Abstract
In this paper, a distributed solution is presented for the composition of complex event services in the Internet of Things (IoT) environments. The composition of objects services in the IoT environment requires scalable and adaptable methods due to the dynamics of the network. The dynamics accommodate both the large volume of objects and the tolerance of object displacement and link failure. The composition of complex event services is more scalable and reusable. The composition of these services is done in several steps. First, the user’s goals are transformed into an event schema through a backward-chaining mechanism. Then, the event schema is matched with complex event services in the fog layer. Finally, this event schema is used to access the required services. Besides, heuristic functions are also provided to control network traffic, increase execution consistency, and reduce service failure rates. An extensive evaluation of various metrics has been done. The results show that the proposed solution is scalable and adaptable in a hierarchical IoT network with mobile objects.
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References
Khanouche ME, Amirat Y, Chibani A, Kerkar M, Yachir A (2016) Energy-centered and QoS-aware services selection for Internet of Things. IEEE Trans Autom Sci Eng 13(3):1256–1269
Zhang Y, Duan L, Chen JL (2014) Event-driven SOA for IoT services. Paper Presented at the 2014 IEEE International Conference on Services Computing,
Mahmud R, Kotagiri R, Buyya R (2018) Fog computing: a taxonomy, survey and future directions. Internet of everything. Springer, Heidelberg, pp 103–130
Gao F, Curry E, Bhiri S (2014) Complex event service provision and composition based on event pattern matchmaking. In: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, 2014. ACM, pp 71–82
Ottenwälder B, Koldehofe B, Rothermel K, Hong K, Lillethun D, Ramachandran U (2014) MCEP: a mobility-aware complex event processing system. ACM Trans Internet Technol (TOIT) 14(1):6
Deng S, Huang L, Taheri J, Yin J, Zhou M, Zomaya AY (2016) Mobility-aware service composition in mobile communities. IEEE Trans Syst Man Cybern Syst 47(3):555–568
Cheng B, Wang M, Zhao S, Zhai Z, Zhu D, Chen J (2017) Situation-aware dynamic service coordination in an IoT environment. IEEE/ACM Trans Netw (TON) 25(4):2082–2095
Sotiriadis S, Bessis N (2016) An inter-cloud bridge system for heterogeneous cloud platforms. Future Gener Comput Syst 54:180–194
Amrani M, Gilson F, Englebert V (2017) Complex event processing for user-centric management of IoT Systems. Springer, Heidelberg, pp 426–448
Gao F, Curry E (2020) Quality of service-aware complex event service composition in real-time linked dataspaces. In: Curry E (ed) Real-time linked dataspaces: enabling data ecosystems for intelligent systems. Springer Cham, New York, pp 169–190. https://doi.org/10.1007/978-3-030-29665-0_11
Bok K, Kim D, Yoo J (2018) Complex event processing for sensor stream data. Sensors 18(9):3084
Luthra M, Koldehofe B, Weisenburger P, Salvaneschi G, Arif R (2018) TCEP: Adapting to dynamic user environments by enabling transitions between operator placement mechanisms. In: Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems, 2018. ACM, pp 136–147
Taherkordi A, Eliassen F, Mcdonald M, Horn G (2019) Context-driven and real-time provisioning of data-centric IoT services in the cloud. ACM Trans Internet Technol (TOIT) 19(1):1–24
Taherkordi A, Eliassen F (2017) Data-centric IoT services provisioning in fog-cloud computing systems. In: Proceedings of the Second International Conference on Internet-of-Things Design and Implementation, 2017. ACM, pp 317–318
Asghari P, Rahmani AM, Javadi HHS (2018) Service composition approaches in IoT: a systematic review. J Netw Comput Appl 120:61–77. https://doi.org/10.1016/j.jnca.2018.07.013
Jha DN, Alwasel K, Alshoshan A, Huang X, Naha RK, Battula SK, Garg S, Puthal D, James P, Zomaya A (2020) IoTSim-Edge: a simulation framework for modeling the behavior of Internet of Things and edge computing environments. Softw Pract Exp 50(6):844–867
Alsaryrah O, Mashal I, Chung T-Y (2018) Energy-aware services composition for Internet of Things. In: 2018 IEEE 4th World Forum on Internet of Things (WF-IoT), 2018. IEEE, pp 604–608
Ibrahim GJ, Rashid TA, Akinsolu MO (2020) An energy efficient service composition mechanism using a hybrid meta-heuristic algorithm in a mobile cloud environment. J Parallel Distribut Comput 143:77–87. https://doi.org/10.1016/j.jpdc.2020.05.002
Chen N, Cardozo N, Clarke S (2016) Goal-driven service composition in mobile and pervasive computing. IEEE Trans Serv Comput 11(1):49–62
Ko I-Y, Ko H-G, Molina AJ, Kwon J-H (2016) SoIoT: Toward a user-centric IoT-based service framework. ACM Trans Internet Technol (TOIT) 16(2):8
Shamir R, Tsur D (1999) Faster subtree isomorphism. J Algorithms 33(2):267–280
Miller RB (1968) Response time in man-computer conversational transactions. In: AFIPS Fall Joint Computing Conference, pp 267–277
Sadagopan N, Bai F, Krishnamachari B, Helmy A (2003) PATHS: analysis of PATH duration statistics and their impact on reactive MANET routing protocols. In: Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing, 2003. ACM, pp 245–256
BonnMotion (2019) A mobility scenario generation and analysis tool. https://sys.cs.uos.de/bonnmotion/doc/README.pdf.
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Esmaeilyfard, R., Naderi, M. Distributed composition of complex event services in IoT network. J Supercomput 77, 6123–6144 (2021). https://doi.org/10.1007/s11227-020-03498-2
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DOI: https://doi.org/10.1007/s11227-020-03498-2