Execution Of Composite Services Research Articles

Formal Analysis of Trust and Reputation for Service Composition in IoT

The exponential growth in the number of smart devices connected to the Internet of Things (IoT) that are associated with various IoT-based smart applications and services, raises interoperability challenges. Service-oriented architecture for IoT (SOA-IoT) solutions has been introduced to deal with these interoperability challenges by integrating web services into sensor networks via IoT-optimized gateways to fill the gap between devices, networks, and access terminals. The main aim of service composition is to transform user requirements into a composite service execution. Different methods have been used to perform service composition, which has been classified as trust-based and non-trust-based. The existing studies in this field have reported that trust-based approaches outperform non-trust-based ones. Trust-based service composition approaches use the trust and reputation system as a brain to select appropriate service providers (SPs) for the service composition plan. The trust and reputation system computes each candidate SP's trust value and selects the SP with the highest trust value for the service composition plan. The trust system computes the trust value from the self-observation of the service requestor (SR) and other service consumers' (SCs) recommendations. Several experimental solutions have been proposed to deal with trust-based service composition in the IoT; however, a formal method for trust-based service composition in the IoT is lacking. In this study, we used the formal method for representing the components of trust-based service management in the IoT, by using higher-order logic (HOL) and verifying the different behaviors in the trust system and the trust value computation processes. Our findings showed that the presence of malicious nodes performing trust attacks leads to biased trust value computation, which results in inappropriate SP selection during the service composition. The formal analysis has given us a clear insight and complete understanding, which will assist in the development of a robust trust system.

Design of an Optimal Deep Learning-Based Self-Healing Mechanism With Failure Prediction Model for Web Services

Recently, web service composition technology becomes familiar and it raise the quality offered by the systems designed followed by the service oriented architecture (SOA) framework. Web service composition mainly functioning in dynamic environment, susceptible to the incidence of unpredictable disruption and modifications which could influence the performance of the system. Therefore, the ability to self-healing and manage the execution of web service composition can enhance the reliability and fault tolerance of the system.This study develops an Optimal Deep Learning based Self Healing Mechanism with Failure Prediction (ODL-SHMFP) model for Web Services. The proposed ODL-SHMFP technique aims to accomplish a self healing model for minimizing the failure in web services.

An Optimal Execution of Composite Service in Decentralized Environment

It is important for service-oriented architectures to consider about how the composition of web services affects business processes. For instance, a single web service may not have been adequate for most complex business operations, needing the use of multiple web services. This paper proposed a novel technique for optimal partitioning and execution of the services using a decentralized environment. The proposed technique is designed and developed using a genetic algorithm with multiple high task allocations on a single server. We compared three existing techniques, including meta-heuristic genetic algorithm, heuristics like Pooling-and-Greedy-Merge (PGM) technique, and Merge-by-Define-Use (MDU) technique, to a simulation of Business Process Execution Language (BPEL) partition using genetic algorithm through multiple high tasks allocation to single server node. The proposed technique is practical and advantageous. In terms of execution time, number of server requests, and throughput, the proposed technique outperformed the existing GA, PGM, and MDU techniques.

An effective adaptive adjustment method for service composition exception handling in cloud manufacturing

With the increasing market features of globalization, service and customization, the way manufacturers conduct manufacturing business is changing. Under this background, Cloud Manufacturing (CMfg) emerges as a new networked manufacturing model. However, CMfg is immature in many aspects, especially in exception handling of service composition execution. Due to the complexity of the enterprise manufacturing process, there are a large number of unpredictable abnormal events in the dynamic open cloud manufacturing environment (such as user demand change, machine failure, etc.), so in order to ensure the smooth implementation of the service combination, it is indispensable to establish an effective service exception handling mechanism in CMfg. Moreover, when an exception occurs, in order to ensure the smooth execution of the downstream services after the exception point, the exception handling must satisfy the strict time constraints. To realize the exception-handing of service-composition with the strict deadline or strict time constraints, this paper proposes a service-composition exception adaptive adjustment model, considering the influences of the logistics transferring time and cost. And the occupied time of the cloud services and the valid replacement time range of the exception service are considered as the constraints in this model. In addition, the processing quality, the cost, and the quality of service are set as the optimal objectives. On the above basis, a service-composition exception handling adaptive adjustment (SCEHAA) algorithm based on the improved ant colony optimization algorithm (ACO) is proposed and applied to address the above model. Finally, to validate the performance of SCEHAA, a case study and the comparison experiment between SCEHAA and other algorithms (Particle Swarm Optimization and Artificial Bee Colony) are performed. The results show that the SCEHAA algorithm can perform the adaptive adjustment of the service-composition with strict time limit effectively, through the adaptive service execution path reconfiguration and has fast convergence effects.

Adaptive BPEL Service Compositions via Variability Management

Service-Oriented Architectures are a popular development paradigm to enable distributed applications constructed from independent web services. When coordinated, web services are an infrastructure to fulfill dynamic and vertical integration of business. They may face frequent changes of both requirements and execution environments. Static and predefined service compositions using business process execution language (BPEL) are not able to cater for such rapid and unpredictable context shifts. The authors propose a variability management-based adaptive and configurable service composition approach that treats changes as first-class citizens and consists of identifying, expressing, realizing, and managing changes of service compositions. The proposed approach is realized with a language called VxBPEL to support variability in service compositions and a platform for design, execution, analysis, and maintenance of VxBPEL-based service compositions. Four case studies validate the feasibility of the proposed approach while exhibiting good performance of the supporting platform.

Constraint verification failure recovery in web service composition

Automated service composition aims at fulfilling complex tasks by combining different existing elementary web services in a workflow and creating value-added services. Many approaches have been proposed for automatic web service composition. Most of these approaches are based on the matching of input/output parameters across different elementary services. However, in addition to input/output parameters, many real-world services have applicable conditions and usage restrictions (i.e., service constraints) that are imposed by their providers. The constraints of a service should be verified prior to service call to ensure its correct execution. However, constraint verification of a composite service is different, as verification of some of the elementary services’ constraints might require execution of other elementary services inside the composite plan. In addition, failure during verification of constraints inside a composite plan results in the failure of execution of the whole composite service, which requires failure recovery for the composite service to continue execution. Composite service failure recovery implies the rollback of certain service transactions during the recovery of the composite plan. Current composite service failure recovery approaches are not adapted to the minimization of service rollbacks due to constraint verification failures. In this paper, a constraint-aware failure recovery approach is proposed to predict failures inside a composite service. Then, a method is proposed to do failure recovery based on those predictions and minimize the number of service rollbacks upon failure resulting from constraint verification. The proposed solution includes a planning-based algorithm and a novel constraint-processing method for service failure prediction and recovery. A publicly available test set generator is used to evaluate and analyze the proposed solution.

Fuzzy ACID properties for self‐adaptive composite cloud services execution

SummaryThe ACID transaction model has played a cornerstone role in service composition to guarantee that composite services (CSs) have transactional support and consistent outcomes even in presence of failures. However, the classical ACID properties are too restrictive for independent and multi‐proprietors services running on distributed environments, such clouds. Transactional properties allow a relaxed atomicity and isolation, providing an “all‐or‐(almost)nothing” model. In previous works, we proposed a model to relax atomicity, called fuzzy atomicity, according user requirements (acceptable fuzzy atomicity). In this article, we extend that model and propose an approach to measure the fuzzy atomicity. Our model allows to self‐adapt the CS execution, taking into account the state of the CS execution and user preferences (ie, the acceptable fuzzy atomicity expressed in the user requirements). This fuzzy atomicity measure is applied in a self‐adaptive CS execution model based on the transactional properties (pivot, compensatable, and retriable) of its component services and on a checkpointing mechanism. It is suitable to cloud computing, which offers cloud services on demand and in which CS execution should preserve the self‐organizing and self‐adaptivity properties of such environment, specially in the presence of failures. We show how it is possible to relax the retriable property in CSs execution, based on our fuzzy atomicity model. Additionally, in this work, we present a comparative analysis of the most recent works in the context of ACID properties relaxation for CS.

Adaptive composition in dynamic service environments

Due to distribution, participant autonomy and lack of local control, service-based systems operate in highly dynamic and uncertain environments. In the face of such dynamism and volatility, the ability to manage service changes and exceptions during composite service execution is a vital requirement. Most current adaptive composition approaches, however, fail to address service changes without causing undesirable disruptions in execution or considerably degrading the quality of the composite application. In response, this paper presents a novel adaptive execution approach, which efficiently handles service changes occurring at execution time, for both repair and optimisation purposes. The adaptation is performed as soon as possible and in parallel with the execution process, thus reducing interruption time, increasing the chance of a successful recovery, and producing the most optimal solution according to the current environment state. The effectiveness of the proposed approach is demonstrated both analytically and empirically through a case study evaluation applied in the framework of learning object composition. In particular, the results show that, even with frequent changes (e.g. 20 changes per service execution), or in the cases where interference with execution is non-preventable (e.g., when an executed service delivers unanticipated quality values), our approach manages to recover from the situation with minimal interruption.

The Executable Invocation Policy of Web Services Composition With Petri Net

The web service composition execution engine is a critical problem for web service composition. Based on Petri net and the analysis of structural relationships among web services, the invocation sequence of web service composition and its related invocation policies are fully studied in this paper. Also, the executable invocation policies of web service composition are successfully constructed based on Petri net. Finally, an example of a scientific computation service is given to validate the effectiveness of this method.

Conformance Checking and QoS Selection Based on CPN for Web Service Composition

The development of new services by composition of existing ones has gained considerable momentum as a means of integrating heterogeneous applications and realizing business collaborations. More and more Web services with similar function attributes but different QoS are available. The performance of the composed service is determined by the involved Web services. Therefore, QoS properties are crucial for selecting the Web services to take part in the composition, which can identify the best candidate Web services from a set of functionally-equivalent services. Web service composition enables seamless and dynamic integration of business applications on the web. Due to the inherent autonomy and heterogeneity of component Web services, it is difficult to predict the behavior of the overall composite service. Conformance checking identifies failure and conflict of execution of composite Web service that ensures reliable execution. In this paper we use skyline computation to select services for composition efficiently, reducing the number of candidate services to be considered. Then a novel color Petri net model of Web service composition is presented that combines QoS-based optimal service selection and consistence verification. In the model we define aggregation functions, and use a Multiple Attribute Decision Making approach for the utility function to achieve optimal services selection of QoS properties. We also propose a consistence verification approach to identify potential logical inconsistence of the semantic Web service process before the deployment. Proofs are also presented. We evaluate our approach experimentally using both real and synthetically generated datasets.

Cloud Logistics Path Optimization Based on Ant Colony Algorithm

Cloud Manufacturing is developed in the cloud computing, which is based on the idea of "Made in service" recently. Cloud manufacturing mode connect all sorts of manufacturing resources and capability together and form standard manufacturing services which customers can obtain according to their demand at any time. Logistics mode should coincide with manufacturing mode for the certain correlation between logistics and manufacturing process,so the production and development of cloud manufacturing mode had the logistics mode reformed. In this paper we present a cloud manufacturing service composition method considering execution reliability based on ant algorithm, to optimize the use of composite service execution path to save the costs.

Cost‐aware execution of transactional web services using labelled transition systems

Recently web service composition has become a very cost-effective way to develop business applications. However, owing to the unreliable nature of web services, providing the transactional support in execution of a service composition is an important design requirement. To guarantee the transactional execution of service compositions, a fault-handling routine has to be started once a service failure occurs in order to undo the effect of previously completed services by calling their corresponding compensation operations. Currently this fault-handling mechanism is implemented by means of low-level programming constructs such as exception-handling mechanism in languages such as WS-BPEL. However, since the logic of handling service failures might become very complex in some applications, this concern should be separated from the normal flow of the composition workflow based on the separation of concerns principle. To achieve this, in this study we have proposed an orchestration pattern for building a transactional service composition in which the failure-recovery logic is imposed on the composition workflow by a Labelled Transition System (LTS) as a separate module. It is assumed that each service within the composition is associated with two known transactional properties: (i) a rollback cost that indicates the cost of undoing (compensating) the service and (ii) a failure probability. The transactional logic of the service composition is also specified using the rollback dependencies represented in a rollback graph. An LTS then is generated to schedule the execution of services within the composition based on the composition transactional logic and properties such that upon a service failure, a recovery path with the lowest cost is followed.

Research of Cloud Manufacturing Execution Path Optimization Based on Adaptive Ant Colony Algorithm on Hadoop Platform

Cloud Manufacturing is developed in the cloud computing, which is based on the idea of "Made in service" recently. As execution of manufacturing resources is more complicated than computational resources the service combination execution reliability becomes a mandatory considering problem in cloud manufacturing. In this paper we present a cloud manufacturing service composition method considering execution reliability based on adaptive ant algorithm, which in hadoop environment to optimize the use of composite service execution path to save the costs. As the experimental result shown, this method can effectively avoid the congestion of data on the critical path.

Study on Ant Colony Algorithm about Resource Search and Optimization in Cloud Manufacturing

These years, a new networked manufacturing mode named cloud manufacturing is arising. Cloud manufacturing comprehensively uses various information technology, manufacturing technology and management technology, through virtualization and servitization of manufacturing hardware and software resources. CloudM is to provide user with on-demand, always-ready, high-quality and low-consumption service, which is available from product design, manufacturing, testing, simulation and maintenance and other manufacturing lifecycle process. Service composition is one of the key issues in implementing CloudM system. In this paper, an adaptive ant algorithms have been proposed, which In hadoop environment to optimize the use of composite service execution path. As the experimental result shown, this method can effectively avoid the congestion of data on the critical path.

QoS Aware Adaptive Service Composition

In current business scenario the business processes of enterprises are service oriented. The services of various applications are advertised in service registry using Web Service Description Language description for service selection and composition. Service composition process integrates services based on Business Process Execution Language description of composite service and executed by the orchestration coordinator. As all compliant services description are included in the description, the service selection and execution consumes more time users need select the service form set of complaint services. This study proposes an adaptive service composition methodology over extended web service Quality Aware Service Integration architecture (QASI). The proposed service composition methodology reads the composite service description and constructs a composition tree. In each service node of composition tree a service is replaced by one that satisfies functional and QoS requirement. During execution of composite service or binding of service, the parameters like server maximum capacity, current load on server and expected time for completing current load for service at each level of composition tree are analyzed. An alternative service will be allocated at particular level to improve the overall response time of composite service. The QASI architecture provides a repository to store composition tree as symbolic notations to ensure repeatability. Experimental results indicates selection of best service and better response time by proposed methodology using QASI architecture compared to contemporary web service composition methodology using static BPEL description.

A survey of methods and approaches for reliable dynamic service compositions

An increasing amount of today’s software systems is developed by dynamically composing available atomic services to form a single service that responds to consumers’ demand. These composite services are distributed across the network, adapted dynamically during run-time, and still required to work correctly and be available on demand. The development of these kinds of modern services requires new modeling and analysis methods and techniques to enable service reliability during run-time. In this paper, we define the required phases of the composite service design and execution to achieve reliable composite service. These phases are described in the form of a framework. We perform a literature survey of existing methods and approaches for reliable composite services to find out how they match with the criteria of our framework. The contribution of the work is to reveal the current status in the research field of reliable composite service engineering.

OpenCOPI: middleware integration for Ubiquitous Computing

In this paper, we present OpenCOPI (Open COntext Platform Integration), a Service-Oriented Architecture-based middleware platform that supports the integration of services provided by distinct sources, ranging from services offered by simple systems to more complex services provided by context-provision middleware. OpenCOPI offers selection and composition mechanisms to, respectively, select and compose services provided by different sources, considering applications of both Quality of Service and Quality of Context requirements. It also offers an adaptation mechanism that enables to adapt the application execution due to service failures, service quality fluctuation and user mobility. OpenCOPI allows the definition of applications in a higher abstraction level by the specification of a semantic workflow that contains abstract activities. This paper illustrates the use of OpenCOPI in an application from the Gas & Oil Industry and it also shows the evaluation of the main mechanisms of OpenCOPI: the service selection, composition, adaptation and workflow execution.

Exception Handling of Composite Services Based on Autonomic Management

BPEL-based composition of Web services has become one important part of business processes, but because of the dynamic and complexity of network, it easily raises various exceptions during the execution. In order to address various exceptions may exist in execution of composite Web services process effectively; this paper proposes an effective exception handling model of composite Web services in combination of the autonomic management theories and techniques in the field of autonomic computing. This model incorporates the autonomic management element of autonomic computing to monitor the execution of composite services and to compensate or restore the business process of the composite services according to the specified policy when an exception occurs. The model enhances the exception handling autonomy while reducing the complexity of exception handling of composite services.

A Dynamic Composition and Stubless Invocation Approach for Information-Providing Services

The automated specification and execution of composite services are important capabilities of service-oriented systems. In practice, service invocation is performed by client components (stubs) that are generated from service descriptions at design time. Several researchers have proposed mechanisms for late binding. They all require an object representation (e.g., Java classes) of the XML data types specified in service descriptions to be generated and meaningfully integrated in the client code at design time. However, the potential of dynamic composition can only be fully exploited if supported in the invocation phase by the capability of dynamically binding to services with previously unknown interfaces. In this work, we address this limitation by proposing a way of specifying and executing composite services, without resorting to previously compiled classes that represent XML data types. Semantic and structural properties encoded in service descriptions are exploited to implement a mechanism, based on the Graphplan algorithm, for the run-time specification of composite service plans. Composite services are then executed through the stubless invocation of constituent services. Stubless invocation is achieved by exploiting structural properties of service descriptions for the run-time generation of messages.

Threat Representation Methods for Composite Service Process Models

The Business Process Modeling Notation (BPMN) has become a popular standard for expressing high level business processes as well as technical specifications for software systems. However, the specification does not contain native support to express security information, which should not be overlooked in today’s world where every organization is exposed to threats and has assets to protect. Although a substantial amount of work enhancing BPMN 1.x with security related information already exists, the opportunities provided by version 2.0 have not received much attention in the security community so far. This paper gives an overview of security in BPMN and investigates several possibilities of representing threats in BPMN 2.0, in particular for design-time specification and runtime execution of composite services with dynamic behavior. Enriching BPMN with threat information enables a process-centric threat modeling approach that complements risk assessment and attack scenarios. We have included examples showing the use of error events, escalation events and text annotations for process, collaboration, choreography and conversation diagrams.