An Automated Approach for Assisting the Design of Configurable Process Models

Assy, Nour; Chân, Nguyêñ Ngoc; Gaaloul, Walid

doi:10.1109/tsc.2015.2477815

Cited by 28 publications

(18 citation statements)

References 26 publications

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“…The author of [9] uses trace-clustering method for configurable process model discovery from collection of event logs. In [10], the author discovers configurable process fragments to avoid complex and large models. The author of [14] presents an approach using process mining and analysis techniques to merge two business process models into a single model for further process optimization.…”

Section: Configurable Process Model Discovery Workmentioning

confidence: 99%

“…For that reason, configurable process model discovery is used as an alternative for reusable process design. In this context, several ASTESJ ISSN: 2415-6698 works have proposed approaches for configurable process discovery [8,9,10]. However, existing works discover the controlflow as the main process perspective without considering other process perspectives like data and resources.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Configurable Process Model: Discovery Approach from Event Logs

Sikal¹,

Sbai²,

Kjiri³

2020

Adv. sci. technol. eng. syst. j.

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In the domain of business process management, the configurable process model is widely used to optimize time and cost of business process models design, which is known as the concept of "reuse". Using process mining techniques for process model discovery helps to provide a better view on processes and improve quality of models. The majority of existing configurable model discovery approaches work intensively on control flow discovery as main process perspective without considering other perspectives such as resources and data, and do not propose a detailed discovery of variability elements. In addition, the configurable process model creation is generally done by merging variant models not directly from event logs, which is not the optimal way to get a reliable configurable process model. This paper presents an overview of new multi-perspective variability discovery approach. The approach respects the variability of different process perspectives and allows users to create a configurable process model directly from event logs.

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Section: Configurable Process Model Discovery Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Configurable Process Model: Discovery Approach from Event Logs

Sikal¹,

Sbai²,

Kjiri³

2020

Adv. sci. technol. eng. syst. j.

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“…For each deployment request, the proposed heuristic chooses a VNF graph that has the minimum overall data rate requirement among all possible VNF graphs available for that request. There are automated approaches as well, such as in [16,47], to assist the design of configurable service models, which can be applied to SFC architecture.…”

Section: Fig 3 Nfv Architecture Proposed By Etsimentioning

confidence: 99%

Optimal virtual network function placement in multi-cloud service function chaining architecture

Bhamare

Samaka

Erbad

et al. 2017

Computer Communications

192

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Service Function Chaining (SFC) is the problem of deploying various network service instances over geographically distributed data centers and providing inter-connectivity among them. The goal is to enable the network traffic to flow smoothly through the underlying network, resulting in an optimal quality of experience to the end-users. Proper chaining of network functions leads to optimal utilization of distributed resources. This has been a de-facto model in the telecom industry with network functions deployed over underlying hardware. Though this model has served the telecom industry well so far, it has been adapted mostly to suit the static behavior of network services and service demands due to the deployment of the services directly over physical resources. This results in network ossification with larger delays to the end-users, especially with the data-centric model in which the computational resources are moving closer to end users. A novel networking paradigm, Network Function Virtualization (NFV), meets the user demands dynamically and reduces operational expenses (OpEx) and capital expenditures (CapEx), by implementing network functions in the software layer known as virtual network functions (VNFs). VNFs are then interconnected to form a complete end-toend service, also known as service function chains (SFCs). In this work, we study the problem of deploying service function chains over network function virtualized architecture. Specifically, we study virtual network function placement problem for the optimal SFC formation across geographically distributed clouds. We set up the problem of minimizing inter-cloud traffic and response time in a multi-cloud scenario as an ILP optimization problem, along with important constraints such as total deployment costs and service level agreements (SLAs). We consider link delays and computational delays in our model. The link queues are modeled as M/D/1 (single server/Poisson arrival/deterministic service times) and server queues as M/M/1 (single server/Poisson arrival/exponential service times) based on the statistical analysis. In addition, we present a novel affinity-based approach (ABA) to solve the problem for larger networks. We provide a performance comparison between the proposed heuristic and simple greedy approach (SGA) used in the state-of-the-art systems. Greedy approach has already been widely studied in the literature for the VM placement problem. Especially we compare our proposed heuristic with a greedy approach using first-fit decreasing (FFD) method. By observing the results, we conclude that the affinity-based approach for placing the service functions in the network produces better results compared against the simple greedy (FFD) approach in terms of both, total delays and total resource cost. We observe that with a little compromise (gap of less than 10% of the optimal) in the solution quality (total delays and cost), affinity-based heuristic can solve the larger problem more quickly than ILP.

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“…These approaches permit redundancies to be eliminated by representing variant commonalities only once (Ayora et al, 2012) thus providing a global view of the business process variants (Assy et al, 2015). It also fosters model reuse, i.e., parts of the model can be shared among multiple variants and comparison (Buijs et al, 2013).…”

Section: Configuring Process Variants Through Semantic Reasoning In Smentioning

confidence: 99%

Configuring Process Variants Through Semantic Reasoning in Systems Engineering

Detro¹,

Portela²,

Rocha³

et al. 2017

INSIGHT

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When dealing with processes, engineering systems need to be able to deal with the existence of many versions of the same process, known as variants. Each process variant aims to represent a specific business context but, due to some differences in the activities, resources, and control flow, they may differ in their logic. As result, the concept of a customizable process model has emerged. A process model can be customized by representing the process family in one single model deriving a variant through transformations in this single model. However, the process customization is not a trivial‐task. It must be ensured that the variant is correct. Besides, the resulting variant must respect all requirements related to the application context and internal and external regulations, among others. In addition, recommendations and guidance should be provided during the customization. In this context, this research aims to propose a framework for customizing variants according to the user's requirements. The customization is achieved by reasoning in an ontology based on the rules for selecting a variant, in the internal/external regulations, and on expert knowledge.

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An Automated Approach for Assisting the Design of Configurable Process Models

Cited by 28 publications

References 26 publications

Configurable Process Model: Discovery Approach from Event Logs

Configurable Process Model: Discovery Approach from Event Logs

Optimal virtual network function placement in multi-cloud service function chaining architecture

Configuring Process Variants Through Semantic Reasoning in Systems Engineering

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