Mouna Rekik

A decision-making method for business process outsourcing to the cloud based on business motivation model and AHP

Outsourcing business processes to the cloud is among the proposed solutions to help SME to emerge in the market and enhance their added value. However, the benefits of such solution highly depend on several factors specific to the enterprise context. Hence, an enterprise needs a decision-making method to assist it in deciding whether its business plan calls for cloud computing adoption, which parts of its business process are the most profitable from outsourcing, which cloud computing model is the most suitable, ... This paper highlights the need and proposes a context-aware decision method for cloud adoption to enable enterprises to understand, self-assess, and select an appropriate cloud computing model aligned to their business context. Besides proposing an appropriate enterprise context, this paper shows how the business motivation model of an enterprise also enhances the outsourcing decision-making by taking into account the business plan and vision of the enterprise.

A Comprehensive Framework for Business Process Outsourcing to the Cloud.

The lack of a framework that provides for business process outsourcing to the cloud hinders the widespread adoption of this emerging computing environment. Unlike the multiple decision methods related to outsourcing classical applications in a cloud environment, there is no standard dealing with the outsourcing of business processes starting from the enterprise business concerns to select the appropriate business process to be outsourced, to a finer level of decision to select the business process fragments to be supported by the cloud. In this paper, we first present an end-to-end framework that addresses some of these shortages. The presented framework, entitled Business Process Outsourcing to the cloud (BPO2C), covers the outsourcing process lifecyle. Indeed, the BPO2C framework elaborates several phases pertinent to the outsourcing decision, starting from the elaboration of the enterprise business motivations to identify the implied business process in the outsourcing decision, to the identification of outsourceable process fragments to minimize the business process costs, duration and to mitigate cloud risks.

A Decision Method for Business Process Outsourcing Based on Enterprise Context

Business process outsourcing has regained further attention with the emergence of Cloud computing. In fact, enterprises can benefit from the cloud at the service (i.e., business), the platform and/or the infrastructure levels. Face to these various benefits, an enterprise that desires to outsource and/or deploy parts of its business process in the Cloud must resolve two decisional points: which part of its business process to outsource, which Cloud and which level of the Cloud environment are the most beneficial. The resolution of these decisional points must take into account several contextual factors that are specific to each enterprise. This paper presents the elements of enterprise context that influence the decision whether to outsource or not in a Cloud environment. In addition, it shows how AHP can be used to assist manager in taking their decision.

An end-to-end framework for context-aware business process outsourcing to the cloud

Abstract Highly motivated by the advantages of cloud computing, enterprises are considering outsourcing their business processes to the cloud to reduce their cost, increase their flexibility, and enhance their performance. The purpose of this paper is to propose a comprehensive end-to-end framework for business process outsourcing to the cloud, that considers the dynamic business process context. The framework comprises different methods able to efficiently take into account accurate and up-to-date business process context to identify the best process fragment to outsource and the most suitable cloud service to adopt. The optimality of the identified solutions is insured by NSGA II (Elitist Non-Dominated Sorting Genetic Algorithm) for which we proposed a set of context-based objective functions. In addition, the framework considers the business process context prior and post the outsourcing decision in order to change a decision to account for context changes. The performance of the framework is experimentally illustrated.

Specifying Business Process Outsourcing Requirements

Outsourcing enterprises’ data, business processes and applications to the Cloud is emerging as a major trend thanks to the Cloud offerings and features. Basically, enterprises expect when outsourcing to save cost, improve software and hardware performance and gain more flexibility by responding to the dynamic customers’ requirements. However, adopting the Cloud as an alternative environment for the management of the business processes leads to a radical change in the enterprise IT infrastructure. Furthermore, additional challenges may appear such as data security, vendor-lock-in and labor union rendering the outsourcing decision require a deep analysis and knowledge about the business processes context. Assisting enterprises’ experts in the business process outsourcing to the Cloud decision is the focus of this paper: it extends the BPMN 2.0 language to explicitly support the specification of outsourcing concepts, and it presents an automated approach to help decision makers identify those parts of their business process that benefit most from outsourcing to the Cloud. Using this extension helps also in identifying Cloud services considered as the most suitable to support the outsourced business process requirements.

Measurement framework for business process outsourcing to the Cloud

Face to the increasingly stringent business competition, small and medium sized enterprises strive to excel in the marketplace by adopting different strategies and solutions. Outsourcing their business processes to the Cloud has been among the most widely adopted strategies. Among others, enterprises outsource their related business process to improve their performance. However, this strategy is not without inconvenience especially when the decision is taken without being aware about the business process functional and non functional requirements. We focus in this paper on identifying the business process performance enhancement needs so to be able to identify requirements when outsourcing business process to the Cloud. This papers major contribution is the presentation of a measurement framework for SOA-based business process performance. The proposed framework allows firstly to identify essential metrics to monitor starting from an abstract business level. Then, identified metrics are monitored using our Business/Qos (BisQos) listener. The gathered data are then stored in a database for analysis purpose. The output of the framework specifies whether business process instances reveal a degradation of their performance caused by business metrics or by Qos metrics, in addition to the infrastructure properties supporting each web service execution.

Control of a wind turbine for grid fault detection in stand-alone or grid-connected modes

In this study, a wind generation is considered as a unit able to supply an isolated load or to be integrated into a network coupled with classical alternators. This generator operates without auxiliary source and participates in the production-consumption balance by adjusting the provided amplitude and frequency of the voltages, through the generation or the absorption of active and reactive powers. For a smooth transition between different operation modes, a control strategy is proposed to receive measurements and operates in grid-connected or stand-alone modes with automatic switches. The transition from first to second mode corresponds to an islanding one. In this context, an algorithm, based on surveillance of the wind power, the voltage and frequency of the grid, is suggested to detect islanding in case of defects and to participate in the grid stabilization by reducing the voltage and frequency fluctuations across the injection of active and reactive powers.

FC4CD: a new SOA-based Focused Crawler for Cloud service Discovery

In this paper, we propose a Focused Crawler for Cloud service Discovery (FC4DC). Its service oriented architecture ensures an easier modification for rapid updating and better performance. Furthermore, the proposed crawler guarantees saving the search time and a better exploitation of the provider offerings thanks to a dedicated Cloud service description ontology. We finally present some experiments to evaluate the proposed crawler and demonstrate its effectiveness and efficiency.

A Framework for Cloud Selection Based on Business Process Profile

The lack of a system that assists in the business process out-sourcing to the cloud hinders the widespread adoption of this emerging computing paradigm. To the best of our knowledge, there is no system that has tackled the business process outsourcing to the cloud issues such as selecting the activities to outsource and the cloud services to support their execution based on objective and subjective assessments of cloud services. In this paper, we propose a system tackling these issues by using previous cloud users experience for the subjective assessment. The objective assessment is based on simulations using the well-known CloudSim toolkit. The aggregation of the objective and subjective assessment allows for more reliable cloud service selection. Furthermore, we propose an optimal deployment of business process activities by proposing a novel penalty based genetic algorithm while considering business process profile.

Towards an Autonomic Outsourcing to the Cloud Decision

When enterprises decide to outsource their business processes to the Cloud, various considerations should be tackled. Indeed, the enterprises aim to reduce the business processes investment cost, to enhance their performance, and to focus on the enterprise core competency while considering security constraints. Hence, it is essential to assist enterprises to take the suitable decision by providing an appropriate decision system that specifies the activities to be outsourced as well as the Cloud resource to support them while considering the above enterprise preferences. Obviously, the outsourcing decision, when taken in a specific business process context, may be influenced by some variants that make it not suitable in another one. For instance, the business process workloads vary according to its execution period and thus the decision may require to change the Cloud resources as well as the outsourced activities to fit the new context requirements. This consideration should be taken when tackling an outsourcing decision to alleviate enterprise experts from the burden of assessing by themselves the changing business processes context and react by consequence to this change. In this paper, we present an adaptive outsourcing decision system, which provides personalized and autonomic decision-making to support the dynamic business process context when outsourced to the Cloud. The system predicts the business process context and provides accordingly appropriate decisions using the penalty based genetic algorithm.