Abstract
The development of the Semantic Web of Things (SWoT) is challenged by the nature of IoT architectures where constrained devices are connected to powerful cloud servers in charge of processing remotely collected data. Such an architectural pattern introduces multiple bottlenecks constituting a hurdle for scalability, and degrades the QoS parameters such as response time. This hinders the development of a number of critical and time-sensitive applications. As an alternative to this Cloud-centric architecture, Fog-enabled architectures can be considered to take advantage of the myriad of devices that can be used for partially processing data circulating between the local sensors and the remote Cloud servers. The approach developed in this paper is a contribution in this direction: it aims to enable rule-based processing to be deployed closer to data sources, in order to foster the implementation of semantic-enabled applications. For this purpose, we define a dynamic deployment technique for rule-based semantic reasoning on Fog nodes. This technique has been evaluated according to a strategy improving information delivery delay to applications. The implementation in Java based on SHACL rules has been executed on a platform containing a server, a laptop and a Raspberry Pi, and is evaluated on a smart building use case where both distribution and scalability have been considered.
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Notes
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Used namespaces: edr:<https://w3id.org/laas-iot/edr>, lmu:<https://w3id.org/laas-iot/lmu>, sh:<http://www.w3.org/ns/shacl>, ex:<http://example.org/ns>.
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Individuals such as \(n-p\) and \(n_c\) are identified with a URI in the triplets.
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The code is available at https://framagit.org/nseydoux/edr.
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Topology representations are available at https://w3id.org/laas-iot/edr/iiot/scala_syndream/clone_f_<0,1,2>.ttl respectively.
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References
Alaya, M.B., Medjiah, S., Monteil, T., Drira, K.: Toward semantic interoperability in oneM2M architecture. IEEE Commun. Mag. 53(12), 35–41 (2015). https://doi.org/10.1109/MCOM.2015.7355582
Ali, M.I., et al.: Real-time data analytics and event detection for IoT-enabled communication systems. Web Semant.: Sci. Serv. Agents World Wide Web 42, 19–37 (2017). https://doi.org/10.1016/j.websem.2016.07.001
Desai, P., Sheth, A., Anantharam, P.: Semantic Gateway as a Service architecture for IoT Interoperability. Netw. Internet Arch., 16 (2014). https://doi.org/10.1109/MobServ.2015.51
Gyrard, A., Serrano, M., Jares, J.B., Datta, S.K., Ali, M.I.: Sensor-based Linked Open Rules (S-LOR): An Automated Rule Discovery Approach for IoT Applications and its use in Smart Cities. In: International Conference on World Wide Web Companion, pp. 1153–1159 (2017). https://doi.org/10.1145/3041021.3054716
Kaed, C.E., Khan, I., Berg, A.V.D., Hossayni, H., Saint-Marcel, C.: SRE: semantic rules engine for the industrial Internet-of-Things gateways. IEEE Trans. Ind. Inform. 14(2), 715–724 (2018). https://doi.org/10.1109/TII.2017.2769001
Kaed, C.E., Khan, I., Hossayni, H., Nappey, P.: SQenloT: semantic query engine for industrial Internet-of-Things gateways. In: 2016 IEEE 3rd World Forum on Internet of Things, WF-IoT 2016, pp. 204–209 (2016). https://doi.org/10.1109/WF-IoT.2016.7845468
Kaed, C.E., Khan, I., Van Den Berg, A., Hossayni, H., Saint-Marcel, C.: SRE: semantic rules engine for the industrial Internet- of-Things gateways. IEEE Trans. Ind. Inform. 14(2), 715–724 (2018). https://doi.org/10.1109/TII.2017.2769001
Khandelwal, A., Jacobi, I., Kagal, L.: Linked rules: principles for rule reuse on the web. In: Rudolph, S., Gutierrez, C. (eds.) RR 2011. LNCS, vol. 6902, pp. 108–123. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-23580-1_9
Kiljander, J., et al.: Semantic interoperability architecture for pervasive computing and Internet of Things. IEEE Access 2, 856–873 (2014). https://doi.org/10.1109/ACCESS.2014.2347992
Li, Z., Chu, C.H., Yao, W., Behr, R.A.: Ontology-driven event detection and indexing in smart spaces. In: IEEE International Conference on Semantic Computing, pp. 285–292 (2010). https://doi.org/10.1109/ICSC.2010.63
Maarala, A.I., Su, X., Riekki, J.: Semantic reasoning for context-aware internet of things applications. IEEE Internet Things J. 4(2), 461–473 (2017)
Nikoli, S., Penca, V., Konjovi, Z.: Semantic web based architecture for managing hardware heterogeneity in wireless sensor network. Int. J. Comput. Sci. Appl. 8(2), 38–58 (2011)
Patel, P., Intizar Ali, M., Sheth, A.: On using the intelligent edge for IoT analytics. IEEE Intell. Syst. 32(5), 64–69 (2017). https://doi.org/10.1109/MIS.2017.3711653
Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Context aware computing for the internet of things: a survey. IEEE Commun. Surv. Tutor. 16(1), 414–454 (2014). https://doi.org/10.1109/SURV.2013.042313.00197
Pfisterer, D., et al.: SPITFIRE: toward a semantic web of things. IEEE Commun. Mag. 49(11), 40–48 (2011). https://doi.org/10.1109/MCOM.2011.6069708
Poslad, S., Middleton, S.E., Chaves, F., Tao, R., Necmioglu, O., Bugel, U.: A semantic IoT early warning system for natural environment crisis management. IEEE Trans. Emerg. Top. Comput. 3(2), 246–257 (2015). https://doi.org/10.1109/TETC.2015.2432742
Seydoux, N., Drira, K., Hernandez, N., Monteil, T.: Reasoning on the edge or in the cloud? Internet Technol. Lett., e51
Seydoux, N., Drira, K., Hernandez, N., Monteil, T.: Capturing the contributions of the semantic web to the IoT: a unifying vision. In: Maleshkova, M., Verborgh, R., Gyrard, A. (eds.) Proceedings of the Second SWIT Workshop Co-located with ISWC. CEUR Workshop Proceedings, vol. 1930 (2017)
Sezer, O.B., Dogdu, E., Ozbayoglu, A.M.: Context-aware computing, learning, and big data in internet of things: a survey. IEEE Internet Things J. 5, 1–27 (2018)
Sheth, A., Henson, C., Sahoo, S.S.: Semantic sensor web. IEEE Internet Comput. 12(4), 78–83 (2008). https://doi.org/10.1109/MIC.2008.87
Shi, W., Dustdar, S.: The promise of edge computing. Computer 49(5), 78–81 (2016)
Su, X., et al.: Distribution of semantic reasoning on the edge of Internet of Things. In: IEEE UbiComp, p. 79, November 2018
Szilagyi, I., Wira, P.: Ontologies and semantic web for the Internet of Things - a survey. In: IECON. IEEE (2016)
Taneja, M., Davy, A.: Resource aware placement of IoT application modules in Fog-Cloud Computing Paradigm. In: 2017 IFIP/IEEE Symposium on Integrated Network and Service Management, pp. 1222–1228. IEEE, May 2017. https://doi.org/10.23919/INM.2017.7987464
Wang, S., Wan, J., Li, D., Liu, C.: Knowledge reasoning with semantic data for real-time data processing in smart factory. Sensors (Switzerland) 18(2), 1–10 (2018). https://doi.org/10.3390/s18020471
Xu, G., Cao, Y., Ren, Y., Li, X., Feng, Z.: Network security situation awareness based on semantic ontology and user-defined rules for internet of things. IEEE Access 5, 21046–21056 (2017)
Zanella, A., Bui, N., Castellani, A., Vangelista, L., Zorzi, M.: Internet of Things for smart cities. IEEE Internet Things J. 1(1), 22–32 (2014). https://doi.org/10.1109/JIOT.2014.2306328
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Seydoux, N., Drira, K., Hernandez, N., Monteil, T. (2018). Towards Cooperative Semantic Computing: A Distributed Reasoning Approach for Fog-Enabled SWoT. In: Panetto, H., Debruyne, C., Proper, H., Ardagna, C., Roman, D., Meersman, R. (eds) On the Move to Meaningful Internet Systems. OTM 2018 Conferences. OTM 2018. Lecture Notes in Computer Science(), vol 11229. Springer, Cham. https://doi.org/10.1007/978-3-030-02610-3_23
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