Towards pattern-based reliability certification of services

On Service-Oriented Architectures (SOAs), the mechanism for run-time discovery and selection of services may conflict with the need to make sure that business process instances satisfy their reliability requirements. In this paper we describe a certification scheme based on machine-readable reliability certificates that will enable run-time negotiation. Service reliability is afforded by means of reliability patterns. Our certificates describe the reliability mechanism implemented by a service and the reliability pattern used to implement such a mechanism. Digital signature is used to associate the reliability claim contained in each certificate with the party (service supplier or accredited third-party) taking responsibility for it

State of runtime adaptation in service-oriented systems:what, where, when, how and right

Software as a Service reflects a ‘service-oriented’ approach to software development that is based on the notion of composing applications by discovering and invoking network-available services to accomplish some task. However, as more business organisations adopt service-oriented solutions and the demands on them grow, the problem of ensuring that the software systems can adapt fast and effectively to changing business needs, changes in their runtime environment and failures in provided services has become an increasingly important research problem. Dynamic adaptation has been proposed as a way to address the problem. However, for adaptation to be effective several other factors need to be considered. This study identifies the key factors that influence runtime adaptation in service-oriented systems (SOSs) and examines how well they are addressed in 29 adaptation approaches intended to support SOSs

A self-learning framework for validation of runtime adaptation in service-oriented systems

Ensuring that service-oriented systems can adapt quickly and effectively to changes in service quality, business needs and their runtime environment is an increasingly important research problem. However, while considerable research has focused on developing runtime adaptation frameworks for service-oriented systems, there has been little work on assessing how effective the adaptations are. Effective adaptation ensures the system remains relevant in a changing environment. One way to address the problem is through validation. Validation allows us to assess how well a recommended adaptation addresses the concerns for which the system is reconfigured and provides us with insights into the nature of problems for which different adaptations are suited. However, the dynamic nature of runtime adaptation and the changeable contexts in which service-oriented systems operate make it difficult to specify appropriate validation mechanisms in advance. This thesis describes a novel consumer-centred approach that uses machine learning to continuously validate and refine runtime adaptation in service-oriented systems, through model-based clustering and deep learning. To evaluate the efficacy of the approach a medium sized health care case study was devised and implemented. The results obtained show that self-validation significantly improves the dynamic adaptation process by autonomously addressing changing user requirements at runtime. Further work in this area can improve the framework by integrating other learning algorithms as well as testing the framework on a larger case study

Towards Self-Adaptation for Dependable Service Oriented Systems

Abstract. Increasingly complex information systems operating in dynamic environments ask for management policies able to deal intelligently and autonomously with problems and tasks. An attempt to deal with these aspects can be found in the Service-Oriented Architecture (SOA) paradigm that foresees the creation of business applications from independently developed services, where services and applications build up complex dependencies. Therefore the dependability of SOA systems strongly depends on their ability to self-manage and adapt themselves to cope with changes in the operating conditions and to meet the required dependability with a minimum of resources. In this paper we propose a model-based approach to the realization of self-adaptable SOA systems, aimed at the fulfillment of dependability requirements. Specifically, we provide a methodology driving the system adaptation and we discuss the architectural issues related to its implementation. To bring this approach to fruition, we developed a prototype tool and we show the results that can be achieved with a simple example.