Optimal business process deployment cost in cloud resources

Halima, Rania Ben; Kallel, Slim; Nacer, Mehdi Ahmed; Gaaloul, Walid

doi:10.1007/s11227-020-03316-9

Cited by 7 publications

(5 citation statements)

References 52 publications

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“…With the aim of validating the objective function's values (cost) of our approach, we relied on our previous work [35] that extends CloudSim to support AWS pricing strategies and the simulation of a time-constrained BP deployed in cloud resources. Thereby, we show through the experiments that the difference between the cost value of our approach and the cost computed using CloudSim simulator is "limited".…”

Section: Simulation Resultsmentioning

confidence: 99%

Toward a correct and optimal time-aware cloud resource allocation to business processes

Halima

Kallel

Gaaloul

et al. 2020

Future Generation Computer Systems

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Section: Simulation Resultsmentioning

confidence: 99%

Toward a correct and optimal time-aware cloud resource allocation to business processes

Halima

Kallel

Gaaloul

et al. 2020

Future Generation Computer Systems

Self Cite

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“…In addition, in Rekik et al (2016), the authors propose a linear programming (LP) to determine an adjustable BP for using optimal methods for a cloud federation. In Ben Halima et al (2020), an approach is presented to assist BP designers in finding an optimal assignment or scheduling plan based on different pricing strategies using LP models with an objective function under a set of constraints for cloud resources. In Labba et al (2017), they attempts to optimize resource allocation for deploying BPs in the cloud in terms of final deployment costs.…”

Section: Related Workmentioning

confidence: 99%

Adaptive IWD-based algorithm for deployment of business processes into cloud federations

Nasiriasayesh

Yari

Nazemi

2021

IJPCC

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Purpose The concept of business process (BP) as a service is a new solution in enterprises for the purpose of using specific BPs. BPs represent combinations of software services that must be properly executed by the resources provided by a company’s information technology infrastructure. As the policy requirements are different in each enterprise, processes are constantly evolving and demanding new resources in terms of computation and storage. To support more agility and flexibility, it is common today for enterprises to outsource their processes to clouds and, more recently, to cloud federation environment. Ensuring the optimal allocation of cloud resources to process service during the execution of workflows in accordance with user policy requirements is a major concern. Given the diversity of resources available in a cloud federation environment and the ongoing process changes required based on policies, reallocating cloud resources for service processing may lead to high computational costs and increased overheads in communication costs. Design/methodology/approach This paper presents a new adaptive resource allocation approach that uses a novel algorithm extending the natural-based intelligent water drops (IWD) algorithm that optimizes the resource allocation of workflows on the cloud federation which can estimate and optimize final deployment costs. The proposed algorithm is implemented and embedded within the WokflowSim simulation toolkit and tested in different simulated cloud environments with different workflow models. Findings The algorithm showed noticeable enhancements over the classical workflow deployment algorithms taking into account the challenges of data transfer. This paper made a comparison between the proposed IWD-based workflow deployment (IWFD) algorithm with other proposed algorithms. IWFD presented considerable improvements in the makespan, cost and data transfer in most situations in the cloud federation environment. Originality/value An extension for WorkflowSim to support the implementation of BPs in a federation cloud space regarding BP policy. Optimize workflow execution performance in Federated clouds by means of IWFD algorithm.

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“…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]).…”

Section: Introductionmentioning

confidence: 99%

“…[14,15] propose an architecture to support the outsourcing of the IoT-aware BP. Furthermore, we notice, from Table 1, that several of the studied approaches [7][8][9]13,18,20,21] are limited to the cloud environment to ensure the outsourcing of the process. However, the cloud is not recommended for latency-sensitive applications, such as IoT applications (e.g., health care, smart home, and smart agriculture).…”

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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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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Optimal business process deployment cost in cloud resources

Cited by 7 publications

References 52 publications

Toward a correct and optimal time-aware cloud resource allocation to business processes

Toward a correct and optimal time-aware cloud resource allocation to business processes

Adaptive IWD-based algorithm for deployment of business processes into cloud federations

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

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