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A time interval-based approach for business process fragmentation over cloud and edge resources

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Abstract

This paper presents an approach for fragmenting business processes over 2 types of complementary platforms referred to as cloud resources and edge resources. Fragmentation caters to the separate needs and requirements of business processes’ owners. Indeed, some owners prioritize the security of their fragmented processes over availability while others prioritize the reliability of their fragmented processes over performance. Despite its benefits, fragmentation raises many concerns like how to reduce communication delays between disparate fragments and how to maintain acceptable loads over all the distributed resources. To identify the necessary cloud and edge resources that would accommodate fragmented business processes, the approach resorts to Allen’s time algebra allowing to simultaneously reason over both resources’ availability-time intervals and processes’ use-time intervals. This reasoning covers a good range of time relations like overlaps, during, and meets, is aware of resources’ properties like limited-but-extensible, and satisfies business processes’ requirements like data freshness. The fragmentation approach, in this paper, is illustrated with a banking case-study, validated through a system developed on top of Google Colaboratory, and evaluated through a set of real experiments.

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Notes

  1. Puliafito et al. report that “the average round trip time between an Amazon Cloud server in Virginia (USA) and a device in the US Pacific Coast is 66ms; it is equal to 125ms if the end device is in Italy; and reaches 302ms when the device is in Beijing” [19].

  2. In this paper, edge and fog are considered the same.

  3. Requests for extra-time could be repeated, if deemed necessary, but not indefinitely.

  4. https://colab.research.google.com.

  5. https://bpmn.io/modeler.

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Authors and Affiliations

  1. ReDCAD, University of Sfax, Sfax, Tunisia

    Saoussen Cheikhrouhou, Rawya Mars & Slim Kallel

  2. Zayed University, Dubai, UAE

    Zakaria Maamar

Authors
  1. Saoussen Cheikhrouhou
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  2. Zakaria Maamar
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  3. Rawya Mars
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  4. Slim Kallel
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Correspondence to Slim Kallel.

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Appendices

Appendix 1

Screenshots of data, announcement strategy, and resources of the credit application use case, respectively (Figs. 4, 5, 6).

Fig. 4
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Screenshot of data definition

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Fig. 5
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Screenshot of announcement strategy selection

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Fig. 6
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Screenshot of resource definition

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Appendix 2

Definitions of time intervals of the credit application BP’s tasks, data, and resources, respectively (Tables 9, 10, 11, 12, 13).

Table 9 Definition of tasks’ time intervals
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Table 10 Definition of data’s time intervals
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Table 11 Definition of available resources
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Table 12 Resource assignment to tasks/data using the AT announcement strategy (extensible resources)
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Table 13 Resource assignment to tasks/data using the EF announcement strategy (extensible resource)
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Appendix 3

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figure g

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Cheikhrouhou, S., Maamar, Z., Mars, R. et al. A time interval-based approach for business process fragmentation over cloud and edge resources. SOCA 16, 263–278 (2022). https://doi.org/10.1007/s11761-022-00345-5

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  • DOI: https://doi.org/10.1007/s11761-022-00345-5

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