Santhosh Kumaran

On the Duality of Information-Centric and Activity-Centric Models of Business Processes

Most of the work in modeling business processes is activity-centric. Recently, an information-centric approach to business process modeling has emerged, where a business process is modeled as the interacting life cycles of information entities. The benefits of this approach are documented in a number of case studies. The goal of this paper is to formalize the information-centric approach and derive the relationships between the two approaches. We do this by formally defining the notion of a business entity from first principles and using this definition to derive an algorithm that generates an information-centric process model from an activity-centric model. We illustrate the two models using a real-world business process and provide an analysis of the respective strengths and weaknesses of the two modeling approaches.

Conversation support for business process integration

Business process integration and automation (BPIA) has emerged as an important aspect of the enterprise computing landscape. Intra-enterprise application integration (EAI) as well as the inter enterprise integration (B2B) are increasingly being performed in the context of business processes. The integration scenarios typically involve distributed systems that are autonomous to some degree. From the BPIA perspective, the autonomy refers to the fact that the systems being integrated have their own process choreography engines and execute internal business processes that are private to them. In the case of B2B integration, the systems being integrated are fully autonomous, while various levels of autonomy exist in systems partaking in EAI. We present a new paradigm for business process integration. Our approach is based on a conversation model that enables autonomous, distributed BPM (Business Process Management) modules to integrate and collaborate. Our conversation model supports the exchange of multiple correlated messages with arbitrary sequencing constraints and covers the formatting of messages that are to be sent as well as the parsing of the messages that have been received. The crux of our conversation model is the notion of a conversation policy, which is a machine-readable specification of a pattern of message exchange in a conversation. Our model supports nesting and composition of conversation policies to provide a dynamic, adaptable, incremental, open-ended, and extensible mechanism for business process integration. We discuss the current implementation of this conversation model and early experience in applying the model to solve customer problems. The implementation utilizes distributed object technology.

From business process model to consistent implementation: a case for formal verification methods

Todays business applications and their underlying process models are becoming more and more complicated, making the implementation of these processes an increasingly challenging task. On the one hand, tools and methods exist to describe the business processes. On the other hand, different tools and method exist to describe the IT artifacts implementing them. But a significant gap exists between the two. To overcome this gap, new methodologies are sought. In this paper we discuss a pattern-based modeling and mapping process. Starting from a business process model, which emphasizes the underlying structural process pattern and its associated requirements, we map this model into a corresponding IT model based on nondeterministic automata with state variables. Model checking techniques are used to automatically verify elementary requirements on a process such as the termination and reachability of states. Using an example involving coupled, repetitive activities we discuss the advantages of an iterative process of correcting and refining a model based on insights gained in the interleaved verification steps.

A-Teams: An Agent Architecture for Optimization and Decision Support

The effectiveness of an agent architecture is measured by its successful application to real problems. In this paper, we describe an agent architecture, A-Teams, that we have successfully used to develop real-world optimization and decision support applications. In an A-Team, an asynchronous team of agents shares a population of solutions and evolves an optimized set of solutions. Each agent embodies its own algorithm for creating, improving or eliminating a solution. Through sharing of the population of solutions, cooperative behavior between agents emerges and tends to result in better solutions than any one agent could produce. Since agents in an A-Team are autonomous and asynchronous, the architecture is both scalable and robust. In order to make the architecture easier to use and more widely available, we have developed an A-Team class library that provides a foundation for creating A-Team based decision-support systems.

Model-driven synthesis of SOA solutions

The current approach to the design, maintenance, and governance of service-oriented architecture (SOA) solutions has focused primarily on flow-driven assembly and orchestration of reusable service components. The practical application of this approach in creating industry solutions has been limited, because flow-driven assembly and orchestration models are too rigid and static to accommodate complex, real-world business processes. Furthermore, the approach assumes a rich, easily configured library of reusable service components when in fact the development, maintenance, and governance of these libraries is difficult. An alternative approach pioneered by the IBM Research Division, model-driven business transformation (MDBT), uses a model-driven software synthesis technology to automatically generate production-quality business service components from high-level business process models. In this paper, we present the business entity life cycle analysis (BELA) technique for MDBT-based SOA solution realization and its integration into service-oriented modeling and architecture (SOMA), the end-to-end method from IBM for SOA application and solution development. BELA shifts the process-modeling paradigm from one that is centered on activities to one that is centered on entities. BELA teams process subject-matter experts with IT and data architects to identify and specify business entities and decompose business processes. Supporting synthesis tools then automatically generate the interacting business entity service components and their associated data stores and service interface definitions. We use a large-scale project as an example demonstrating the benefits of this innovation, which include an estimated 40 percent project cost reduction and an estimated 20 percent reduction in cycle time when compared with conventional SOA approaches.

A model-driven transformation method

Model-driven architectures (MDA) separate the business or application logic from the underlying platform technology and represent this logic with precise semantic models. These models are supposed to span the entire life cycle of a software system and ease the software production and maintenance tasks. Consequently, tools will be needed that support these tasks. In this paper, we present a method that implements model-driven transformations between particular platform-independent (business view) and platform-specific (IT architectural) models. On the business level, we focus on business view models expressed in ADF or UML2, whereas on the IT architecture side we focus on service-oriented architectures with Web service interfaces and processes specified in business process protocol languages such as BPEL4WS.

Cooperative Multiobjective Decision Support for the Paper Industry

We built and deployed a decision-support system for scheduling paper manufacturing and distribution, an extremely complex task with multiple stages of production and strong interaction between stages. In contrast to earlier approaches, our system considers multiple scheduling objectives and multiple stages of production and distribution simultaneously using multiple evaluation criteria. Our system functions as an intelligent assistant to the schedulers and generates multiple good scheduling alternatives using a portfolio of algorithms and direct human-expert input. The successful deployment of our system at several paper mills in North America has resulted insignificant savings, greater customer satisfaction, and improved business processes.

Using a model-driven transformational approach and service-oriented architecture for service delivery management

IT (information technology) service providers often assume that efficient and effective service delivery can be achieved by migrating to a standard set of tools. This assumption is true only if the service provider has monolithic control over the scope and architecture of the customer environment. The trend, however, is toward selective outsourcing, customer control over the architecture of IT solutions, and retention of legacy tools. Target environments are extremely heterogeneous, and the ability of the service provider to control them is diminishing. Consequently, there is a need for a new approach to IT service workflow automation and a new generation of service-delivery management systems that support heterogeneity and collaboration. This paper introduces a new approach to automating complex and variable workflows, applies this approach to IT service delivery management (SDM), presents an SDM architecture based on this approach, and discusses an SDM implementation driven by this architecture. Our implementation architecture leverages service-oriented architecture (SOA) principles by defining loosely coupled service components and a service fulfillment pattern that dynamically integrates them. We discuss the modeling of performance metrics for service delivery and describe how the monitoring and management of key performance indicators (KPIs) are supported as an integral part of our SDM platform.

An intelligent event adaptation mechanism for business performance monitoring

Business performance monitoring is to observe, analyze, and possibly control the execution of business operations. Often in the information technology implementation environment, dynamic events are generated to indicate the states of the business processes. These isolated and heterogeneous low-level events create needs for adaptation and standardization, before the events can be handled by a central mediation engine, which fillers, sorts and correlates events into key performance indicators relating to business goals. In this paper, we propose an intelligent event adaptation mechanism for capturing, analyzing, enriching and transforming application-dependent IT-level events into a standard event format called the common base event. The resulting event adapter can capture and process low-level events and forward only business related events to the central mediation engine. We select the SAP system as a reference application, and illustrate the configuration issues between the application and its adapter. The architecture and functionality of the proposed event adaptation mechanism are explained with practical industry problems and scenarios

Scheduling Solutions for the Paper Industry

This paper describes a decision support system for paper production scheduling. This is the first system to provide an integrated solution to paper production scheduling and to consider interactions between different stages of the manufacturing and distribution process. Using a multicriteria optimization approach, the system generates multiple enterprisewide schedules to reveal tradeoffs between the multiple, often competing, objectives. The large portfolio of algorithms used by the system is embedded in an agent-based decision support framework, called Asynchronous Team (A-Team). Successful implementations of the system in several paper mills in North America have resulted in significant savings and improved customer satisfaction.