Business Process As A Service Research Articles

Conformance-oriented Predictive Process Monitoring in BPaaS Based on Combination of Neural Networks

As a new cloud service for delivering complex business applications, Business Process as a Service (BPaaS) is another challenge faced by cloud service platforms recently. To effectively reduce the security risk caused by business process execution load in BPaaS, it is necessary to detect the non-compliant process executions (instances) from tenants in advance by checking and monitoring the conformance of the executing process instances in real-time. However, the vast majority of existing conformance checking techniques can only be applied to the process instances that have been executed completely offline and only focus on the conformance from the single control-flow perspective. We develop an extensible multi-perspective conformance measurement method to address these issues first and then investigate the predictive conformance monitoring approach by automatically constructing an online multi-perspective conformance prediction model based on deep learning techniques. In addition, to capture more decisive features in the model from both local information and long-distance dependency within an executed process instance, we propose an approach, called CNN-BiGRU, by combining Convolutional Neural Network (CNN) with a variant and enhancement of Recurrent Neural Network (RNN). Extensive experiments on two data sets demonstrate the effectiveness and efficiency of the proposed CNN-BiGRU.

Predictive BPaaS management with quantum and neural computing

AbstractWith the increasing adoption of cloud computing, the deployment and management of business processes over cloud environments have become an essential operation for most enterprises, leading to the emergence of BPaaS (Business Process as a Service) as a new cloud service model. This SaaS‐like service, like its ancestors, should be strategically distributed and managed over multiple cloud zones, while taking into account several constraints and conditions (e.g., sensitivity of BPaaS fragments, insecure and untrusted cloud zones, lack of resources, and workload changes). However, current BPaaS approaches are static, which means that they are no longer suitable to manage such enterprise‐oriented cloud service model and to deal with the uncertain and dynamic nature of cloud availability zones. To fill this gap, we adopt a predictive BPaaS management strategy by proposing a model that forecasts the next‐short time overload of cloud zones. These latter, as hosting environments for the managed BPaaS, are categorized as overloaded or underloaded, which triggers the migration of BPaaS fragments to high‐performance cloud zones. The proposed neural network prediction model (called QGA‐NN) is enhanced with a quantum genetic algorithm to optimize the prediction of cloud zones' overload. QGA‐NN is evaluated using a BPaaS placement algorithm, which we defined as a triggered management operation. Experimental results have proved the accuracy and effectiveness of our predictive approach, compared with state‐of‐the‐art solutions.

An Empirical Study on Data Flow Bugs in Business Processes

An increasing number of service-based business processes are being developed with the booming of BPaaS (Business Process as a Service) in cloud computing. The profits and performance of enterprises strongly depend on the soundness of their processes being bereft of control flow and data flow bugs. Although some work has focused on the detection of control flow bugs, few studies have comprehensively and empirically investigated data flow bugs in business processes. To this end, we report an empirical study on data flow bugs in business (BPEL) processes. Our analysis of 178 real-world BPEL processes reveals that data flow bugs are surprisingly common: 94 BPEL processes involve data flow bugs, among which redundant output is predominant. The distribution and common scenarios of data flow bugs provide a reference for BPEL process designers. We also investigate the correlation between process complexity metrics and data flow bugs. Based on the statistics of the process complexity metrics and data flow bugs in our empirical study, we present a method to select appropriate metrics as features of BPEL processes and utilize state-of-the-art supervised learning algorithms to predict data flow bugs in an unseen BPEL process. The prediction accuracies of the different classification algorithms exceed 90 percent on average when using our selected metrics.

Method towards reconstructing collaborative business processes with cloud services using evolutionary deep Q-learning

Service-oriented architecture (SOA) is a significant framework that enables intelligent information systems to offer business process-based services, namely Business Process as a Service (BPaaS). Cloud service-based business model reconstruction within and across enterprises has become an important issue to obtain competitive advantages. Finding appropriate service component is a critical phase in enterprise collaboration, to improve the quality and correlations among collaborative service-providers. Existed methods for business processes reconstruction have not systematically and fully considered the quality correlations in finer-grain, i.e. task-level or activity-level, and temporal performance in a process model optimization. Moreover, the existed approaches might fail to work in an uncertain cloud environment where the quality parameters are unknown in advance. Q-learning has proven its worth in an uncertain cloud environment. However, advances in Q-learning are challenges to leverage in collaborative business process reconstruction. The reconstruction algorithms based on Q-learning suffered from the two core drawbacks: lack of effective exploration and extremely slow convergence property. A hybrid Evolutionary Deep Q-Learning-based BPaaS reconstruction algorithm, named as EDQL-BPR, is proposed by leveraging Particle Swarm Optimization to improve Deep Q-Learning algorithm for systematically optimizing collaborative business processes reconstruction. In order to verify the effectiveness of the proposed algorithm, an annotated transition system has been developed supporting for all possible behaviors state convention from heterogeneous initial states to the target with several collaborative information at activity level, and encoding annotated BP representation matrix automatically. Then, an autonomous three-layer framework has been built to facilitate business process discovery and service reconstruction. In this framework, our optimal collaborative services composition is treated as a multi-objective constraint optimization problem via Evolutionary Deep Q-learning with updated strategy of Q-value, and each annotated component launch a service discovery by service agent. Extensive evaluation results show that EDQL-BPR can outperform several representative business process reconstructions in terms of model optimal convergence, QoS optimality, effectiveness and efficiency under heterogeneous service selection workloads in an uncertain Cloud environment.

Toward Reconfiguration of BPaaS Based on SaaS Services using Clustering and Boolean Satisfiability

Business Process as a Service (BPaaS) met a considerable proliferation and an exponential emergence as a new Cloud service for delivering complex and complete business applications. To better position themselves in the harshly competitive Cloud services market, BPaaS providers should offer to their clients, flexible services responding both to their functional and non-functional requirements. This article proposes a Reconfigurable BPaaS-based SaaS services Federation system (RBPF) allowing flexible support of user requirements changes. RBPF proposes to end-users minimal on the fly compositions whenever a reconfiguration is required. To do so, Boolean Satisfiability Problem-based algorithms are adopted to select the minimal reconfiguration. To reduce composition candidates research space, we propose new algorithms to group BPaaS services that are likely to compose within the same cluster. The clustering process leverages semantic Linked Open Data similarity measures to match service capabilities and identify composable ones.

A Correctness Checking Approach for Collaborative Business Processes in the Cloud

With the increasing popularity of cloud computing, especially the emergence of Business Process as a Service (BPaaS), more and more enterprises construct their process collaborations based on BPaaS services. Indeed, the collaborative business process built by BPaaS services can be seen as a complex system, as it covers multiple business processes (i.e., BPaaS services) and they act independently. Since business processes corresponding to BPaaS services are usually provided by different cloud service providers, and their interactions are unforeseen in advance, in actual execution, some behavioral anomalies (e.g., deadlocks) may occur. To this end, based on BPaaS services, we propose an approach to build process collaborations in the cloud. In this approach, we first model collaborative business processes using open nets. Then, we check their correctness based on stubborn sets. Finally, in case they are partially correct, we generate reliable paths for the coordination execution between business processes. Our approach is implemented in the PIPE (an open tool for Petri nets) and evaluated on actual cases that show its effectiveness and efficiency.

Blockchain and Business Model Innovation: Designing a P2P Mortgage Lending System

This paper explores P2P lending in the context of mortgage financing. While P2P lending has gained considerable traction in the consumer loan segment, it remains absent for the economically and socially important mortgage sector. Following a design research approach (most specifically, Action Design Research), the paper defines a series of questions about how a sound business model would make P2P mortgage lending feasible from a technical and business perspective. In order to provide an initial answer, a model is developed by providing a theoretical explanation and a partial formalization in Business Process Modelling and Notation (BPMN). The business model introduces artificial intelligence, blockchain/smart contracts and Business-Process-as-a-Service (BPaaS) as its main features. A preliminary evaluation of the model’s feasibility and effectiveness is offered, as a way of providing an initial prescriptive theory on a subject (P2P mortgage lending) where academic studies and business applications are basically absent.

Transactional Behavior Verification in Business Process as a Service Configuration

Business Process as a Service (BPaaS) is an emerging type of cloud service that offers configurable and executable business processes to clients over the Internet. As BPaaS is still in early years of research, many open issues remain. Managing the configuration of BPaaS builds on areas such as software product lines and configurable business processes. The problem has concerns to consider from several perspectives, such as the different types of variable features, constraints between configuration options, and satisfying the requirements provided by the client. In our approach, we use temporal logic templates to elicit transactional requirements from clients that the configured service must adhere to. For formalizing constraints over configuration, feature models are used. To manage all these concerns during BPaaS configuration, we develop a structured process that applies formal methods while directing clients through specifying transactional requirements and selecting configurable features. The Binary Decision Diagram (BDD) analysis is then used to verify that the selected configurable features do not violate any constraints. Finally, model checking is applied to verify the configured service against the transactional requirement set. We demonstrate the feasibility of our approach with several validation scenarios and performance evaluations.

Innovating Managed Services Business Models

Objective: Business Model Innovation approaches in service business model context are not adequately studied in the extant literature and there is a clear need for extension of different business model typologies for innovating service business models. Principal aim of this study is to explore how service business model archetypes can be explained as a business model representation such as Business Model Canvas, particularly what the term managed services really mean. Also, it is intended to add clarity to current business model innovation approaches in providing managed services, especially business process services in a service value chain. This will prompt further research to address related implications of networked business model setup and information technology as an enabler in managed services context. Methods/Statistical Analysis: Established framework of Business Model Canvas from extant literature and recent trends in business model representations that cover digitally enabled service business models are compared and contrasted. In line with service dominant logic, approaches for management and optimization of key resources and key activities are used as basis of stacking up different service business model archetypes. Service value chain and network business model implications are emphasized for further differentiating the innovation approaches in managed services business models. Findings: Among various business model design tools and representations, service business models can be better represented as a business model canvas with special emphasis on how key resources and key activities are managed and optimized in a service value chain. Digital enablement with the use of IT and/or cloud infrastructure shall act as accelerators for effective business model innovation in service context. Service business models shall be categorized as a stack of service offerings such as outsourced services, resource outsourcing, professional services, BPO/ITeS, managed services and Business Process As A service (BPaaS). services currently mean to only manage IT services but there is new paradigm of Managed Business Services which is emerging. Applications/Improvements: Suggested findings of this paper and the identification of broad types of service offerings, which clearly differentiate managed services from other service models, can be applied in practice. This approach shall bring in more consensuses about understanding of managed services business models among practitioners and researchers.

Universal Artifacts

In most BPM systems (a.k.a. workflow systems), the data for process execution is scattered across databases for enterprise, auxiliary local data stores within the BPM systems, and even file systems (e.g., specification of process models). The interleaving nature of data management and BP execution and the lack of a coherent conceptual data model for all data needed for execution make it hard for (1) providing Business-Process-as-a-Service (BPaaS) and (2) effective support for collaboration between business processes. The primary reason is that an enormous effort is required for maintaining both the engines and the data for the client applications. In particular, different modeling languages and different BPM systems make process interoperation one of the toughest challenges. In this article, we formulate a concept of a “universal artifact,” which extends artifact-centric models by capturing all needed data for a process instance throughout its execution. A framework called SeGA based on universal artifacts is developed to support separation of data and BP execution, a key principle for BPM systems. We demonstrate in this article that SeGA is versatile enough to fully facilitate not only executions of individual processes (to support BPaaS) but also various collaboration models. Moreover, SeGA reduces the complexity in runtime management including runtime querying, constraints enforcement, and dynamic modification upon collaboration across possibly different BPM systems.

Evolution of distributed monitoring for scalable business process management in cloud-based databases

Embodying business process as a service (BPaaS) in cloud computing has been actively investigated by many research studies. There are many proposals to establish the scalable workflows, for instance, by adopting the multiple instances of workflow execute engine (WEE). However, it is difficult to track exactly the states of individual instances of the workflow running across multiple engines globally, by only applying the multiple WEE. It is necessary to implement an independent monitoring function from outside. This study considers making this monitoring function scalable in accordance with increasing the number of WEE. When designing the monitoring function and the maintenance protocol, the following important factors have been considered. First, to deliver the meta-data such as definitions of business processes among WEE for sharing. The second, to deliver the event instances asynchronously, by compensating inconsistent status for recoverable events. This study proposes architecture and a set of maintenance protocols to realise the scalable workflow management. It shows the critical requirements and selects a reasonable approach through qualitative evaluations.

Security-aware Business Process as a Service by hiding provenance

We adress in this paper the security issues that arise when outsourcing business processes in the BPaaS (Business Process as a Service). In particular when sharing and reusing process fragments coming from different organizations for faster and easier development of process-based applications (PBA). The goal is twofold, to preserve the process fragment provenance, i.e., the companies's business activities which provide the reused fragments in order to avoid the competition, and to guarantee the end-to-end availability of PBA to fragment's consumers. We formally define the problem, and offer an efficient anonymization-based protocol. Experiments have been conducted to show the effectiveness of the proposed solution.

A semantic framework for configurable business process as a service in the cloud

With the advent of Cloud Computing, new opportunities for Business Process Outsourcing services have emerged. Business Process as a Service (BPaaS), a new cloud service model, has recently gained a great importance for outsourcing cloud-based business processes constructed for multi-tenancy. In such a multi-tenant environment, using configurable business process models enables the sharing of a reference process among different tenants that can be customized according to specific needs. With a large choice of configurable process modeling languages, different providers may deliver configurable processes with common functionalities but different representations which makes the process discovery and configuration a manual tedious task. This in turn creates cloud silos and vendors lock-in with non-reusable configurable BPaaS models. Therefore, with the aim of enabling the interoperability between multiple BPaaS providers, we propose in this paper a semantic framework for BPaaS configurable models. Taking advantage of Semantic Web technologies and data mining techniques, our framework allows for (1) an ontology-based high level abstract representation of BPaaS configurable models enriched with configuration guidelines and (2) an automated approach for extracting the configuration guidelines from existing process repositories. To show the feasibility and effectiveness of our approach, we extend Signavio with our semantic framework and conduct experiments on a dataset from SAP reference model.

Benefits and Challenges for Business Process Management in the Cloud

Business processes are not only variable they are as well dynamic. A key benefit of Business Process Management (BPM) is the ability to adjust business processes accordingly in response to changing market requirements. In parallel to BPM, enterprise cloud computing technology has emerged to provide a more cost effective solution to businesses and services while making use of inexpensive computing solutions, which combines pervasive, internet, and virtualization technologies (). Despite the slow start, the business benefits of cloud computing are as such that the transition of BPM to the cloud is now underway. Cloud services refer to the operation of a virtualized, automated, and service-oriented IT landscape allowing the flexible provision and usage-based invoicing of resources, services, and applications via a network or the internet. The generic term “X-as-a-Service” summarize the business models delivering almost everything as a service. BPM in the cloud is often regarded as a SaaS application. More recently, BPM is being regarded as a PaaS as it facilitates the creation and deployment of applications, in this case business process solutions. The PaaS landscape is the least developed of the four cloud based software delivery models previously discussed. PaaS vendors, such as IBM, Oracle, and Microsoft delivered an application platform with managed cloud infrastructure services however, more recently the PaaS market has begun to evolve to include other middleware capabilities including process management. BPM PaaS is the delivery of BPM technology as a service via a cloud service provider. For the classification as a PaaS a BPM suite requires the following capabilities: the architecture should be multi-tenant, hosting should be off premise and it should offer elasticity and metering by use capabilities. When we refer to BPM in the cloud, what we are really referring to is a combination of BPM PaaS and BPaaS (Business Process as a Service). Business Process as a Service (BPaaS) is a set of pre-defined business processes that allows the execution of customized business processes in the cloud. BPaaS is a complete pre-integrated BPM platform hosted in the cloud and delivered as a service, for the development and execution of general-purpose business process application. Although such a service harbors an economic potential there are remaining questions: Can an individual and company-specific business process supported by a standardized cloud solution, or should we protect process creativity and competitive differentiation by allowing the company to design the processes individually and solely support basic data flows and structures? Does it make sense to take a software solution “out of the box” that handles both data and process in a cloud environment, or would this hinder the creativity of business (process) development leading to a lower quality of processes and consequently to a decrease in the competitive positioning of a company? How to manage the inherent compliance and security topic. Within a completely integrated business application system, all required security aspects can be implemented as a safeguarding with just enough money. Within the cloud, however, advanced standards and identity prove is required to monitor and measure information exchange across the federation. Thereby there seems to be no need for developing new protocols, but a standardized way to collect and evaluate the collected information.

Benefits and Challenges for BPM in the Cloud

Business processes are not only variable, they are dynamic as well. A key benefit of BPM is the ability to adjust processes accordingly in response to changing market requirements. In parallel to BPM, enterprise cloud computing technology has emerged to provide a more cost effective solution to businesses and services while making use of inexpensive computing solutions, which combines pervasive, internet, and virtualization technologies (). Despite the slow start the business benefits of cloud computing are as such that the transition of BPM to the cloud is now underway. Cloud services refer to the operation of a virtualized, automated, and service-oriented IT landscape that allows the flexible provision and usage-based invoicing of resources, services, and applications via a network or the Internet. The generic term “X-as-a-Service” summarized the business models delivering almost everything as a service. BPM in the cloud is often regarded as a SaaS application. More recently, BPM is being regarded as a PaaS as it facilitates the creation and deployment of applications, in this case business process solutions. The PaaS landscape is the least developed of the four cloud based software delivery models previously discussed. PaaS vendors, such as IBM, Oracle, Microsoft delivered an application platform with managed cloud infrastructure services however more recently the PaaS market has begun to evolve to include other middleware capabilities including process management. BPM PaaS is the delivery of BPM technology as a service via a cloud service provider. In order to be classified as a PaaS a BPM suite requires the following capabilities: the architecture should be multi-tenant, it should be hosted off premise and it should offer elasticity and metering by use capabilities. When we refer to BPM in the cloud what we are really referring to is a combination of BPM PaaS and BPaaS (Business Process as a Service). Business Process as a Service (BPaaS) is a set of pre-defined business processes that allows the execution of customized business processes in the cloud. BPaaS is a complete pre-integrated BPM platform hosted in the cloud and delivered as a service, for the development and execution of general-purpose business process application. Although such a service harbors an economic potential, questions that need to be answered are as follows: Can an individual and company-specific business process supported by a standardized cloud solution, or should we protect process creativity and competitive differentiation by allowing the company to design the processes individually and solely support basic data flows and structures? Does it make sense to take a software solution “out of the box” that handles both data and process in a cloud environment, or would this hinder the creativity of business (process) development leading to a lower quality of processes and consequently to a decrease in the competitive positioning of a company? How to manage the inherent compliance and security topic. Within a completely integrated business application system, all required security aspects can be implemented as safeguards with just enough money. Within the cloud, however, advanced standards and identity prove is required to monitor and measure information exchange across the federation. Thereby there seems to be no need for developing new protocols, but a standardized way to collect and evaluate the collected information.

Emerging Paradigms and Areas for Expansion

Cloud computing was born from the opportunity to open major distributed datacenters to end users to provide on-demand services, ranging from infrastructure as a service (IaaS) to software as a service (SaaS). The new pay-per-use business model is so appealing that we're entering an everything-as-aservice (EaaS) era, extending the approach beyond existing borders-such as hardware-as-a-service (HaaS) and business-process-as-a-service (BPaaS)- to other areas and dimensions (robot-as-a-service, sensor-as-a-service, and so on). The cloud is like the Borg from Star Trek, making all resistance futile and assimilating all existing technologies and services. Emerging paradigms and technologies will have a major impact on society and industry. We plan to cover these paradigms in the “Cloud and Adjacent Technology Trends” area as well as provide a longterm futuristic vision of how the cloud will look and the new opportunities it will offer.