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Data-Aware Service Placement in the Cloud-IoT Continuum

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Book cover Service-Oriented Computing (SummerSOC 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1603))

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Abstract

We present a declarative solution to determine, in a data-aware manner, application service placements and SDN data routings over Cloud-IoT infrastructures while meeting functional (software, hardware, IoT) and non-functional (security, latency, bandwidth) application requirements. The solution employs continuous reasoning to speed up the reconfiguration of application placements and routing decisions at runtime, when needed. An open-source Prolog prototype is presented and assessed over a scenario based on lifelike data.

This work has been partly supported by the EU Horizon 2020 Research and Innovation program, under project ACCORDION (G.A. 871793), and by project Energy-aware management of software applications in Cloud-IoT ecosystems (RIC2021PON_A18), funded with ESF REACT-EU resources by the Italian Ministry of University and Research through the PON Ricerca e Innovazione 2014–20.

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Notes

  1. 1.

    Due to space limitations, only the main predicates of DAPlacer are presented. The prototype is open-sourced at https://github.com/di-unipi-socc/daplacer.

  2. 2.

    Prolog is a declarative programming language based on first-order logic. Prolog programs consist of clauses of the form a :- b1, ..., bn. stating that a holds if b1 \(\wedge \ldots \wedge \) bn holds. Clauses with empty premise (n = 0) are called facts. Predicate definitions can also contain disjunctions (denoted by ;) and negations (denoted by \(\backslash \) +). Variables start with upper-case letters. Prolog programs can be queried, and the Prolog interpreter tries to answer each query by applying SLD resolution [20] and by returning a computed answer substitution instantiating the variables in the query. For instance, the query ?- nice(W). on the program

    figure c

    returns the computed answer substitution {barbara \(/\) W }, obtained by first rewriting the query by applying the first clause for honest/1 and failing, and then applying the second clause for honest/1 and then the clause defining gentle/1.

  3. 3.

    The full application declaration is available at https://github.com/di-unipi-socc/daplacer/blob/main/app.pl.

  4. 4.

    Code of findRoutes/7 predicate is not shown. It is available at https://github.com/di-unipi-socc/daplacer/blob/main/daplacer.pl.

  5. 5.

    Monitoring tools for Cloud-IoT infrastructure exists such as FogMon [10] or those surveyed in [35].

  6. 6.

    All experiments were run on a machine featuring macOS Monterey 12.3, and equipped with 16 GB of RAM and a 2,5 GHz Intel Core i7 quad-core processor. Experiments code is accessible at: https://github.com/di-unipi-socc/daplacer/tree/main/experiment.

  7. 7.

    Experimental results are aggregated over 10 repetitions of the described 600 epoch simulations.

  8. 8.

    For each selected node, its hardware availability is changed by considering its initially available RAM and HDD resources and picking a value in the range [1, 1.1 \(\times \) RAM] and [1, 1.2 \(\times \) HDD], respectively. Analogously, the bandwidth of selected links is picked anew in the range [1, 1.1 \(\times \) BW], where BW is the initial bandwidth featured by the link. Similarly, the latency of selected links is changed within [LAT/2, 1.5 \(\times \) LAT], where LAT is the initial link latency.

References

  1. Aleti, A., Bjornander, S., Grunske, L., Meedeniya, I.: ArcheOpterix: an extendable tool for architecture optimization of AADL models. In: ICSE MOMPES (2009)

    Google Scholar 

  2. Barabási, A.L., Pósfai, M.: Network Science. Cambridge University Press, Cambridge (2016)

    Google Scholar 

  3. Bellavista, P., Berrocal, J., Corradi, A., Das, S.K., Foschini, L., Zanni, A.: A survey on fog computing for the internet of things. Pervasive Mob. Comput. 52, 71–99 (2019)

    Article  Google Scholar 

  4. Brogi, A., Forti, S.: QoS-aware deployment of IoT applications through the fog. IEEE Internet Things J. 4(5), 1185–1192 (2017)

    Article  Google Scholar 

  5. Brogi, A., Forti, S., Guerrero, C., Lera, I.: How to place your apps in the fog - state of the art and open challenges. Softw. Pract. Exp. 50(5), 719–740 (2020)

    Article  Google Scholar 

  6. Casadei, R., Viroli, M.: Coordinating computation at the edge: a decentralized, self-organizing, spatial approach. In: FMEC 2019 (2019)

    Google Scholar 

  7. Forti, S., Bisicchia, G., Brogi, A.: Declarative continuous reasoning in the cloud-IoT continuum. J. Logic Comput. 32(2), 206–232 (2022)

    Article  MathSciNet  Google Scholar 

  8. Forti, S., Brogi, A.: Declarative osmotic application placement. In: Advanced Information Systems Engineering Workshops, vol. 423 (2021)

    Google Scholar 

  9. Forti, S., Ferrari, G.L., Brogi, A.: Secure cloud-edge deployments, with trust. Future Gener. Comput. Syst. 102, 775–788 (2020)

    Article  Google Scholar 

  10. Forti, S., Gaglianese, M., Brogi, A.: Lightweight self-organising distributed monitoring of Fog infrastructures. Future Gener. Comput. Syst. 114, 605–618 (2021)

    Article  Google Scholar 

  11. Forti, S., Lera, I., Guerrero, C., Brogi, A.: Osmotic management of distributed complex systems: a declarative decentralised approach. J. Softw. Evol. Process (2021)

    Google Scholar 

  12. Forti, S., Paganelli, F., Brogi, A.: Probabilistic QoS-aware placement of VNF chains at the edge. Theory Pract. Logic Program. 22(1), 1–36 (2021)

    MathSciNet  Google Scholar 

  13. Guerrero, C., Lera, I., Juiz, C.: A lightweight decentralized service placement policy for performance optimization in fog computing. J. Ambient. Intell. Humaniz. Comput. 10(6), 2435–2452 (2018). https://doi.org/10.1007/s12652-018-0914-0

    Article  Google Scholar 

  14. Gupta, H., Vahid Dastjerdi, A., Ghosh, S.K., Buyya, R.: iFogSim: a toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Soft. Pract. Exp. 47(9), 1275–1296 (2017)

    Article  Google Scholar 

  15. Kadioglu, S., Colena, M., Sebbah, S.: Heterogeneous resource allocation in cloud management. In: NCA 2016 (2016)

    Google Scholar 

  16. Khan, N., et al.: Big data: Survey, technologies, opportunities, and challenges. Sci. World J. (2014)

    Google Scholar 

  17. Koziolek, A., Koziolek, H., Reussner, R.: PerOpteryx: automated application of tactics in multi-objective software architecture optimization (2011)

    Google Scholar 

  18. Lera, I., Guerrero, C., Juiz, C.: Comparing centrality indices for network usage optimization of data placement policies in fog devices. In: 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC) (2018)

    Google Scholar 

  19. Lera, I., Guerrero, C., Juiz, C.: YAFS: a simulator for IoT scenarios in fog computing. IEEE Access 7, 91745–91758 (2019)

    Article  Google Scholar 

  20. Lloyd, J.W.: Foundations of Logic Programming. Springer, Heidelberg (1987). https://doi.org/10.1007/978-3-642-83189-8

    Book  MATH  Google Scholar 

  21. Mahmud, R., Ramamohanarao, K., Buyya, R.: Latency-aware application module management for fog computing environments. ACM Trans. Internet Technol. 19(1), 1–21 (2018)

    Article  Google Scholar 

  22. Mahmud, R., Ramamohanarao, K., Buyya, R.: Application management in fog computing environments: a taxonomy, review and future directions. ACM Comput. Surv. 53(4), 1–43 (2020)

    Article  Google Scholar 

  23. Margariti, S.V., Dimakopoulos, V.V., Tsoumanis, G.: Modeling and simulation tools for fog computing-a comprehensive survey from a cost perspective. Future Internet 12(5), 89 (2020)

    Article  Google Scholar 

  24. NAAS, M.I., Lemarchand, L., Boukhobza, J., Raipin, P.: A graph partitioning-based heuristic for runtime IoT data placement strategies in a fog infrastructure. In: Proceedings of the 33rd Annual ACM Symposium on Applied Computing (2018)

    Google Scholar 

  25. Naas, M.I., Parvedy, P.R., Boukhobza, J., Lemarchand, L.: iFogStor: an IoT data placement strategy for fog infrastructure. In: 2017 IEEE 1st International Conference on Fog and Edge Computing (ICFEC) (2017)

    Google Scholar 

  26. Ning, Z., Kong, X., Xia, F., Hou, W., Wang, X.: Green and sustainable cloud of things: enabling collaborative edge computing. IEEE Commun. Mag. 57(1), 72–78 (2019)

    Article  Google Scholar 

  27. Pianini, D., Casadei, R., Viroli, M., Natali, A.: Partitioned integration and coordination via the self-organising coordination regions pattern. Future Gener. Comput. Syst. 114, 44–68 (2021)

    Article  Google Scholar 

  28. Pietri, I., Sakellariou, R.: Mapping virtual machines onto physical machines in cloud computing: a survey. ACM Comput. Surv. 49(3), 1–30 (2016)

    Article  Google Scholar 

  29. Qiu, T., Chi, J., Zhou, X., Ning, Z., Atiquzzaman, M., Wu, D.O.: Edge computing in industrial internet of things: architecture, advances and challenges. IEEE Commun. Surv. Tutorials 22(4), 2462–2488 (2020)

    Article  Google Scholar 

  30. Rak, J.: Resilience of future internet communications. In: Rak, J. (ed.) Resilient Routing in Communication Networks. CCN, pp. 45–83. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22333-9_3

    Chapter  Google Scholar 

  31. Salaht, F.A., Desprez, F., Lebre, A.: An overview of service placement problem in fog and edge computing. ACM Comput. Surv. 53(3), 1–35 (2020)

    Article  Google Scholar 

  32. Samizadeh Nikoui, T., Rahmani, A., Tabarsaied, H.: Data Management in Fog Computing: Principles and Paradigms. Wiley, Hoboken (2019)

    Google Scholar 

  33. Sándor, H., Genge, B., Sebestyén-Pál, G.: Resilience in the internet of things: the software defined networking approach. In: 2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) (2015)

    Google Scholar 

  34. Sonmez, C., Ozgovde, A., Ersoy, C.: EdgeCloudSim: an environment for performance evaluation of edge computing systems. Trans. Emerg. Telecommun. Technol. 29, e3493 (2018)

    Article  Google Scholar 

  35. Taherizadeh, S., Jones, A.C., Taylor, I., Zhao, Z., Stankovski, V.: Monitoring self-adaptive applications within edge computing frameworks: a state-of-the-art review. J. Syst. Softw. 136, 19–38 (2018)

    Article  Google Scholar 

  36. Tortonesi, M., Govoni, M., Morelli, A., Riberto, G., Stefanelli, C., Suri, N.: Taming the IoT data deluge: an innovative information-centric service model for fog computing applications. Future Gener. Comput. Syst. 93, 888–902 (2019)

    Article  Google Scholar 

  37. Vaquero, L.M., Cuadrado, F., Elkhatib, Y., Bernal-Bernabe, J., Srirama, S.N., Zhani, M.F.: Research challenges in nextgen service orchestration. Future Gener. Comput. Syst. 90, 20–38 (2019)

    Article  Google Scholar 

  38. Verginadis, Y., Alshabani, I., Mentzas, G., Stojanovic, N.: Prestocloud: proactive cloud resources management at the edge for efficient real-time big data processing. In: CLOSER (2017)

    Google Scholar 

  39. Villari, M., Fazio, M., Dustdar, S., Rana, O., Ranjan, R.: Osmotic computing: a new paradigm for edge/cloud integration. IEEE Cloud Comput. 3(6), 76–83 (2016)

    Article  Google Scholar 

  40. Wang, S., Zafer, M., Leung, K.K.: Online placement of multi-component applications in edge computing environments. IEEE Access 5, 2514–2533 (2017)

    Article  Google Scholar 

  41. Yin, Q., Schüpbach, A., Cappos, J., Baumann, A., Roscoe, T.: Rhizoma: a runtime for self-deploying, self-managing overlays. In: Middleware 2009 (2009)

    Google Scholar 

  42. Yousefpour, A., et al.: All one needs to know about fog computing and related edge computing paradigms: a complete survey. J. Syst. Archit. 98, 289–330 (2019)

    Article  Google Scholar 

  43. Zikria, Y.B., Ali, R., Afzal, M.K., Kim, S.W.: Next-generation internet of things (IoT): opportunities, challenges, and solutions. Sensors 21(4), 1174 (2021)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, University of Pisa, Pisa, Italy

    Jacopo Massa, Stefano Forti & Antonio Brogi

Authors
  1. Jacopo Massa
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  2. Stefano Forti
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  3. Antonio Brogi
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Correspondence to Jacopo Massa .

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Editors and Affiliations

  1. University of Stuttgart, Stuttgart, Germany

    Johanna Barzen

  2. University of Stuttgart, Stuttgart, Germany

    Frank Leymann

  3. TU Wien, Vienna, Austria

    Schahram Dustdar

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Massa, J., Forti, S., Brogi, A. (2022). Data-Aware Service Placement in the Cloud-IoT Continuum. In: Barzen, J., Leymann, F., Dustdar, S. (eds) Service-Oriented Computing. SummerSOC 2022. Communications in Computer and Information Science, vol 1603. Springer, Cham. https://doi.org/10.1007/978-3-031-18304-1_8

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  • DOI: https://doi.org/10.1007/978-3-031-18304-1_8

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