Osmotic Flow Deployment Leveraging FaaS Capabilities

  • Alina BuzachisEmail author
  • Maria FazioEmail author
  • Antonio CelestiEmail author
  • Massimo VillariEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11874)


Nowadays, the rapid development of emerging Cloud, Fog, Edge, and Internet of Things (IoT) technologies has accelerated the advancement trends forcing applications and information systems (IS) to evolve. In this hybrid and distributed ecosystem, the management of service heterogeneity is complex, as well as, the service provisioning based on the classification and allocation of suitable computational resources remains a challenge. Osmotic Computing (OC), a new promising paradigm that allows the service migrations ensuring beneficial resource utilization within Cloud, Edge, and Fog Computing environments, was introduced as a potential solution to these issues. Driven by the needs of complex management mitigation, greater agility, flexibility and scalability, this paper aims to propose an innovative OC ecosystem leveraging Functions-as-a-Service (FaaS); there is also introduced the concept of hybrid architectural style combining both microservices and serverless architectures. Furthermore, to support the FaaS-based OC ecosystem, an osmotic flow model for video surveillance in smart cities is presented. To validate the functionality and assess the performance and to further improve the understanding of the usability of the OC flow in real-world applications, several experiments have been carried out.


Osmotic Computing MELs Serverless FaaS Microservice architecture IoT Video surveillance 


  1. 1.
    Serverless or microservices - which is better?
  2. 2.
    Alam, K.M., Saini, M.K., El-Saddik, A.: Workload model based dynamic adaptation of social internet of vehicles. Sensors 15, 23262–23285 (2015)CrossRefGoogle Scholar
  3. 3.
    Buzachis, A., Bernava, G.M., Busa, M., Pioggia, G., Villari, M.: Towards the basic principles of osmotic computing: a closed-loop gamified cognitive rehabilitation flow model. In: 2018 IEEE 4th International Conference on Collaboration and Internet Computing (CIC), pp. 446–452, October 2018.
  4. 4.
    Fox, G., Ishakian, V., Muthusamy, V., Slominski, A.: Status of serverless computing and function-as-a-service (FaaS) in industry and research, August 2017.
  5. 5.
    Nardelli, M., Nastic, S., Dustdar, S., Villari, M., Ranjan, R.: Osmotic flow: osmotic computing + IoT workflow. IEEE Cloud Comput. 4(2), 68–75 (2017)CrossRefGoogle Scholar
  6. 6.
    Rausch, T., Dustdar, S., Ranjan, R.: Osmotic message-oriented middleware for the internet of things. IEEE Cloud Comput. 5, 17–25 (2018)CrossRefGoogle Scholar
  7. 7.
    Sharma, V., Srinivasan, K., Jayakody, D.N.K., Rana, O., Kumar, R.: Managing service-heterogeneity using osmotic computing. ArXiv e-prints, April 2017Google Scholar
  8. 8.
    Sharma, V., You, I., Kumar, R., Kim, P.: Computational offloading for efficient trust management in pervasive online social networks using osmotic computing. IEEE Access (2017). Scholar
  9. 9.
    Taherizadeh, S., Stankovski, V., Grobelnik, M.: A capillary computing architecture for dynamic internet of things: orchestration of microservices from edge devices to fog and cloud providers. Sensors 18, 2938 (2018)CrossRefGoogle Scholar
  10. 10.
    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). Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.MIFT DepartmentUniversity of MessinaMessinaItaly
  2. 2.On behalf of Gruppo Nazionale Per il Calcolo Scientifico (GNCS) - INdAMRomeItaly

Personalised recommendations