Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin

Statistical Delay Bound for WirelessHART Networks

In this paper we provide a performance analysis framework for wireless industrial networks by deriving a service curve and a bound on the delay violation probability. For this purpose we use the (min,x) stochastic network calculus as well as a recently presented recursive formula for an end-to-end delay bound of wireless heterogeneous networks. The derived results are mapped to WirelessHART networks used in process automation and were validated via simulations. In addition to WirelessHART, our results can be applied to any wireless network whose physical layer conforms the IEEE 802.15.4 standard, while its MAC protocol incorporates TDMA and channel hopping, like e.g. ISA100.11a or TSCH-based networks. The provided delay analysis is especially useful during the network design phase, offering further research potential towards optimal routing and power management in QoS-constrained wireless industrial networks.Comment: Accepted at PE-WASUN 201

A QoS-Aware BPEL Framework for Service Selection and Composition Using QoS Properties

Abstract—The promise of service oriented computing, and the availability of web services in particular, promote delivery of services and creation of new services composed of existing services – service components are assembled to achieve integrated computational goals. Business organizations strive to utilize the services and to provide new service solutions and they will need appropriate tools to achieve these goals. As web and internet based services grow into clouds, inter-dependency of services and their complexity increases tremendously. The cloud ontology depicts service layers from a high-level, such as Application and Software, to a low-level, such as Infrastructure and Platform. Each component resides at one layer can be useful to others as a service. It hints the amount of complexity resulting from not only horizontal but also vertical integrations in building and deploying a composite service. Our framework tackles the complexity of the selection and composition issues with additional qualitative information to the service descriptions using Business Process Execution Language (BPEL). Engineers can use BPEL to explore design options, and have the QoS properties analyzed for the design. QoS properties of each service are annotated with our extension to Web Service Description Language (WSDL). In this paper, we describe our framework and illustrate its application to one QoS property, performance. We translate BPEL orchestration and choreography into appropriate queuing networks, and analyze the resulting model to obtain the performance properties of the composed service. Our framework is also designed to support utilizations of other QoS extensions of WSDL, adaptable business logic languages, and composition models for other QoS properties

Performability Evaluation of Voice Services in Converged Networks

In the last years, the transmission of voice services in converged networks has experienced a huge growth. However, there are still some questions considering the ability of these networks to deliver voice services with acceptable quality. In this paper, we applied analytical modeling and simulation to analyze the quality of voice services using a new index, called MOS a , which considers jointly the MOS index and the availability of the subjacent infrastructure. We consider the influence of different CODECs (G.711 and G.729), queuing policies (Priority Queuing and Custom Queuing), and the warm standby redundancy mechanism. Our goal is to analyze the quality of these services by taking into account overloading conditions in different  architectures/scenarios. These scenarios were constructed using the modeling mechanisms Reliability Block Diagram and Stochastic Petri Nets in addition to a discrete event simulator. Experimental results indicate that the G.711 CODEC has a higher sensitivity both in terms of data traffic volume and allocated network resources in relation to the G.729 CODEC

Compositional Performance Modelling with the TIPPtool

Stochastic process algebras have been proposed as compositional specification formalisms for performance models. In this paper, we describe a tool which aims at realising all beneficial aspects of compositional performance modelling, the TIPPtool. It incorporates methods for compositional specification as well as solution, based on state-of-the-art techniques, and wrapped in a user-friendly graphical front end. Apart from highlighting the general benefits of the tool, we also discuss some lessons learned during development and application of the TIPPtool. A non-trivial model of a real life communication system serves as a case study to illustrate benefits and limitations

Proceedings of the First Karlsruhe Service Summit Workshop - Advances in Service Research, Karlsruhe, Germany, February 2015 (KIT Scientific Reports ; 7692)

Since April 2008 KSRI fosters interdisciplinary research in order to support and advance the progress in the service domain. KSRI brings together academia and industry while serving as a European research hub with respect to service science. For KSS2015 Research Workshop, we invited submissions of theoretical and empirical research dealing with the relevant topics in the context of services including energy, mobility, health care, social collaboration, and web technologies

Modelling the operational effects of deploying and retrieving a fleet of uninhabited vehicles on the design of dedicated naval surface ships

Uninhabited vehicles (UXVs) are becoming an important component of naval warfare, providing an entirely new capability. By projecting military power in a more affordable way, through the use of UXVs, exposure of human life to military threats should be significantly reduced. While several navies are employing UXVs for a variety of applications, the concept of operating a fleet of such vehicles from a mothership that supports their overall operations during a mission, is a further challenge. This paper describes the research conducted by University College London (UCL) Design Research Centre (DRC) to develop and demonstrate a relevant analytical approach to design a mothership supporting a fleet of UXVs. This research should provide ship designers with the basis for early stage assessment of the impact of the various facilities seen as appropriate to host and support a substantial fleet of UXVs. It is particularly focused on the Launch and Recovery (LAR) capability of the UXV mothership. The research explored various options to demonstrate the proposed approach, rather than producing a definitive mothership design solution. This was appropriate given the fact that any UXV fleet composition is hard to predict (since mission related) and UXV technology is rapidly developing, so both must be speculative. It was found that the QT tool could provide meaningful investigation into the impact of potential tasks to be undertaken by a fleet of UXVs, addressing the design of mission bays, which were shown to be key to USV mothership design. While more focused simulations could refine subsystem options, this was not pursued, given the technology is still developing. Consequently, at this very early stage of investigating the deployment of a fleet of USVs from surface ships (through case studies), queuing network theory was seen to be more appropriate than a simulation-based analysis for this initial exploratory and investigatory work on future naval deployment of UXVs