Abstract
In recent years, the use of wireless sensors has increased drastically in most fields. Wireless Sensor Networks (WSNs) have attracted the interest of industries and they have been used in several application areas (military, health, transportation, agriculture). WSNs are ad-hoc networks, composed of sensor nodes, which are deployed in an area of interest, in order to monitor and to return information requested by users. Sensor data is transmitted to users over a central station, named base station. Data collection becomes more difficult when the number of sensors increases. Since about a decade, intensive research has started in order to deal with these problems. Many researchers suggested to structure the sensor data in the form of a database and reduce the number of communications and energy consumption in the network. They have often considered the network as a large database and the sensor node as a virtual table. In this article, the existing sensor database approaches in WSNs are studied. Firstly, we will provide the definition of sensor databases, then we will present their architecture and their characteristics. Thereafter, we will present and compare existing sensor database systems. Finally, we will conclude this paper with a discussion of some research issues in the field of sensor databases.
Similar content being viewed by others
Notes
REpresentational State Transfer
Extensible Markup Language
the signal processing functions transform physical signals like temperature, light, humidity, into data
References
Abdaoui, A., & El-Fouly, T. M. (2014). TOSSIM and distributed binary consensus algorithm in wireless sensor networks. Journal Network and Computer Applications, 41, 451–458.
Abramova, V., & Bernardino, J. (2013). Nosql databases: Mongodb vs cassandra. In Proceedings of the international conference on computer science and software engineering, C3S2E ’13 (pp. 14–22). ACM, New York, NY, USA.
Adam, D., & Tsiftes, N. (2011). A database in every sensor. In Proceedings of the ACM conference on networked embedded sensor systems. ACM, Seattle, WA, USA.
Akpinar, K., Hua, K.A., & Li, K. (2015). Thingstore: A platform for internet-of-things application development and deployment. In Proceedings of the 9th ACM international conference on distributed event-based systems, DEBS ’15 (pp. 162–173). ACM, New York, NY, USA.
Alabdulatif, A., Khalil, I., Yi, X., & Guizani, M. (2019). Secure edge of things for smart healthcare surveillance framework. IEEE Access, 7, 31010–31021.
Alami, A. E., Bahaj, M., & Khourdifi, Y. (2018). Supply of a key value database redis in-memory by data from a relational database. In IEEE mediterranean electrotechnical conference (MELECON) (pp. 46–51).
Alsboui, M. T., AB Uarqoub, A., Hammoudeh, M., Bandar, Z., & Nisbet, A. (2012). Information extraction from wireless sensor networks: System and approaches. Sensors and Transducers Journal, 14(2), 1–17.
Amato, G., Chessa, S., & Vairo, C. (2010). MaD-WiSe: A distributed stream management system for wireless sensor networks. Software: Practice and Experience, 40(5), 431–451.
Anamalamudi, S., Sangi, A. R., Alkatheiri, M., & Ahmed, A. M. (2018). AODV routing protocol for cognitive radio access based internet of things (IoT). Future Generation Computer Systems, 83, 228–238.
Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805.
Azqueta-Alzaz, A., Patio-Martinez, M., Brondino, I., & Jimenez-Peris, R. (2017). Massive data load on distributed database systems over HBase. In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) (pp. 776–779).
Bermúdez-Edo, M., Elsaleh, T., Barnaghi, P. M., & Taylor, K. (2017). IoT-Lite: A lightweight semantic model for the internet of things and its use with dynamic semantics. Personal and Ubiquitous Computing, 21(3), 475–487.
Bonnet, P., Gehrke, J., & Seshadri, P. (2001). Towards Sensor Database Systems. In Proceedings of the international conference on mobile data management (pp. 3–14). Springer-Verlag, London, UK.
Botta, A., de Donato, W., Persico, V., & Pescapè, A. (2016). Integration of cloud computing and internet of things: A survey. Future Generation Computer Systems, 56, 684–700.
Chaiporn, J., Chavalit, S., & Chien-Chung, S. (2000). Querying and tasking in sensor networks. In Proceedings of the international symposium on aerospace/defense sensing, simulation, and control (pp. 184–197). SPIE–The International Society for Optical Engineering.
Chipara, O., Lu, C., & Stankovic, J. (2006). Dynamic conflict-free query scheduling for wireless sensor networks. In Proceedings of the IEEE international conference on network protocols (pp. 321–331). IEEE Computer Society, Washington, DC, USA
Compton, M., Barnaghi, P., Bermudez, L., Garca-Castro, R., Corcho, O., Cox, S., et al. (2012). The SSN ontology of the W3C semantic sensor network incubator group. Journal of Web Semantics, 17, 25–32.
Daniel, T. E., Newman, R. M., Gaura, E. I., & Mount, S. N. (2007). Complex query processing in wireless sensor networks. In Proceedings of the workshop on performance monitoring and measurement of heterogeneous wireless and wired networks (pp. 53–60). ACM, New York, NY, USA.
Dawborn, T., & Khoury, R. (2010). Corona developers guide. Technical report, University of Sydney.
Dhand, G., & Tyagi, S. (2016). Data aggregation techniques in WSN: Survey. Procedia Comput. Sci., 92, 378–384.
Diallo, O., Rodrigues, J. J., & Sene, M. (2012). Real-time data management on wireless sensor networks: A survey. Journal of Network and Computer Applications, 35(3), 1013–1021.
Diallo, O., Rodrigues, J. J. P. C., Sene, M., & Mauri, J. L. (2015). Distributed database management techniques for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 26(2), 604–620.
Diallo, O., Rodrigues, J. J. P. C., Sene, M., & Xia, F. (2015). Real-time query processing optimisation for wireless sensor networks. International Journal of Sensor Networks, 18(1/2), 49–61.
Elias, A., Rodrigues, J., Oliveira, L., & Zarpelao, B. (2012). A ubiquitous model for wireless sensor networks monitoring. In International conference on innovative mobile and internet services in ubiquitous computing (pp. 835–839). IEEE.
Erman, A. T., Mutter, T., van Hoesel, L., & Havinga, P. J. M. (2009). A cross-layered communication protocol for load balancing in large scale multi-sink wireless sensor networks. In International symposium on autonomous decentralized systems (pp. 223–230), Athens, Greece.
Fatima, H., & Wasnik, K. (2016). Comparison of SQL, NoSQL and NewSQL databases for internet of things. In 2016 IEEE Bombay Section Symposium (IBSS) (pp. 1–6).
Ferreira, D., Corista, P., Gio, J., Ghimire, S., Sarraipa, J., & Jardim-Gonalves, R. (2017). Towards smart agriculture using fiware enablers. In 2017 International Conference on Engineering, Technology and Innovation (ICE/ITMC) (pp. 1544–1551).
Fouad, M. M., Oweis, N. E., Gaber, T., Ahmed, M., & Snasel, V. (2015). Data mining and fusion techniques for wsns as a source of the big data. Procedia Computer Science, 65, 778–786.
Fung, W. F., Sun, D., & Gehrke, J. (2002). COUGAR: The network is the database. In Proceedings of the international conference on Management of data (pp. 621–621), ACM, New York, NY, USA.
Gajjar, S., Choksi, N., Sarkar, M., & Dasgupta, K. (2014). Comparative analysis of wireless sensor network motes. In 2014 International Conference on Signal Processing and Integrated Networks (SPIN) (pp. 426–431).
Galindo-Serrano, A., & Giupponi, L. (2010). Distributed q-learning for aggregated interference control in cognitive radio networks. IEEE Transactions on Vehicular Technology, 59(4), 1823–1834.
Govindan, R., Hellerstein, J., Hong, W., Madden, S., Franklin, M., & Shenker, S. (2002). The sensor network as a database. Technical Report 02-771, USC Information Sciences Institute.
Hahm, O., Baccelli, E., Petersen, H., & Tsiftes, N. (2016). Operating systems for low-end devices in the internet of things: A survey. IEEE Internet of Things Journal, 3(5), 720–734.
Hu, F., & Cao, X. (2010). Sensor data management. In Wireless sensor networks: Principles and practice (pp. 237–257). SCRC Press, Taylor & Francis Group.
Jabeen, F., & Nawaz, S. (2015). In-network wireless sensor network query processors: State of the art, challenges and future directions. Information Fusion, 25, 1–15.
Jaikaeo, C., Srisathapornphat, C., & Shen, C. C. (2000). Sensor information networking architecture. In Proceedings of the international workshop on parallel processing (pp. 23–30). IEEE.
Jun Zheng, A. J. (2009). Wireless sensor networks: A networking perspective (1st ed.). Hoboken: Wiley-IEEE Press.
Kanzaki, A., Hara, T., Ishi, Y., Yoshihisa, T., Teranishi, Y., & Shimojo, S. (2010). X-sensor: Wireless sensor network testbed integrating multiple networks. In T. Hara, V. I. Zadorozhny, & E. Buchmann (Eds.), Wireless sensor network technologies for the information explosion era (Vol. 278, pp. 249–271)., Studies in computational intelligence Berlin: Springer.
Kaur, K., & Sachdeva, M. (2017). Performance evaluation of NewSQL databases. In 2017 International Conference on Inventive Systems and Control (ICISC) (pp. 1–5).
Kellner, S. (2010). Flexible online energy accounting in TinyOS. In Proceedings of the International Workshop in Real-World Wireless Sensor Networks (pp. 62–73). Springer, Colombo, Sri Lanka.
Khan, M. I., Gansterer, W. N., & Haring, G. (2013). Static vs. mobile sink: The influence of basic parameters on energy efficiency in wireless sensor networks. Computer Communications, 36(9), 965–978.
Khoury, R., Dawborn, T., Gafurov, B., Pink, G., Tse, E., Tse, Q., et al. (2010). Corona: Energy-efficient multi-query processing in wireless sensor networks. In H. Kitagawa, Y. Ishikawa, Q. Li, & C. Watanabe (Eds.), Database systems for advanced applications (Vol. 5982, pp. 416–419)., Lecture notes in computer science Berlin: Springer.
Kiani, F., Amiri, E., Zamani, M., Khodadadi, T., & Manaf, A. A. (2015). Efficient intelligent energy routing protocol in wireless sensor networks. International Journal of Distributed Sensor Networks, 11, 1–13.
Kofoed, L. M. (2007). Enhancing sensor network programming: Extending TinyDB with HAVING and aggregation, and investigating TinyDB reliability. Master’s thesis, University of Oslo, Oslo, Norvège.
Levis, P., & Gay, D. (2009). TinyOS programming (1st ed.). Cambridge: Cambridge University Press.
Li, J., Cai, Z., & Li, J. (2008). Data management in sensor networks. In Y. Li, M. T. Thai, & W. Wu (Eds.), Wireless sensor networks and applications (pp. 287–330). Berlin: Springer.
Li, X., Liu, W., Xie, M., Liu, A., Zhao, M., Xiong, N. N., et al. (2018). Differentiated data aggregation routing scheme for energy conserving and delay sensitive wireless sensor networks. Sensors, 18(7), 2349.
Li, Y., Thai, M. T., & Wu, W. (2008). Wireless sensor networks and applications. Berlin: Springer.
Lim, C., Lee, J., Park, M., & Hyun, S. J. (2015). Design and implementation of spatial operators and energy-efficient query processing strategy in wireless sensor network database system. International Journal of Distributed Sensor Networks, 11(6), 509,471:1–509,471:17.
Madden, S., J. Franklin, M., M. Hellerstein, J., & Hong, W. (2005). TinyDB: An acquisitional query processing system for sensor networks. ACM Transactions on Database Systems, 30(1), 122–173.
Mishra, N., Chang, H., & Lin, C. (2018). Sensor data distribution and knowledge inference framework for a cognitive-based distributed storage sink environment. IJSNetInternational Journal of Sensor Networks, 26(1), 26–42.
Misic, J. V., & Misic, V. B. (2008). Enforcing patient privacy in healthcare wsns through key distribution algorithms. Security and Communication Networks, 1(5), 417–429.
Moraes, P., Reale, R., & Martins, J. (2018). A publish/subscribe QoS-aware framework for massive IoT traffic orchestration. CoRR arXiv:abs/1806.03157.
Mostafaei, H. (2019). Energy-efficient algorithm for reliable routing of wireless sensor networks. IEEE Transactions on Industrial Electronics, 66(7), 5567–5575.
Niu, J., Cheng, L., Gu, Y., Shu, L., & Das, S. K. (2014). R3E: Reliable reactive routing enhancement for wireless sensor networks. IEEE Transactions on Industrial Informatics, 10(1), 784–794.
Noël, G., & Servigne, S. (2004). Po-Tree: un système d’indexation spatio-temporel temps-réel . In: Cassini (ed.) Conférence CASSINI-SIGMA 2004 : Géomatique et Analyse Spatiale, pp. 120–121.
Nol, G. (2006). Indexation dans les bases de données capteurs temps réel. Ph.D. thesis, Institut National des Sciences Appliquées de Lyon.
Nol, G., & Servigne, S. (2005). Indexation multidimensionnelle de bases de données capteur temps-réel et spatiotemporelles. Ingénierie des Systèmes d’Information, 10(4), 59–88.
Pradittasnee, L., Camtepe, S., & Tian, Y. (2017). Efficient route update and maintenance for reliable routing in large-scale sensor networks. IEEE Transactions on Industrial Informatics, 13(1), 144–156.
Randhawa, S., & Jain, S. (2017). Data aggregation in wireless sensor networks: Previous research, current status and future directions. Wireless Personal Communications, 97(3), 3355–3425.
Ren, Y., Liu, Y., Ji, S., Sangaiah, A. K., & Wang, J. (2018). Incentive mechanism of data storage based on blockchain for wireless sensor networks. Mobile Information Systems, 2018, 1–10.
Rifi, N., Rachkidi, E., Agoulmine, N., & Taher, N. C. (2017). Towards using blockchain technology for iot data access protection. In 17th IEEE international conference on ubiquitous wireless broadband, ICUWB 2017 (pp. 1–5), Salamanca, Spain, 12–15 September 2017.
Sadagopan, N., Krishnamachari, B., & Helmy, A. (2003). The acquire mechanism for efficient querying in sensor networks. In Proceedings of the IEEE international workshop on sensor network protocols and applications (pp. 149–155). IEEE.
Samara, K., & Hosseini, H. (2015). A routing protocol for wireless sensor networks with reliable delivery of data. In IEEE international conference on data science and data intensive systems (pp. 632–635), Sydney, Australia.
Sarkar, S. K. (2012). Wireless sensor and ad hoc networks under diversified network scenarios. Norwood: Artech House.
Servigne, S., & Noël, G. (2008). Real time and spatiotemporal data indexing for sensor based databases. In Zlatanova & Li (Eds.), Geo-information technology for emergency response (pp. 123–141). London: Taylor & Francis Group.
Sheltami, T., Musaddiq, M., & Shakshuki, E. (2016). Data compression techniques in wireless sensor networks. Future Generation Computer Systems, 64, 151–162.
Shen, L., Ma, J., Liu, X., Wei, F., & Miao, M. (2017). A secure and efficient id-based aggregate signature scheme for wireless sensor networks. IEEE Internet of Things Journal, 4(2), 546–554.
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637–646.
Shwe, H. Y., Gacanin, H., & Adachi, F. (2010). Multi-layer WSN with power efficient buffer management policy. In IEEE international conference on communication systems (pp. 36–40). IEEE.
Sicari, S., Rizzardi, A., Cappiello, C., Miorandi, D., & Coen-Porisini, A. (2018). Toward data governance in the internet of things (pp. 59–74). Cham: Springer.
Srisathapornphat, C., Jaikaeo, C., & chung Shen, C. (2001). Sensorinformation networking architecture and applications. IEEE Personal Communications, 8, 52–59.
Sun, Y., & Jara, A. J. (2014). An extensible and active semantic model of information organizing for the internet of things. Personal and Ubiquitous Computing, 18(8), 1821–1833.
Terroso-Saenz, F., González-Vidal, A., Ramallo-González, A. P., & Skarmeta, A. F. (2019). An open iot platform for the management and analysis of energy data. Future Generation Computer Systems, 92, 1066–1079.
Thirukrishna, J. T., Karthik, S., & Arunachalam, V. P. (2018). Revamp energy efficiency in homogeneous wireless sensor networks using optimized radio energy algorithm (OREA) and power-aware distance source routing protocol. Future Generation Computer Systems, 81, 331–339.
Tongkaw, S., & Tongkaw, A. (2016). A comparison of database performance of MariaDB and MySQL with OLTP workload. In 2016 IEEE conference on open systems (ICOS) (pp. 117–119).
Tsiftes, N., Dunkels, A., He, Z., & Voigt, T. (2009). Enabling large-scale storage in sensor networks with the coffee file system. In Proceedings of the international conference on information processing in sensor networks (pp. 349–360), IEEE, Washington, DC, USA.
Ventrella, A. V., Grieco, L. A., & Piro, G. (2017). Information-centric networking in environmental monitoring: An overview on publish-subscribe implementations. In International Conference on Advanced Video and Signal Based Surveillance (AVSS) (pp. 1–6).
Wang, W., De, S., Toenjes, R., Reetz, E., & Moessner, K. (2012). A comprehensive ontology for knowledge representation in the internet of things. In International conference on trust, security and privacy in computing and communications (pp. 1793–1798).
Wu, S., Bao, L., Zhu, Z., Yi, F., & Chen, W. (2017). Storage and retrieval of massive heterogeneous IoT data based on hybrid storage. In International conference on natural computation, fuzzy systems and knowledge discovery (pp. 2982–2987), Guilin, China.
Xu, J., Guo, S., Xiao, B., & He, J. (2015). Energy-efficient big data storage and retrieval for wireless sensor networks with nonuniform node distribution. Concurrency Computation Practice and Experience, 27(18), 5765–5779.
Yao, Y., & Gehrke, J. (2002). The Cougar approach to in-network query processing in sensor networks. SIGMOD Record, 31(3), 9–18.
Yi, X., Bouguettaya, A., Georgakopoulos, D., Song, A., & Willemson, J. (2016). Privacy protection for wireless medical sensor data. IEEE Transactions on Dependable and Secure Computing, 13(3), 369–380.
Yi, X., Willemson, J., & Nait-Abdesselam, F. (2013). Privacy-preserving wireless medical sensor network. In 2013 12th IEEE international conference on trust, security and privacy in computing and communications (pp. 118–125).
Zhang, R., Pan, J., Xie, D., & Wang, F. (2016). NDCMC: a hybrid data collection approach for large-scale wsns using mobile element and hierarchical clustering. IEEE Internet of Things Journal, 3(4), 533–543.
Zhao, H., Qin, J., & Hu, J. (2013). An energy efficient key management scheme for body sensor networks. IEEE Transactions on Parallel and Distributed Systems, 24(11), 2202–2210.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Belfkih, A., Duvallet, C. & Sadeg, B. A survey on wireless sensor network databases. Wireless Netw 25, 4921–4946 (2019). https://doi.org/10.1007/s11276-019-02070-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11276-019-02070-y