Coping with Exceptions in Agent-Based Workflow Enactments

Exception handling in workflow management systems (WFMSs) is a very important problem since it is not possible to specify all possible outcomes and alternatives. Effective reuse of existing exception handlers can greatly help in dealing with workflow exceptions. On the other hand, cooperative support for user-driven resolution of unexpected exceptions and workflow evolution at runtime is vital for an adaptive WFMS. We have developed ADOME-WFMS via a meta-modeling approach as a comprehensive framework in which the problem of workflow exception handling can be adequately addressed. In this chapter, we present an overview of exception handling in ADOME-WFMS with procedures for supporting the following: reuse of exception handlers, thorough and automated resolution of expected exceptions, effective management of Problem Solving Agents, cooperative exception handling, user-driven computer supported resolution of unexpected exceptions, and workflow evolution.

This paper proposes a novel architectural framework handling effective unexpected exceptions in workflow management systems (WfMS). Effective unexpected exceptions are events for which the organizations lack handling strategies. Unstructured human interventions are necessary to overcome these situations, but clash with the type of model control currently exercised by WfMS. The proposed framework uses the notion of map guidance to orchestrate these human interventions. Map guidance empowers users with contextual information about the WfMS and environment, enables the interruption of model control on the affected instances, supports collaborative exception handling and facilitates regaining model control after the exception has been resolved. The framework implementation in the Open Symphony open source platform is also described.

Along with rapid development of workflow technology, on the market, there are a lot of workflow products. Workflow exception handling study in the exception of workflow, through the appropriate method to deal effectively with the exception to ensure the implementation of the workflow. Most existing research on workflow management systems (WFMS) has been focused on workflow based on well structured and well-behaved business processes. But it is devoid of the advisement of flexibility and uncertainty. This paper proposes an Agents group based approach for exception handling. Agents group is dispatched to find out the status of running processes in the system to keep track and troubleshoot them when necessary. This model describes the classification of workflow exception, and the corresponding design of different type of exception handing agents and their cooperation.

When multiple participants work on a workflow that represents a large, collaborative activity, it is important to have a well defined process to determine the portions of the workflow that each participant is responsible for executing. In this paper, we describe a process and related algorithms required to assign tasks in a workflow, to hosts that are willing to carry out the execution of these tasks, and thereby contributing to the completion of the activity. This problem is a stylized form of the multi-processor scheduling algorithm which has been shown to be NP-Hard. Further complicating the issue is that we are targeting our approach to mobile ad hoc networks, where hosts are physically mobile, communication links are frequently interrupted, and spatiotemporal considerations become increasingly important. We describe a distributed approach to task allocation in mobile ad hoc networks that employs heuristics to assign tasks in a workflow to mobile hosts based on their capabilities and their mobility patterns. We have implemented our algorithms in the context of CiAN, a workflow management system (WfMS) supporting collaborations in a mobile environment. In addition, we also present performance data of our algorithm and compare it to naive and brute force approaches.

Process Management Systems (PMSs, a.k.a. Workflow Management Systems - WfMSs) are currently more and more used as a supporting tool to coordinate the enactment of processes. In real world scenarios, the environment may change in unexpected ways so as to prevent a process from being successfully carried out. In order to cope with these anomalous situations, a PMS should automatically adapt the process without completely replacing it. In this paper, we propose a general approach and a conceptual architecture to automatic adaptation, based on the concept of declarative modeling of processes and the use of continuous planning techniques. We show the feasibility of the proposed approach by discussing its deployment on top of YAWL, one of the most famous research prototypes of PMSs, in order to demonstrate the modularity and nice integrability with existing models and techniques. A running example shows the practical applicability of the approach.

During workflow design, workflow modelers generally specify the performers of a task by their organizational role. However, during workflow enactment, numerous workers with different skills and expertise may share the same role in an organization, making it hard to select appropriate individuals based merely on the assignment relation between a role and a task. To bridge the gap between abstract roles and real workers, this work proposes a multi-criteria assessment model capable of evaluating the suitability of individual workers for a specified task according to their capabilities, social relationships, and existing tasks. Candidates are ranked based on their suitability scores to support workflow administrators in selecting appropriate workers to perform the tasks assigned to a given role. The proposed assessment model overcomes the lack of role-based task assignment in current workflow management systems.

An agent-based Web service workflow model for inter-enterprise collaboration

Current workflow management systems do not provide adequate support for workflow modeling. Real life work processes are much richer in variations and more dynamic than is expressed in a typical workflow model. Users need to be able to adjust workloads and modify workflow models on-the-fly. In addition, data about workflow executions are analyzed with process analysis/simulation tools to evaluate design alternatives, so workflow models and data must be structured to reflect the questions that managers and designers are likely to ask. The authors present dynamic workflow management (DWM), a framework for modeling workflows that aims to satisfy these requirements. DWM provides high level packaged task templates for composing task sequences, a MOP-like structure based on dynamic memory theory to organize the task sequences into flexible workflow models, and four perspectives into a workflow model geared toward different users' interests. They illustrate these features of DWM with a case study of an interlibrary loan process and discuss its application in workflow enactment and simulation.

Workflow management systems help to execute, monitor and manage work process flow and execution. These systems, as they are executing, keep a record of who does what and when (e.g. log of events). The activity of using computer software to examine these records, and deriving various structural data results is called workflow mining. The workflow mining activity, in general, needs to encompass behavioral (process/control-flow), social, informational (data-flow), and organizational perspectives; as well as other perspectives, because workflow systems are "people systems" that must be designed, deployed, and understood within their social and organizational contexts. This paper particularly focuses on mining the behavioral aspect of workflows from XML-based workflow enactment event logs, which are vertically (semantic-driven distribution) or horizontally (syntactic-driven distribution) distributed over the networked workflow enactment components. That is, this paper proposes distributed workflow mining approaches that are able to rediscover ICN-based structured workflow process models through incrementally amalgamating a series of vertically or horizontally fragmented temporal workcases. And each of the approaches consists of a temporal fragment discovery algorithm, which is able to discover a set of temporal fragment models from the fragmented workflow enactment event logs, and a workflow process mining algorithm which rediscovers a structured workflow process model from the discovered temporal fragment models. Where, the temporal fragment model represents the concrete model of the XML-based distributed workflow fragment events log.

Workflow systems are popular in daily business processing. Since vulnerability cannot be totally removed from a workflow management system, successful attacks always happen and may inject malicious tasks or incorrect data into the workflow system. Referring to the incorrect data further corrupt more data objects in the system, which comprises the integrity level of the system. This problem cannot be efficiently solved by existing defense mechanisms, such as access control, intrusion detection, and checkpoints. In this paper, we propose a practical solution for online attack recovery of workflows. The recovery system discovers all damages caused by the malicious tasks that the intrusion detection system reports and automatically repairs the damages based on data and control dependencies among workflow tasks. We analyze the behaviors of our attack recovery system based on the continuous time Markov chain model. The analytical results demonstrate that our system is practical when the parameters of the system are reasonably designed.

Work flow management systems (WFMSs) are an important new technology, which are likely to have a significant impact on the way in which clerical and administrative operations are organized and executed. This paper seeks to investigate how WFMSs are being exploited and used commercially by UK-based organizations operating in the financial services sector. In-depth interviews were conducted with 14 project managers to explore the development, application and commercial implications of this powerful yet flexible technology. The results indicate that work flow technology has the potential to facilitate significant changes in the way in which an organization conducts its business, through the automation of a wide range of document-intensive operations. Furthermore, when applied in a well-focused manner, it has the potential to realize significant increases in an organization's flexibility and productivity, as well as delivering major improvements to the quality, speed and consistency of customer service.

Workflow Management Systems, such as Galaxy and Taverna, provide a portal through which data can be processed using a sequence of different tools. This sequence allows for the creation of a logical workflow that describes the process. However, when the data workload becomes large enough the time spent in each logical step increases making it difficult to run the workflow fast and efficiently. The proposed solutions is to use task level expansion. Task expansion aims to take each step of the logical workflow and expand it into a new self-contained workflow. These workflows would allow for greater scalability and concurrency by creating more tasks. The resulting workflows will be used indistinguishably from the original tool, but perform more quickly and efficiently. The concept was applied to the BWA tool in Galaxy and we were able to see a 7.36 times speedup in runtime on our 32 GB dataset.

Big data workflow management systems (BDWMS)s have recently emerged as popular data analytics platforms to conduct large-scale data analytics in the cloud. However, the protection of data confidentiality and secure execution of workflow applications remains an important and challenging problem. Although a few data analytics systems, such as VC3 and Opaque, were developed to address security problems, they are limited to specific domains such as Map-Reduce-style and SQL query workflows. A generic secure framework for BDWMSs is still missing. In this article, we propose SecDATAVIEW, a distributed BDWMS that employs heterogeneous workers, such as Intel SGX and AMD SEV, to protect both workflow and workflow data execution, addressing three major security challenges: (1) Reducing the TCB size of the big data workflow management system in the untrusted cloud by leveraging the hardware-assisted TEE and software attestation; (2) Supporting Java-written workflow tasks to overcome the limitation of SGX’s lack of support for Java programs; and (3) Reducing the adverse impact of SGX enclave memory paging overhead through a “Hybrid” workflow task scheduling system that selectively deploys sensitive tasks to a mix of SGX and SEV worker nodes. Our experimental results show that SecDATAVIEW imposes moderate overhead on the workflow execution time.

This paper describes the workflow management system and its reference model. It discusses the common workflow modeling method as well as the existing problem, analyzes agent-based workflow modeling process, gives the execution agent structure model, combined with the present situation of scientific research management, analyzes the workflow agent model of the project outcomes entering database and presents the access control model based on task and role in workflow. The model with good usability well solves the problem of management complex in scientific research management and has a certain application value.

We present a parametric Hoare-like logic for computer-aided reasoning about typeable properties of functional programs. The logic is based on the concept of a specialised assertion, which is a predicate expressing the semantics of a typing judgment in a logical framework (here higher-order logic). Replacing in a type inference rule the judgments by the appropriate specialised assertions, one obtains a specialised rule. Specialised assertions have a uniform format, and soundness proofs of specialised rules employ uniform sequences of steps for a variety of type systems. This allows to abstract from the type system and define parametric specialised assertion and rules. Moreover, we define a parametric soundness condition for each program construct which ensures soundness of the corresponding rule. To prove soundness of the specialised rule for the concrete type system one checks the condition and instantiates the parametric rule. We consider specialised logics for ``non-pure'' type systems which contain rules with semantical side conditions. A semantical condition makes type-checking for such a system undecidable. However, the condition may be approximated by another type system. We introduce a product-like composition of two inference systems that eliminates semantical side conditions. The soundness condition of the composition follows straightforwardly from the soundness conditions of its components and a statement about the approximation.