The evolution of edge and cloud computing infrastructures has opened avenues for developing Internet-centered distributed applications characterized by adaptability, evolvability, and emergence. These applications, such as knowledge-driven distributed workflows are dynamically orchestrated and managed using resources across enterprise networks, cloud data centers, and Internet of Things (IoT) devices. Unlike traditional business processes and scientific workflows, knowledge-driven workflows dynamically evolve and adapt by responding to the environmental context, current execution status, and specific parameters of the case at hand, which are not predictable beforehand. In this demonstration, we present the Orchflow system, designed for dynamic orchestration and management of adaptive IoT-centric workflows. Orchflow enables flexible and location-aware resource selection, iterative and incremental binding, and dynamic deployment of services by considering factors such as spatio-temporal requirements of workflow tasks, resource availability status, underlying service infrastructure constraints, and real-time processing requirements within the workflow.

Current Internet of Things (IoT) devices provide a diverse range of functionalities, ranging from measurement and dissemination of sensory data observation, to computation services for real-time data stream processing. In extreme situations such as emergencies, a significant benefit of IoT devices is that they can help gain a more complete situational understanding of the environment. However, this requires the ability to utilize IoT resources while taking into account location, battery life, and other constraints of the underlying edge and IoT devices. A dynamic approach is proposed for orchestration and management of distributed workflow applications using services available in cloud data centers, deployed on servers, or IoT devices at the network edge. Our proposed approach is specifically designed for knowledge-driven business process workflows that are adaptive, interactive, evolvable and emergent. A comprehensive empirical evaluation shows that the proposed approach is effective and resilient to situational changes.

The use of blockchain technology has been proposed to provide auditable access control for individual resources. Unlike the case where all resources are owned by a single organization, this work focuses on distributed applications such as business processes and distributed workflows. These applications are often composed of multiple resources/services that are subject to the security and access control policies of different organizational domains. Here, blockchains provide an attractive decentralized solution to provide auditability. However, the underlying access control policies may have event-driven constraints and can be overlapping in terms of the component conditions/rules as well as events. Existing work cannot handle event-driven constraints and does not sufficiently account for overlaps leading to significant overhead in terms of cost and computation time for evaluating authorizations over the blockchain. In this work, we propose an automata-theoretic approach for generating a cost-efficient composite access control policy. We reduce this composite policy generation problem to the standard weighted set cover problem. We show that the composite policy correctly captures all the local access control policies and reduces the policy evaluation cost over the blockchain. We have implemented the initial prototype of our approach using Ethereum as the underlying blockchain and empirically validated the effectiveness and efficiency of our approach. Ablation studies were conducted to determine the impact of changes in individual service policies on the overall cost.

Cloud and edge-computing based platforms have enabled rapid development of distributed business process (BP) applications in a plug and play manner. However, these platforms do not provide the needed capabilities for identifying or repairing faults in BPs. Faults in BP may occur due to errors made by BP designers because of their lack of understanding of the underlying component services, misconfiguration of these services, or incorrect/incomplete BP workflow specifications. Such faults may not be discovered at design or development stage and may occur at runtime. In this paper, we present a unified framework for automated fault resolution in BPs. The proposed framework employs a novel and efficient fault resolution approach that extends the generate-and-validate program repair approach. In addition, we propose a hybrid approach that performs fault resolution by analyzing a faulty BP in isolation as well as by comparing with other BPs using similar services. This hybrid approach results in improved accuracy and broader coverage of fault types. We also perform an extensive experimental evaluation to compare the effectiveness of the proposed approach using a dataset of 208 faulty BPs.

An emergency response process outlines the workflow of different activities that need to be performed in response to an emergency. Effective emergency response requires communication and coordination with the operational systems belonging to different collaborating organizations. Therefore, it is necessary to establish information sharing and system-level interoperability among the diverse operational systems. Unlike typical e-government processes that are well structured and have a well-defined outcome, emergency response processes are knowledge-centric and their workflow structure and execution may evolve as the incident unfolds. It is impractical to define static plans and response process workflows for every possible situation. Instead, a dynamic response should be adaptable to the changing situation. We present an integrated approach that facilitates the dynamic composition of an executable response process. The proposed approach employs ontology-based reasoning to determine the default actions and resource requirements for the given incident and to identify relevant response organizations based on their jurisdictional and mutual aid agreement rules. The Web service APIs of the identified response organizations are then used to generate an executable response process that evolves dynamically. The proposed approach is implemented and experimentally validated using an example scenario derived from the FEMA Hazardous Materials Tabletop Exercises Manual.