Composition and Self-Adaptation of Service-Based Systems with Feature Models

The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932, TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Information systems for adaptive shariah compliant financial services: defining adaptation constructs

Asymmetry of information in financial service creates excessive uncertainty termed gharar, which makes a financial transaction invalid (haram) in Islamic Law (Shariah). Information systems customised to shariah compliant financial service (SCFS) can make information flow more symmetric and can in turn reduce gharar. Based on information related to emergent SCFS design stakeholders i.e. financial regulators, bankers and customers make adaptation and migration decisions. However, unique nature of SCFS design requires adaptation (migration) of emergent SCFS in compliance to shariah. We discuss general service and SCFS literatures to define structural constructs of SCFS. We then discuss qiyas, which is the juridical principle of defining emergence for expansion in shariah rulings, and theory of deferred action, which is a design adaptability theory drawing in complexity. The adaptation construct for SCFS designs is defined and discussed in the joint framework of qiyas and theory of deferred action

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings

Designing and Adapting Service-based Systems: A Service Discovery Framework

This chapter describes a service discovery framework that has been developed within the EU 6th Framework projects SeCSE and Gredia. The framework supports design of service-based systems based on existing services and adaptation of service based systems during their execution due to different situations. It assumes services described from different perspectives and uses complex service discovery queries specified in a XML-based language that we have developed. The work is illustrated with the Cell Phone Operator case study

Conceptualizing smart service systems.

Recent years have seen the emergence of physical products that are digitally networked with other products and with information systems to enable complex business scenarios in manufacturing, mobility, or healthcare. These "smart products", which enable the co-creation of "smart service" that is based on monitoring, optimization, remote control, and autonomous adaptation of products, profoundly transform service systems into what we call "smart service systems". In a multi-method study that includes conceptual research and qualitative data from in-depth interviews, we conceptualize "smart service" and "smart service systems" based on using smart products as boundary objects that integrate service consumers' and service providers' resources and activities. Smart products allow both actors to retrieve and to analyze aggregated field evidence and to adapt service systems based on contextual data. We discuss the implications that the introduction of smart service systems have for foundational concepts of service science and conclude that smart service systems are characterized by technology-mediated, continuous, and routinized interactions

On-Demand Composition of Smart Service Systems in Decentralized Environments

The increasing number of smart systems inevitably leads to a huge number of systems that potentially provide independently designed, autonomously operating services. In near-future smart computing systems, such as smart cities, smart grids or smart mobility, independently developed and heterogeneous services need to be dynamically interconnected in order to develop their full potential in a rather complex collaboration with others. Since the services are developed independently, it is challenging to integrate them on-the-fly at run time. Due to the increasing degree of distribution, such systems operate in a decentralized and volatile environment, where central management is infeasible. Conversely, the increasing computational power of such systems also supersedes the need for central management. The four identified key problems of adaptable, collaborative Smart Service Systems are on-demand composition of complex service structures in decentralized environments, the absence of a comprehensive, serendipity-aware specification, a discontinuity from design-time specification to run-time execution, and the lack of a development methodology that separates the development of a service from that of its role essential to a collaboration. This approach utilizes role-based models, which have a collaborative nature, for automated, on-demand service composition. A rigorous two-phase development methodology is proposed in order to demarcate the development of the services from that of their role essential to a collaboration. Therein, a collaboration designer specifies the collaboration including its abstract functionality using the proposed role-based collaboration specification for Smart Service Systems. Thereof, a partial implementation is derived, which is complemented by services developed in the second phase. The proposed middleware architecture provides run-time support and bridges the gap between design and run time. It implements a protocol for coordinated, role-based composition and adaptation of Smart Service Systems. The approach is quantitatively and qualitatively evaluated by means of a case study and a performance evaluation in order to identify limitations of complex service structures and the trade-off of employing the concept of roles for composition and adaptation of Smart Service Systems.:1 Introduction 1.1 Motivation 1.2 Terminology 1.3 Problem Statement 1.4 Requirements Analysis 1.5 Research Questions and Hypothesis 1.6 Focus and Limitations 1.7 Outline 2 The Role Concept in Computer Science 2.1 What is a Role in Computer Science? 2.2 Roles in RoleDiSCo 3 State of the Art & Related Work 3.1 Role-based Modeling Abstractions for Software Systems 3.1.1 Classification 3.1.2 Approaches 3.1.3 Summary 3.2 Role-based Run-Time Systems 3.2.1 Classification 3.2.2 Approaches 3.2.3 Summary 3.3 Spontaneously Collaborating Run-Time Systems 3.3.1 Classification 3.3.2 Approaches 3.3.3 Summary 3.4 Summary 4 On-Demand Composition and Adaptation of Smart Service Systems 4.1 RoleDiSCo Development Methodology 4.1.1 Role-based Collaboration Specification for Smart Service Systems 4.1.2 Derived Partial Implementation 4.1.3 Player & Context Provision 4.2 RoleDiSCo Middleware Architecture for Smart Service Systems 4.2.1 Infrastructure Abstraction Layer 4.2.2 Context Management 4.2.3 Local Repositories & Knowledge 4.2.4 Discovery 4.2.5 Dispatcher 4.3 Coordinated Composition and Subsequent Adaptation 4.3.1 Initialization and Planning 4.3.2 Composition: Coordinating Subsystem 4.3.3 Composition: Non-Coordinating Subsystem 4.3.4 Competing Collaborations & Negotiation 4.3.5 Subsequent Adaptation 4.3.6 Terminating a Pervasive Collaboration 4.4 Summary 5 Implementing RoleDiSCo 5.1 RoleDiSCo Development Support 5.2 RoleDiSCo Middleware 5.2.1 Infrastructure Abstraction Layer 5.2.2 Knowledge Repositories and Local Class Discovery 5.2.3 Planner 6 Evaluation 6.1 Case Study: Distributed Slideshow 6.1.1 Scenario 6.1.2 Phase 1: Collaboration Design 6.1.3 Phase 2: Player Complementation 6.1.4 Coordinated Composition and Adaptation at Run Time 6.2 Runtime Evaluation 6.2.1 General Testbed Setup and Scenarios 6.2.2 Discovery Time 6.2.3 Composition Time 6.2.4 Discussion 6.3 The ›Role‹ of Roles 6.4 Summary 7 Conclusion 7.1 Summary 7.2 Research Results 7.3 Future Wor

Automatic Adaptation of SOA Systems Supported by Machine Learning

Part 3: Service OrientationInternational audienceRecent advances in the development of information systems have led to increased complexity and cost in terms of the required maintenance and management. On the other hand, systems built in accordance with modern architectural paradigms, such as Service Oriented Architecture (SOA), posses features enabling extensive adaptation, not present in traditional systems. Automatic adaptation mechanisms can be used to facilitate system management. The goal of this work is to show that automatic adaptation can be effectively implemented in SOA systems using machine learning algorithms. The presented concept relies on a combination of clustering and reinforcement learning algorithms. The paper discusses assumptions which are necessary to apply machine learning algorithms to automatic adaptation of SOA systems, and presents a machine learning-based management framework prototype. Possible benefits and disadvantages of the presented approach are discussed and the approach itself is validated with a representative case study

QoS-driven proactive adaptation of service composition

Proactive adaptation of service composition has been recognized as a major research challenge for service-based systems. In this paper we describe an approach for proactive adaptation of service composition due to changes in service operation response time; or unavailability of operations, services, and providers. The approach is based on exponentially weighted moving average (EWMA) for modelling service operation response time. The prediction of problems and the need for adaptation consider a group of services in a composition flow, instead of isolated services. The decision of the service operations to be used to replace existing operations in a composition takes into account response time and cost values. A prototype tool has been implemented to illustrate and evaluate the approach. The paper also describes the results of a set of experiments that we have conducted to evaluate the work