Design and Realisation of Scalable Business Process Management Systems for Deployment in the Cloud

Business Process Management Systems ( BPMSs ) provide automated support for the execution of business processes in modern organisations. With the emergence of cloud computing, BPMS deployment considerations are shifting from traditional on-premise models to the Software-as-a-Service ( SaaS ) paradigm, aiming at delivering Business Process Automation as a Service. However, scaling up a traditional BPMS to cope with simultaneous demand from multiple organisations in the cloud is challenging, since its underlying system architecture has been designed to serve a single organisation with a single process engine. Moreover, the complexity in addressing both the dynamic execution environment and the elasticity requirements of users impose further challenges to deploying a traditional BPMS in the cloud. A typical SaaS often deploys multiple instances of its core applications and distributes workload to these application instances via load balancing. But, for stateful and often long-running process instances, standard stateless load balancing strategies are inadequate. In this article, we propose a conceptual design of BPMS capable of addressing dynamically varying demands of end users in the cloud, and present a prototypical implementation using an open source traditional BPMS platform. Both the design and system realisation offer focused strategies on achieving scalability and demonstrates the system capabilities for supporting both upscaling, to address large volumes of user demand or workload, and downscaling, to release underutilised computing resources, in a cloud environment.

Executing Distributed Healthcare and Research Processes – The HiGHmed Data Sharing Framework

Several standards and frameworks have been described in existing literature and technical manuals that contribute to solving the interoperability problem. Their data models usually focus on clinical data and only support healthcare delivery processes. Research processes including cross organizational cohort size estimation, approvals and reviews of research proposals, consent checks, record linkage and pseudonymization need to be supported within the HiGHmed medical informatics consortium. The open source HiGHmed Data Sharing Framework implements a distributed business process engine for executing arbitrary biomedical research and healthcare processes modeled and executed using BPMN 2.0 while exchanging information using FHIR R4 resources. The proposed reference implementation is currently being rolled out to eight university hospitals in Germany as well as a trusted third party and available open source under the Apache 2.0 license.

Concept and Implementation of Data Usage Proposal Process Based on International Standards in SMITH

Accessing secondary-use healthcare data in Germany requires contracting with each organization that acts as a data provider. The SMITH Service Platform offers a central access point for scientists, facilitating contracting as part of an integrated data use and access process with several Data Integration Centers (DIC) at once. Process support is realized by a central Business Process Engine (BPE), which manages process definition and process control, combined with a central IHE infrastructure. The use of IHE XDS and IHE XDW profiles enables the exchange of process instance information with multiple distributed visualization and user interaction tools for provided user tasks based on international standards. User task information include structured forms for submitting instructions and results as task input and output for the users, and are synchronized between the shared process instance and the BPE. A reference user interface is also provided with the SMITH Marketplace. In the future, further standardization efforts regarding the structured forms and the use of the IHE XDW profile should be pursued.

Resource Controllability of Business Processes Under Conditional Uncertainty

A current research problem in the area of business process management deals with the specification and checking of constraints on resources (e.g., users, agents, autonomous systems, etc.) allowed to be committed for the execution of specific tasks. Indeed, in many real-world situations, role assignments are not enough to assign tasks to the suitable resources. It could be the case that further requirements need to be specified and satisfied. As an example, one would like to avoid that employees that are relatives are assigned to a set of critical tasks in the same process in order to prevent fraud. The formal specification of a business process and its related access control constraints is obtained through a decoration of a classic business process with roles, users, and constraints on their commitment. As a result, such a process specifies a set of tasks that need to be executed by authorized users with respect to some partial order in a way that all authorization constraints are satisfied. Controllability refers in this case to the capability of executing the process satisfying all these constraints, even when some process components, e.g., gateway conditions, can only be observed, but not decided, by the process engine responsible of the execution. In this paper, we propose conditional constraint networks with decisions (CCNDs) as a model to encode business processes that involve access control and conditional branches that may be both controllable and uncontrollable. We define weak, strong, and dynamic controllability of CCNDs as two-player games, classify their computational complexity, and discuss strategy synthesis algorithms. We provide an encoding from the business processes we consider here into CCNDs to exploit off-the-shelf their strategy synthesis algorithms. We introduce $$\textsc {Zeta}$$ Z E T A , a tool for checking controllability of CCNDs, synthesizing execution strategies, and executing controllable CCNDs, by also supporting user interactivity. We use $$\textsc {Zeta}$$ Z E T A to compare with the previous research, provide a new experimental evaluation for CCNDs, and discuss limitations.

Thermochemical and Sensible Energy Recuperation Using Thermally-Integrated Reactor and Diesel-Ammonia Dual Fueling Strategy

Anhydrous ammonia produced using wind power on farms can be a renewable alternative to conventional fertilizers and to fossil fuels used in engine-powered equipment. Although it has been shown that ammonia can be used in dual fuel modes in diesel engines, its inherently low flame speed results in poor combustion efficiency and thus reduces allowable diesel fuel replacement ratios. In this work, a novel method using a thermochemical recuperation (TCR) reactor system to partially decompose ammonia into hydrogen and nitrogen over a catalyst was demonstrated in diesel engine powered tractor. In the experiments, a John Deere 6400 agricultural tractor powered by a non-EPA tier-certified 4045TL diesel engine was operated in dual-fuel mode using anhydrous ammonia as the secondary fuel. Liquid ammonia from a tank was vaporized and heated using a series of heat exchangers and partially decomposed to hydrogen gas before being fumigated into the intake manifold. The catalytic TCR reactor utilized both exhaust waste heat and unburned hydrocarbon heating value to drive the ammonia decomposition process. Engine emissions and performance data were collected across a standard 8-mode test. The engine was operated using diesel only and in dual fuel mode with up to 42% replacement of diesel with ammonia on a lower heating value basis. Engine loading was accomplished using a power takeoff (PTO) dynamometer. Measured brake thermal efficiency was improved by up to 5.0% using thermochemical recuperation, and brake specific CO2 emissions were reduced by up to 44% over diesel-only rates.