A Multi-Criteria Decision Making Approach for Cloud-Fog Coordination

Yahya, Fadwa; Maamar, Zakaria; Boukadi, Khouloud

doi:10.1007/978-3-030-44041-1_99

Cited by 6 publications

(12 citation statements)

References 10 publications

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“…Table 8. Comparison between expert's expected results and the obtained ones for the outsourcing of an IoRT-aware BP using the approach in [16]. During this evaluation, we notice that the precision value reaches 0.75%, and the recall is equal to 0.51%, while the F-score estimates 0.60% (see Table 9).…”

Section: Validation and Robustnessmentioning

confidence: 82%

“…This section is dedicated to appreciating the validation and robustness of the proposed IoRT-aware BP outsourcing approach based on the ELECTRE IS method. Therefore, to perform this goal, we choose to compare our approach regarding the outsourcing method published in [16]. In their proposal, the authors took into account a set of six criteria, which are frequency, sensitivity, freshness, time, volume, and criticality, to perform the outsourcing of a goal of a thing to the fog and cloud (see Table 7).…”

Section: Validation and Robustnessmentioning

confidence: 99%

“…Throughout this section, we intend to compare the results of our approach based on the ELECTRE IS method to the proposal in [16]. Therefore, we applied their approach to the agriculture scenario presented above (see Figure 2), which constitutes a set of tasks.…”

Section: Validation and Robustnessmentioning

confidence: 99%

“…Our extensive literature exercise revealed that most of the existing approaches deal mainly with the decision-making of traditional BPs, such as [7][8][9][10][11][12][13]. Some recent works have addressed the decision-making of the BPs that embedded only the IoT technology (e.g., [14][15][16]). More research on the outsourcing of IoRT-aware BPs, on the other hand, is required.…”

Section: Introductionmentioning

confidence: 99%

“…We also notice that there is a lack of approaches that deal with the MCDM methods, despite their ability to decide on a set of alternatives according to a set of criteria. Moreover, we notice from this table that in most cases, the approaches that deal with the MCDM methods [9,15,16] do not take into account the weight generation method to automatically generate weights.…”

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confidence: 99%

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Decision-Making Approach for an IoRT-Aware Business Process Outsourcing

Fattouch

Lahmar

Rekik

et al. 2022

Digital

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In the context of Industry 4.0, IoRT-aware BPs represent an attractive paradigm that aims to automate the classic business process (BP) using the internet of robotics things (IoRT). Nonetheless, the execution of these processes within the enterprises may be costly due to the consumed resources, recruitment cost, etc. To bridge these gaps, the business process outsourcing (BPO) strategy can be applied to outsource partially or totally a process to external service suppliers. Despite the various advantages of BPO, it is not a trivial task for enterprises to determine which part of the process should be outsourced and which environment would be selected to deploy it. This paper deals with the decision-making outsourcing of an IoRT-aware BP to the fog and/or cloud environments. The fog environment includes devices at the edge of the network which will ensure the latency requirements of some latency-sensitive applications. However, relying on cloud, the availability and computational requirements of applications can be met. Toward these objectives, we realized an in-depth analysis of the enterprise requirements, where we identified a set of relevant criteria that may impact the outsourcing decision. Then, we applied the method based on the removal effects of criteria (MEREC) to automatically generate the weights of the identified criteria. Using these weights, we performed the selection of the suitable execution environment by using the ELECTRE IS method. As an approach evaluation, we sought help from an expert to estimate the precision, recall, and F-score of our approach. The obtained results show that our approach is the most similar to the expert result, and it has acceptable values.

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Section: Validation and Robustnessmentioning

confidence: 82%

Section: Validation and Robustnessmentioning

confidence: 99%

Section: Validation and Robustnessmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Decision-Making Approach for an IoRT-Aware Business Process Outsourcing

Fattouch

Lahmar

Rekik

et al. 2022

Digital

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An IoT Application Business-Model on Top of Cloud and Fog Nodes

Maamar

Al-Khafajiy

Dohan

2021

Advanced Information Networking and Applications

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This paper discusses the design of a business model dedicated for IoT applications that would be deployed on top of cloud and fog resources. This business model features 2 constructs, flow (specialized into data and collaboration) and placement (specialized into processing and storage). On the one hand, the flow construct is about who sends what and to whom, who collaborates with whom, and what restrictions exist on what to send, to whom to send, and with whom to collaborate. On the other hand, the placement construct is about what and how to fragment, where to store, and what restrictions exist on what and how to fragment, and where to store. The paper also discusses the development of a system built-upon a deep learning model that recommends how the different flows and placements should be formed. These recommendations consider the technical capabilities of cloud and fog resources as well as the networking topology connecting these resources to things.

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