Runtime Behavior Monitoring and Self-Adaptation in Service-Oriented Systems

Service-Oriented Computing

Mietzner

et al. 2011

Self Cite

Abstract. Large-scale and complex distributed systems are increasingly implemented as SOAs. These comprise diverse types of components, e.g., Web services, registries, workflow engines, and services buses, that interact with each others to establish composite functionality. The drawback of this trend is that testing of complex SOAs becomes a challenging task. During the development phase, testers must verify the system's correct functionality, but often do not have access to adequate testbeds. In this paper, we present an approach for solving this issue. We combine the Genesis2 testbed generator, that emulates SOA environments, with Cafe, a framework for provisioning of component-based applications in the cloud. Our approach allows to model large-scale service-based testbed infrastructures, to specify their behavior, and to deploy these automatically in the cloud. As a result, testers can emulate required environments on-demand for evaluating SOAs at runtime.

Section: Cage Methodology and Rolesmentioning

confidence: 99%

CAGE: Customizable Large-Scale SOA Testbeds in the Cloud

Juszczyk

Service-Oriented Computing

Mietzner

et al. 2011

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“…For this purpose, we utilise a testbed generator framework called Genesis2 enhanced with additional adaptation capabilities (Psaier et al, 2010). The next step in the evaluation process is to define the behaviour of actors in the testbed.…”

Section: Crowdsourcing Evaluation Environmentmentioning

confidence: 99%

“…In our previous work we introduced the building blocks for mixed service-oriented systems (also known as socially-enhanced services computing). The building blocks include: human-provided services (HPS) (Schall et al, 2008) and the HPS framework (Schall, 2011), metrics and a socially-aware reputation algorithm , trust inference techniques and behaviour-based network adaptation (Psaier et al, 2010). The idea of our previously performed work was to realise a feedback cycle; in a manner similar to the monitoring, analysing, planing and execution (MAPE) loop as known in control theory; to monitor, analyse and adjust interaction styles between actors at runtime.…”

Section: Introductionmentioning

confidence: 99%

Formation and interaction patterns in social crowdsourcing environments

2013

IJCNDS

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Abstract:Over the past years, the web has transformed from a pool of statically linked information to a people-centric web. Various web-based tools and social services have become available enabling people to communicate, coordinate, and collaborate in a distributed manner. In this work, we consider social crowdsourcing environments that are based on the capabilities of human-provided services (HPS) and software-based services (SBS). Unlike traditional crowdsourcing platforms, we consider collaborative environments where people and software services jointly perform tasks. We propose formation and interaction patterns that are based on social principles. The idea of our social crowdsourcing approach is that interactions emerge dynamically at runtime based on social preferences among actors. The evolution of interactions is guided by a monitoring and control feedback cycle to recommend competitive compositions and to adjust interaction behaviour. Here we present fundamental formation patterns including link mesh and broker-based formations. We discuss the prototype implementation of our service-oriented crowdsourcing framework.

“…Therefore, in this paper, we revisit the interaction monitoring concept in SOA environments from a technical point of view; deal with service descriptions in terms of functional and non-functional properties to support the discovery process; and demonstrate how to enable run-time adaptations in the Genesis hosting environment (see also [12]). …”

Section: Monitoringmentioning

confidence: 99%

Adaptive provisioning of human expertise in service-oriented systems

Skopik

Proceedings of the 2011 ACM Symposium on Applied Computing

Psaier

et al. 2011

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Web-based collaborations have become essential in today's business environments. Due to the availability of various SOA frameworks, Web services emerged as the de facto technology to realize flexible compositions of services. While most existing work focuses on the discovery and composition of software based services, we highlight concepts for a people-centric Web. Knowledge-intensive environments clearly demand for provisioning of human expertise along with sharing of computing resources or business data through software-based services. To address these challenges, we introduce an adaptive approach allowing humans to provide their expertise through services using SOA standards, such as WSDL and SOAP. The seamless integration of humans in the SOA loop triggers numerous social implications, such as evolving expertise and drifting interests of human service providers. Here we propose a framework that is based on interaction monitoring techniques enabling adaptations in SOA-based socio-technical systems.