Blockchain technologies pave a promising way for implementing the inter-organizational processes. Most of the current research works translate the execution logic in the process models into the smart contracts, which can run independently on the blockchain without the outside process engine. However, the works usually suffer from the execution and storage costs, since the translation needs to be done when the processes are deployed. In this paper, we customize a process engine for executing the inter-organizational business processes via a blockchain-style procedure, i.e., checking the validity of transactions, adding the valid transactions into the blockchain through the consensus mechanism, and then updating the process states according to the committed transactions. And then, we build a blockchain system by embedding the customized process engine into the blockchain nodes. Moreover, in order to realize the interactions between the inter-organizational processes running on blockchain and the services outside blockchain, we propose a blockchain-based approach for service registration, binding and invocation, and design a lease-based concurrency control protocol to logically isolate transactions from each other when invoking the services simultaneously. Finally, we implement a prototype system based on a permissioned blockchain platform Hyperledger Fabric and a process engine Activiti. The experimental results show the proposed blockchain system can execute the inter-organizational processes correctly and efficiently.

With recent advancements in Industrial Internet of Things (IIoT), the stream data generated in IIoT applications presents new characteristics: huge amount of data, ultrahigh computational complexity and large memory consumption, and the existence of concept drift leading to the ineffective distinction between real drift and anomalies. It is difficult for the current mainstream methods to cope with the above problems effectively. In this article, we propose an efficient Gaussian kernel microcluster real-time-clustering method for IIoT data streams (GKMC).The method uses a microcluster sketch structure instead of individual data sample points to participate in clustering directly, which solves the problem of not being able to store unlimited data in limited memory; it uses a Gaussian kernel function to calculate the local density of microclusters to enhance the detection of anomalies; in addition, using the gravity energy function recursively to update the microcluster online and using the relearning strategy to improve the detection ability of whether the outdated microcluster belongs to abnormal microcluster or has real concept drift, ensuring that the current microcluster is always the latest microcluster most closely related to the cluster. The theoretical analysis and sufficient comparison experiments on three data sets show that the proposed algorithm has a better clustering effect than the current mainstream stream clustering algorithms.

Abstract Locality‐sensitive hashing (LSH) is widely used in the context of nearest neighbor search of large‐scale high‐dimensions. However, there are serious imbalance problems between the efficiency of data index structure construction and the query accuracy of LSH methods. In this article, a novel higher‐entropy‐hyperplane clusters LSH (HEHC‐LSH) algorithm is proposed, which we improve vector quantization to preprocess the data and greatly shortens the preprocessing time; We innovatively integrate the maximum entropy principle into the distribution estimation algorithm to construct a novel hash function cluster method, also incorporate bootstrap aggregating of ensemble learning, and adopt the parallel index dictionary to improve the generalization performance of the index structure. And in the query stage, we realize the comprehensive filtering of index set using integrated learning idea, which not only avoids a lot of distance calculation, but also improves the quality of query results. We also analyze the rationality and effectiveness of the proposed method. Finally, extensive experiment results show that HEHC‐LSH can achieve more higher precision and efficiency simultaneously comparing to current methods, and reflect the strong robustness on different datasets.

In a mobile system, mobility refers to a change in position of a mobile object with respect to time and its reference point, whereas isolation means the isolation relationship between mobile objects under some scheduling policies. Inspired by event-based formal models and the ambient calculus, we first propose the two types of special events, entering and exiting an ambient, as movement events to model and analyze mobility. Based on mobility, we then introduce the notion of the isolation of mobile objects for ambients. To ensure the isolation, a priority policy needs to be used to schedule the movement of mobile objects. However, traditional scheduling policies focus on task scheduling and depend on the strong hypothesis: The scheduled tasks are independent—that is, the scheduled tasks do not affect each other. In a practical mobile system, mobile objects and ambients interact with each other. It is difficult to separate a mobile system into independent tasks. We finally present an automatic approach for generating a priority scheduling policy without considering the preceding assumption. The approach can guarantee the isolation of the mobile objects for ambients in a mobile system. Experiments demonstrate these results.

Mobility is a critical issue that must be considered during the modeling and analyzing of a mobile system. At a high abstract level, event-based models can directly specify a mobile system without the introduction of additional mechanisms. In this article, we first propose two types of special events, entering and exiting an ambient, as movement events. Next, based on the movement events, we introduce the notion of a movement path and propose a feasible movement criterion (deciding whether a given movement path of a mobile object (agent) is feasible or not in terms of spatiotemporal topological relationships of ambients). Then, we investigate how a message movement--based communication model represents synchronous communication, asynchronous communication, and broadcast communication in a unified way. Finally, we use movement event sequences to discuss the exclusivity of ambients (an ambient only allows one mobile object to occupy (enter) it at any moment) and show that a priority scheduling control policy can guarantee exclusivity. Accordingly, we propose a correct movement criterion—that is, a correct movement path is feasible and satisfies the exclusivity of ambients. Case studies demonstrate these results.

In a business cloud environment, a reference business process model needs to be customized in order to meet the individualized requirements of each organization. Consequently, a reference process model is generally evolved to a couple of process variants, known as a process family. Currently, there exist some approaches and tools that can efficiently configure a reference process model. However, a key issue is how to manage co-evolution appropriately within a family of process models if the base process model of a process family is changed. Contemporary process management tools do not adequately support the management of such co-evolution. Each process variant in the process family has to be changed as a separate process model which often leads to redundancies and inefficiencies. In this article, we propose a novel approach for managing co-evolution of process families based on an aspect-oriented approach. Change options on base process model are abstracted and extracted as a pluggable component, which can be selectively reused for all members, and consequently, guides the co-evolution for the whole process family. In particular, the control-flow and data-flow relations between process extension and a member of process families can be built by leveraging process extensibility patterns. The correctness of our extension approach is proved based on graph theory. The whole approach in this article have been implemented as a working open-source prototype and tested against a real case study from the city logistic distribution domain as well as real data set from SAP reference models.

The traditional research on scheduling focuses on task scheduling and schedulability analysis in concurrent reactive systems. In this article, we dedicate ourselves to event-based scheduling. We first formally define an event-based scheduling policy and propose the notion of the correctness of a scheduling policy in terms of weak termination. Then we investigate the correctness of the decomposition of scheduling controls and finally obtain a decentralized scheduling method. The method can automatically decompose the scheduling policies of a concurrent reactive system into atomic scheduling policies. Every atomic scheduling policy corresponds to one subsystem. Each of the subsystems is a completely independent system, which may be developed and deployed independently. An experiment demonstrates these results that may help engineers to design correct and efficient schedule policies for a concurrent reactive system.

Virtualization is fundamental to cloud computing. It allows abstraction centred on services and isolation of lower level functionalities and underlying hardware. Modeling, analyzing and verifying cloud systems necessarily involve virtualization and services. However, there exist few efforts to effectively formalizing virtualization in cloud computing. In this paper, based on services we present an approach for defining virtualization. We discuss some properties of service virtualization under some operations and the correctness of virtual services (virtual services without abnormal behavioral problems). Moreover, we investigate automatic configuration of a service based on virtualization, that is, given a virtualized service, how can we automatically obtain all possible correct virtual services of such a service? The configuration process is to first separate a virtualized service into atomic and correct virtual services and then merge these atomic virtual services into all possible correct virtual services of such a virtualized service. The obtained theoretical results help to formally analyze, verify and configure cloud systems.

Semantically annotated process model (SPM) is a process model with semantic annotations, which include the precondition and effect, labeled for its activities based on the domain ontology. Such semantic annotations can increase the model's understanding and reusability, and facilitate its implement as well as compliance analysis. However, SPM analysis is challenging, since its correctness is beyond the soundness of process model and its formal semantics needs to consider domain state change. To assuring the correctness of SPM, the executablity analysis, i.e., whether there exists activity whose precondition is falsatisfied when it is active, is essential and has also been identified as a coNP-hard problem. To tame the hardness of the executability, we define a dynamic semantics for SPM based on a model which is proposed for defining domain state transition, present an encoding method by which the formal semantics is encoded into formulae as well as the executability, and propose a procedure which can bounded model check and diagnose the executability by using SAT solver. Our method has been implemented as a tool called SPMT and its validity is also illustrated through examples.

Nowadays, SOA is considered as a promising architecture for enterprise applications integration. OWL-S, as a Semantic Web Service technology, promises to facilitate various service tasks, such as service specification, discovery, composition, etc.. It is essential to analysis the OWL-Sprocess model for the quality issue of the composition of web services before its deployment. In this work, By CSPm and FDR tool, a formal analysis method for OWL-S process model, especially the interplay between the control part and dataflow part, is proposed, and its validity is illustrated by the extended version of the Bravo Air process model.

Mismatch patterns capture the possible differences between two service (business) protocols to adapt. For these mismatches, formal definitions are presented in this paper. And a novel technique provides support for adapting two or more services. This technique requires that messages and message dependencies are used to directly model service (business) protocols and form a novel model, called a\emph{protocol structure}. Unlike most of existing approaches that only consider typical mismatches (e.g. deadlock), this model is easily used to detect multiple mismatches at a time and to automatically generate BPEL adapters.

In SOA, adaptation techniques aim to automatically generate adapters. However, the generation of the adapter is a complicated task and requires extra knowledge to resolve all kinds of mismatches. We propose a novel model, called a protocol structure, which is used to model services and adapters and detect the mismatches among services. Once developers present interface mappings among services, adapters can be derived from the interface mappings.