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Towards big services: a synergy between service computing and parallel programming

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Abstract

Over the last years, cloud computing has emerged as a natural choice to host, manage, and provide various kinds of virtualized resources (e.g., software, business processes, databases, platforms, mobile and social applications, etc.) as on-demand services. This “servicelization” across various domains has produced a huge volume of data, leading to the emergence of a new service model, called big service. This latter consists of the encapsulation, abstraction and the processing of big data, allowing then to hide their complexity. However, this promising approach still lacks management facilities and tools. Indeed, due to the highly dynamic and uncertain nature of their hosting cloud environments, big services together with their accessed data need continuous management operations, so that to maintain a moderate state and high quality of their execution. In this context, frameworks for designing, composing, executing and managing big services become a major need. The purpose of this paper is to provide an understanding of the new emerging big service model from the lifecycle management phases’ point of view. We also study the role of big data frameworks and multi-cloud strategies in the provisioning of big services. A research road map on this topic will be summarized at the end of this paper.

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Notes

  1. https://www.alibabacloud.com/blog/maxcompute-2-0-evolution-of-alibabas-big-data-service_231835.

  2. https://cloud.oracle.com/opc/paas/datasheets/BDCS-Datasheet.pdf.

  3. https://hadoop.apache.org/.

  4. https://spark.apache.org/.

  5. https://storm.apache.org/.

  6. https://flink.apache.org/.

  7. http://samza.apache.org/.

  8. https://hive.apache.org/.

  9. https://incubator.apache.org/clutch/heron.html.

  10. https://www.serf.io.

  11. https://oozie.apache.org.

  12. https://airflow.apache.org/.

  13. https://kafka.apache.org/.

  14. https://samoa.incubator.apache.org.

  15. https://www.qubole.com/.

  16. https://azure.microsoft.com/en-in/services/hdinsight/.

  17. https://www.ibm.com/analytics/us/en/business/insight-cloud-services/.

  18. https://azure.microsoft.com/en-us/services/machine-learning/.

  19. https://cloud.google.com/products/ai/.

  20. https://aws.amazon.com/machine-learning/.

  21. https://developers.google.com/knowledge-graph.

  22. https://sentry.apache.org.

  23. https://ranger.apache.org

  24. http://metron.apache.org.

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Authors and Affiliations

  1. SMART Lab, Higher Institute of Management, University of Tunis, Tunis, Tunisia

    Haithem Mezni

  2. University of Jendouba, Jendouba, Tunisia

    Haithem Mezni & Mokhtar Sellami

  3. Taibah University, Madinah, Kingdom of Saudi Arabia

    Haithem Mezni

  4. RIADI Lab, ENSI Mannouba, Tunisia

    Mokhtar Sellami

  5. University of Lorraine, Nancy, France

    Sabeur Aridhi

  6. Department Computer Science, University of Tunis El Manar, Tunis, Tunisia

    Faouzi Ben Charrada

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  1. Haithem Mezni
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  2. Mokhtar Sellami
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  3. Sabeur Aridhi
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  4. Faouzi Ben Charrada
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Correspondence to Haithem Mezni.

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Mezni, H., Sellami, M., Aridhi, S. et al. Towards big services: a synergy between service computing and parallel programming. Computing 103, 2479–2519 (2021). https://doi.org/10.1007/s00607-021-00999-7

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