Distributed Service Composition Research Articles

Interoperable and network‐aware service workflows for big data executions at internet scale

SummarySharing of computing resources and workload across different big data frameworks is challenging due to their lack of interoperable interfaces. In contrast, web services natively support an interoperable execution. Therefore, an increasing number of big data workflows are composed of data services and web service implementations that access and process big data. On the other hand, big data execution in the wide area networks needs to minimize latency and communication overheads to be able to scale seamlessly. Lack of network‐awareness of classic web service execution beyond data centers significantly challenges the scope of data services.Software‐Defined Networking (SDN) offers better control and management to the network, by unifying the control plane centrally, away from the distributed data plane devices. In this paper, we propose Software‐Defined Data Services (SDDS), an SDN‐based distributed service composition and workflow placement approach for data services in wide area networks. We first present the design of an SDDS framework that models the big data executions as composable data service workflows in multi‐domain network environments. We then evaluate the performance of a prototype SDDS framework through microbenchmarks. The benchmarks highlight the efficiency of SDDS in data service execution inside and beyond data centers.

A Reliable and Efficient Distributed Service Composition Approach in Pervasive Environments

The global, ubiquitous usage of smart handsets and diverse wireless communication tools calls for a meticulous reexamination of complex and dynamic service componentization and remote invocation. In order to satisfy ever-increasing service requirements and enrich users’ experiences, efficient service composition approaches, which leverage the computing resources on nearby devices to form an on-demand composite service, should be developed. This is especially true for situations that are confronted with limited local computing capacity and device mobility. For any mobile pervasive environment, execution reliability and latency of the composite service are major concerns that impact users’ satisfaction. In this paper, we propose a novel three-staged approach which takes reliability and latency into account to solve a distributed service composition efficiently. First, the graph of the functional process description is decomposed into multiple path structures through a graph-traversing algorithm. Second, messages are forwarded among the network nodes (i.e., intelligent handsets) to search for the sub-solutions for these path structures. Finally, an efficient combinatorial optimization algorithm computes the optimal service composition by the selection from these sub-solutions. This approach is validated extensively in static and mobile environments, and the results show the effectiveness and outperformance of this approach over existing approaches.

Structural Process Pattern Matching Based on Graph Morphism Detection

Context: Processes are central to the operation of many systems or organizations. Process-centric systems, ranging from enterprise workflow systems to open distributed service compositions, have significantly increased in number and complexity. Objective: Designers of process-centric systems can benefit from process abstractions (including patterns) capturing and allowing the reuse of designs for frequent operational problems. Existing process patterns detection techniques have efficiency problems and difficulties to identify partial and inexact pattern instances. Method: We propose a process pattern detection technique based on a family of subgraph matching algorithms. The algorithms implement surjective graph morphism detection and a mechanism to incorporate semantic similarity computation for types and attributes of process graph elements. Results: Efficiency is addressed using simplified data structures, reducing the search space and its exploration. Match accuracy and time-complexity are demonstrated in an experimental study. Conclusions: Using process patterns allows business and technical processes to be provided as sharable service resources. Patterns can help to manage processes as configurable resources where a pattern can define a family of concrete customizable processes.

Distributed service-based approach for sensor data fusion in IoT environments.

The Internet of Things (IoT) enables the communication among smart objects promoting the pervasive presence around us of a variety of things or objects that are able to interact and cooperate jointly to reach common goals. IoT objects can obtain data from their context, such as the home, office, industry or body. These data can be combined to obtain new and more complex information applying data fusion processes. However, to apply data fusion algorithms in IoT environments, the full system must deal with distributed nodes, decentralized communication and support scalability and nodes dynamicity, among others restrictions. In this paper, a novel method to manage data acquisition and fusion based on a distributed service composition model is presented, improving the data treatment in IoT pervasive environments.

Software Architectural Patterns for Service Composition

Distributed services provided a new way of distributed computing that achieve the interoperability between heterogonous application through platform and language independent interfaces. The creation of value added services by composition of existing ones is gaining a significant momentum. Distributed service composition is meant to support loose relationships between implemented services in order to provide new functions. A composite service is the one resulting from the integration, coordination and synchronization of different service components. In this paper, we generated A Services Composition Model (SCM) that provides a general solution for the services composition problem by realizing the requirements of a new service using the requirements of the already existing service. We explained in details all the steps of the composition process; services registration, services discovery, services selection, services invoking, and services integration. Although the SCM is not bounded to one particular algorithm to compose services, we generated an application as an example to test our Service Composition Model.

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

We propose an efficient technique for improving the performance of automatic and cooperative compositions in unstructured Peer-to-Peer networks during service discovery. The technique exploits a probabilistic forwarding algorithm that uses different sources of knowledge, such as network density and service grouping, to reduce the amount of messages exchanged in the network. The technique, analysed in several network configurations by using a simulator to observe resolution time, recall and message overhead, presents good performance especially in dense and large-scale service networks.To further improve performance and effectiveness of service discovery, we propose a bidirectional search strategy for distributed service composition. It enables concurrent searches over the Peer-to-Peer network exploring the service space in two search directions, hence reducing the response time when solutions are present; in case the requests for a service cannot be completely satisfied, discovered partial solutions may be analysed to identify service gaps that suggest future service implementations and consequently new opportunities for service providers. This technique further reduces the time for discovering compositions, highlighting only a limited increment, when compared with the unidirectional search, of the number of messages exchanged.

QoS decomposition for service composition using genetic algorithm

Recently, a lot of research has been dedicated to optimizing the QoS-aware service composition. This aims at selecting the optimal composed service from all possible service combinations regarding user's end-to-end quality requirements. Existing solutions often employ the global optimization approach, which does not show promising performance. Also, the complexity of such methods extensively depends on the number of available web-services, which continuously increase along with the growth of the Internet. Besides, the local optimization approaches have been rarely utilized, since they may violate the global constraints. In this paper, we propose a top-down structure, named quality constraints decomposition (QCD) here, to decompose the global constraints into the local constraints, using the genetic algorithm (GA). Then the best web service for each task is selected through a simple linear search. In contrast to existing methods, the QCD approach mainly depends on a limited set of tasks, which is considerably less complex, especially in the case of dynamically distributed service composition. Experimental results, based on a well-known data set of web services (QWSs), show the advantages of the QCD method in terms of computation time, considering the number of web services.

A systematic literature review of service choreography adaptation

A service choreography is a distributed service composition in which services interact without a centralized control. Adequate adaptation strategies are required to face complex and ever-changing business processes, given the collaborative nature of choreographies. Choreographies should also be able to adapt to changes in its non-functional requirements, such as response time, and especially for large-scale choreographies, adaptation strategies need to be automated and scale well. However, the body of knowledge regarding choreography adaptation approaches has not yet been consolidated and systematically evaluated. By means of a systematic literature review, in which we examined seven scientific paper sources, we identified and analyzed the state-of-the-art in choreography adaptation. We found 24 relevant primary studies and grouped them into six categories: model-based, measurement-based, multi-agent-based, formal method-based, semantic reasoning-based, and proxy layer-based. We analyzed (i) how each strategy deals with different types of requirements, (ii) what their required degree of human intervention is, (iii) how the different studies considered scalability, (iv) what implementations are currently available, and (v) which choreography languages are employed. From the selected studies, we extracted key examples of choreography adaptation usage and analyzed the terminology they adopted with respect to dynamic adaptation. We found out that more attention has been devoted to functional requirements and automated adaptation; only one work performs scalability evaluation; and most studies present some sort of implementation and use a specific choreography notation.

A model-driven approach to performance evaluation of ontology-based service composition

The DAML-based Web Service ontology is one of the major standards for modeling and description of distributed service composition. To analyze the performance of composite service processes specified in DAML-S gives the way to tell whether the process meet the performance requirements, and to choose the process with higher efficiency from those with similar function. In this paper, we propose a stochastic-Petri-net-based approach for performance analysis of DAML-S processes, which employs non-markovian-stochastic-petri-nets (SPN) as the intermediate representation. The main innovation of this research includes a translation from DAML-S to non-markovian-stochastic-petri-nets and a performance (using expected-process-normal-completion-time as the metric) analysis method . We also validate the correctness of the approach in the case study by showing 90% confidence intervals obtained from experimental results cover corresponding theoretical prediction values.

A non‐Markovian stochastic Petri net‐based approach to performance evaluation of ontology‐based service composition

SUMMARYThe Ontology Web Language (OWL)‐based web service ontology is one of the major standards for modeling and description of distributed service composition. To analyze the performance of composite service, processes specified in OWL‐S give way to tell whether the process meets the performance requirements and to choose the process with higher efficiency from those with similar function. In this paper, we propose a stochastic Petri net‐based approach for performance analysis of OWL‐S processes, which employs non‐Markovian stochastic Petri nets as the intermediate representation. The main innovation of this research includes a translation from OWL‐S to non‐Markovian stochastic Petri nets and a performance (using expected‐process‐normal‐completion‐time as the metric) analysis method. We also validate the correctness of the approach in the case study by showing 90% CI obtained from experimental results that cover corresponding theoretical prediction values. Copyright © 2012 John Wiley & Sons, Ltd.

A distributed service composition method based on service association

In this paper, a Web service composition architecture based on structured P2P network is proposed. Semantics is used to achieve service accurately matching and user personality customization. Through Web service virtual mapping(WVM) association the fast computing of distributed service composition based on the service function is also implemented. The Web service composition architecture and distributed service composition algorithm proposed in this paper solve a series of existent problems in service discovery and composition in distributed environment, and provide a service composition result meeting user personality requirement. At the same time, they improve the efficiency of service composition calculation.