security in sensor networks is, therefore, a challenge. Access control is a critical security service that offers the appropriate access privileges to legitimate users and prevents illegitimate users from unauthorized access. However, access control has not received much attention in the context of WSNs. This paper provides an overview of security threats and attacks, outlines the security requirements and presents a state-of-the-art survey on access control models, including a comparison and evaluation based on their characteristics in WSNs. Potential challenging issues for access control schemes in WSNs are also discussed.Peer reviewe

Energy Consumption of Wireless Network Access Points

2nd International Conference on Green Communications and Networking, GreeNets 2012; Gandia; Spain; 25 October 2012 through 26 October 2012The development of low cost technology based on IEEE 802.11 standard permits to build telecommunication networks at low cost, allowing providing Internet access in rural areas in developing countries. The lack of access to the electrical grid is a problem when the network is being developed in rural areas, so that wireless access points should operate using solar panels and batteries. Many cases can be found where the energy consumption becomes a key point in wireless network design. In this paper we present a comparative study of the energy consumption of several wireless network access points. We will compare the energy consumption of different brands and models, for several operation scenarios and operating modes. Obtained results allow us to achieve the objective of this article, that is, promote the development of wireless communication networks energetically efficient.Andrade Morelli, S.; Ruiz Sanchez, E.; Granell Romero, E.; Lloret, J. (2013). Energy Consumption of Wireless Network Access Points. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST. 113:81-91. doi:10.1007/978-3-642-37977-2_8S8191113Khoa Nguyen, K., Jaumard, B.: Routing Engine Architecture for Next Generation Routers: Evolutional Trends. Network Protocols and Algorithms 1(1), 62–85 (2009)IEEE Std 802.11: IEEE Standard for Information technology -Telecommunications and information exchange between systems -Local and metropolitan area networks - Specific requirements – Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications. Institute of Electrical and Electronics Engineers, New York, USA, pp.1–1184 (2007)Lloret, J., Garcia, M., Bri, D., Sendra, S.: A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification. Sensors 9(11), 8722–8747 (2009)Tapia, A., Maitland, C., Stone, M.: Making IT work for Municipalities: Building municipal wireless networks. Government Information Quarterly 23(3), 359–380 (2006)van Drunen, R., Koolhaas, J., Schuurmans, H., Vijn, M.: Building a Wireless Community Network in the Netherland. In: USENIX 2003 / Freenix Annual Technical Conference Proceedings, San Antonio, Texas, USA, June 9-14, pp. 219–230 (2003)Powell, A., Shade, L.R.: Going Wi-Fi in Canada: Municipal and Community Initiatives. Canadian Research Alliance for Community Innovation and Networking (2005)Sendra, S., Fernández, P.A., Quilez, M.A., Lloret, J.: Study and Performance of Interior Gateway IP routing Protocols. Network Protocols and Algorithms 2(4), 88–117 (2010)Galperin, H.: Wireless Networks and Rural Development: Opportunities for Latin America. Information Technologies and International Development 2(3), 47–56 (2005)Segal, M.: Improving lifetime of wireless sensor networks. Network Protocols and Algorithms 1(2), 48–60 (2009)Momani, A.A.E., Yassein, M.B., Darwish, O., Manaseer, S., Mardini, W.: Intelligent Paging Backoff Algorithm for IEEE 802.11 MAC Protocol. Network Protocols and Algorithms 4(2), 108–123 (2012)Mohsin, A.H., Bakar, K.A., Adekiigbe, A., Ghafoor, K.Z.: A Survey of Energy-aware Routing protocols in Mobile Ad-hoc Networks: Trends and Challenges. Network Protocols and Algorithms 4(2), 82–107 (2012)Feeney, L.M., Nilsson, M.: Investigating the Energy Consumption of a Wireless Network Interface in an Ad Hoc Networking Environment. In: Proceedings of the Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2001, Anchorage, Alaska, April 22-26, vol. 3, pp. 1548–1557. IEEE (2001)Barbancho, J., León, C., Molina, F.J., Barbancho, A.: Using artificial intelligence in routing schemes for wireless networks. Computer Communications 30(14-15), 2802–2811 (2007)Tao, C., Yang, Y., Honggang, Z., Haesik, K., Horneman, K.: Network energy saving technologies for green wireless access networks. IEEE Wireless Communications 18(5), 30–38 (2011)Sendra, S., Lloret, J., Garcia, M., Toledo, J.F.: Power saving and energy optimization techniques for Wireless Sensor Networks. Journal of Communications 6(6), 439–459 (2011

Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks

[EN] In underwater acoustic modem design, pure asynchrony can contribute to improved wake-up coordination, thus avoiding energy-inefficient synchronization mechanisms. Nodes are designed with a pre-receptor and an acoustically adapted Radio Frequency Identification system, which wakes up the node when it receives an external tone. The facts that no synchronism protocol is necessary and that the time between waking up and packet reception is narrow make pure asynchronism highly efficient for energy saving. However, handshaking in the Medium Control Access layer must be adapted to maintain the premise of pure asynchronism. This paper explores different models to carry out this type of adaptation, comparing them via simulation in ns-3. Moreover, because energy saving is highly important to data gathering driven by underwater vehicles, where nodes can spend long periods without connection, this paper is focused on multi-hop topologies. When a vehicle appears in a 3D scenario, it is expected to gather as much information as possible in the minimum amount of time. Vehicle appearance is the event that triggers the gathering process, not only from the nearest nodes but from every node in the 3D volume. Therefore, this paper assumes, as a requirement, a topology of at least three hops. The results show that classic handshaking will perform better than tone reservation because hidden nodes annulate the positive effect of channel reservation. However, in highly dense networks, a combination model with polling will shorten the gathering time.Blanc Clavero, S. (2020). Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks. Sensors. 20(5):1-16. https://doi.org/10.3390/s20051407S116205Roy, A., & Sarma, N. (2018). Effects of Various Factors on Performance of MAC Protocols for Underwater Wireless Sensor Networks. Materials Today: Proceedings, 5(1), 2263-2274. doi:10.1016/j.matpr.2017.09.228Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges. Wireless Communications and Mobile Computing, 2019, 1-20. doi:10.1155/2019/6470359Rudnick, D. L., Davis, R. E., Eriksen, C. C., Fratantoni, D. M., & Perry, M. J. (2004). Underwater Gliders for Ocean Research. Marine Technology Society Journal, 38(2), 73-84. doi:10.4031/002533204787522703Petritoli, E., & Leccese, F. (2018). High Accuracy Attitude and Navigation System for an Autonomous Underwater Vehicle (AUV). ACTA IMEKO, 7(2), 3. doi:10.21014/acta_imeko.v7i2.535Nam, H. (2018). Data-Gathering Protocol-Based AUV Path-Planning for Long-Duration Cooperation in Underwater Acoustic Sensor Networks. IEEE Sensors Journal, 18(21), 8902-8912. doi:10.1109/jsen.2018.2866837Sun, J., Hu, F., Jin, W., Wang, J., Wang, X., Luo, Y., … Zhang, A. (2020). Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences. Sensors, 20(3), 893. doi:10.3390/s20030893Wahid, A., Lee, S., Kim, D., & Lim, K.-S. (2014). MRP: A Localization-Free Multi-Layered Routing Protocol for Underwater Wireless Sensor Networks. Wireless Personal Communications, 77(4), 2997-3012. doi:10.1007/s11277-014-1690-6Sánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2012). An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks. Sensors, 12(6), 6837-6856. doi:10.3390/s120606837Li, S., Qu, W., Liu, C., Qiu, T., & Zhao, Z. (2019). Survey on high reliability wireless communication for underwater sensor networks. Journal of Network and Computer Applications, 148, 102446. doi:10.1016/j.jnca.2019.102446Jiang, S. (2018). State-of-the-Art Medium Access Control (MAC) Protocols for Underwater Acoustic Networks: A Survey Based on a MAC Reference Model. IEEE Communications Surveys & Tutorials, 20(1), 96-131. doi:10.1109/comst.2017.2768802Chirdchoo, N., Soh, W., & Chua, K. C. (2008). RIPT: A Receiver-Initiated Reservation-Based Protocol for Underwater Acoustic Networks. IEEE Journal on Selected Areas in Communications, 26(9), 1744-1753. doi:10.1109/jsac.2008.081213Zenia, N. Z., Aseeri, M., Ahmed, M. R., Chowdhury, Z. I., & Shamim Kaiser, M. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computer Applications, 71, 72-85. doi:10.1016/j.jnca.2016.06.005Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. (2017). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061-2075. doi:10.1007/s11276-017-1461-xSánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2015). An Acoustic Modem Featuring a Multi-Receiver and Ultra-Low Power. Circuits and Systems, 06(01), 1-12. doi:10.4236/cs.2015.6100

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig