Mobility and Bandwidth Prediction as a Service in Virtualized LTE Systems

Recently telecommunication industry benefits from infrastructure sharing, one of the most fundamental enablers of cloud computing, leading to emergence of the Mobile Virtual Network Operator (MVNO) concept. The most momentous intents by this approach are the support of on-demand provisioning and elasticity of virtualized mobile network components, based on data traffic load. To realize it, during operation and management procedures, the virtualized services need be triggered in order to scale-up/down or scale-out/in an instance. In this paper we propose an architecture called MOBaaS (Mobility and Bandwidth Availability Prediction as a Service), comprising two algorithms in order to predict user(s) mobility and network link bandwidth availability, that can be implemented in cloud based mobile network structure and can be used as a support service by any other virtualized mobile network services. MOBaaS can provide prediction information in order to generate required triggers for on-demand deploying, provisioning, disposing of virtualized network components. This information can be used for self-adaptation procedures and optimal network function configuration during run-time operation, as well. Through the preliminary experiments with the prototype implementation on the OpenStack platform, we evaluated and confirmed the feasibility and the effectiveness of the prediction algorithms and the proposed architecture.

PROJECTION OF HEALTH DEMAND IN TERMS OF HOSPITAL ADMISSIONS FOR SELECTED DIAGNOSES IN HEALTH SYSTEMS AGENCY SERVICE AREAS

The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^

Analysis of service-oriented computing systems

La computación basada en servicios (Service-Oriented Computing, SOC) se estableció como un paradigma ampliamente aceptado para el desarollo de sistemas de software flexibles, distribuidos y adaptables, donde las composiciones de los servicios realizan las tareas más complejas o de nivel más alto, frecuentemente tareas inter-organizativas usando los servicios atómicos u otras composiciones de servicios. En tales sistemas, las propriedades de la calidad de servicio (Quality of Service, QoS), como la rapídez de procesamiento, coste, disponibilidad o seguridad, son críticas para la usabilidad de los servicios o sus composiciones en cualquier aplicación concreta. El análisis de estas propriedades se puede realizarse de una forma más precisa y rica en información si se utilizan las técnicas de análisis de programas, como el análisis de complejidad o de compartición de datos, que son capables de analizar simultáneamente tanto las estructuras de control como las de datos, dependencias y operaciones en una composición. El análisis de coste computacional para la composicion de servicios puede ayudar a una monitorización predictiva así como a una adaptación proactiva a través de una inferencia automática de coste computacional, usando los limites altos y bajos como funciones del valor o del tamaño de los mensajes de entrada. Tales funciones de coste se pueden usar para adaptación en la forma de selección de los candidatos entre los servicios que minimizan el coste total de la composición, basado en los datos reales que se pasan al servicio. Las funciones de coste también pueden ser combinadas con los parámetros extraídos empíricamente desde la infraestructura, para producir las funciones de los límites de QoS sobre los datos de entrada, cuales se pueden usar para previsar, en el momento de invocación, las violaciones de los compromisos al nivel de servicios (Service Level Agreements, SLA) potenciales or inminentes. En las composiciones críticas, una previsión continua de QoS bastante eficaz y precisa se puede basar en el modelado con restricciones de QoS desde la estructura de la composition, datos empiricos en tiempo de ejecución y (cuando estén disponibles) los resultados del análisis de complejidad. Este enfoque se puede aplicar a las orquestaciones de servicios con un control centralizado del flujo, así como a las coreografías con participantes multiples, siguiendo unas interacciones complejas que modifican su estado. El análisis del compartición de datos puede servir de apoyo para acciones de adaptación, como la paralelización, fragmentación y selección de los componentes, las cuales son basadas en dependencias funcionales y en el contenido de información en los mensajes, datos internos y las actividades de la composición, cuando se usan construcciones de control complejas, como bucles, bifurcaciones y flujos anidados. Tanto las dependencias funcionales como el contenido de información (descrito a través de algunos atributos definidos por el usuario) se pueden expresar usando una representación basada en la lógica de primer orden (claúsulas de Horn), y los resultados del análisis se pueden interpretar como modelos conceptuales basados en retículos. ABSTRACT Service-Oriented Computing (SOC) is a widely accepted paradigm for development of flexible, distributed and adaptable software systems, in which service compositions perform more complex, higher-level, often cross-organizational tasks using atomic services or other service compositions. In such systems, Quality of Service (QoS) properties, such as the performance, cost, availability or security, are critical for the usability of services and their compositions in concrete applications. Analysis of these properties can become more precise and richer in information, if it employs program analysis techniques, such as the complexity and sharing analyses, which are able to simultaneously take into account both the control and the data structures, dependencies, and operations in a composition. Computation cost analysis for service composition can support predictive monitoring and proactive adaptation by automatically inferring computation cost using the upper and lower bound functions of value or size of input messages. These cost functions can be used for adaptation by selecting service candidates that minimize total cost of the composition, based on the actual data that is passed to them. The cost functions can also be combined with the empirically collected infrastructural parameters to produce QoS bounds functions of input data that can be used to predict potential or imminent Service Level Agreement (SLA) violations at the moment of invocation. In mission-critical applications, an effective and accurate continuous QoS prediction, based on continuations, can be achieved by constraint modeling of composition QoS based on its structure, known data at runtime, and (when available) the results of complexity analysis. This approach can be applied to service orchestrations with centralized flow control, and choreographies with multiple participants with complex stateful interactions. Sharing analysis can support adaptation actions, such as parallelization, fragmentation, and component selection, which are based on functional dependencies and information content of the composition messages, internal data, and activities, in presence of complex control constructs, such as loops, branches, and sub-workflows. Both the functional dependencies and the information content (described using user-defined attributes) can be expressed using a first-order logic (Horn clause) representation, and the analysis results can be interpreted as a lattice-based conceptual models.

Inter-organizational information systems adoption for service innovation in building sector

The building sector has experienced a significant decline in recent years in Spain and Europe as a result of the financial crisis that began in 2007. This drop accompanies a low penetration of information and communication technologies in inter-organizational oriented business processes. The market decrease is causing a slowdown in the building sector, where only flexible small and medium enterprises (SMEs) survive thanks to specialization and innovation in services, which allow them to face new market demands. Inter-organizational information systems (IOISs) support innovation in services, and are thus a strategic tool for SMEs to obtain competitive advantage. Because of the inherent complexity of IOIS adoption, this research extends Kurnia and Johnston's (2000) theoretical model of IOIS adoption with an empirical model of IOIS characterization. The resultant model identifies the factors influencing IOIS adoption in SMEs in the building sector, to promote further service innovation for competitive and collaborative advantages. An empirical longitudinal study over six consecutive years using data from Spanish SMEs in the building sector validates the model, using the partial least squares technique and analyzing temporal stability. The main findings of this research are the four ways an IOIS might contribute to service innovation in the building sector. Namely: a) improving client interfaces and the link between service providers and end users; b) defining a specific market where SMEs can develop new service concepts; c) enhancing the service delivery system in traditional customer?supplier relationships; and d) introducing information and communication technologies and tools to improve information management.

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An in-service evaluation of the performance, reliability, maintainability, and durability of antilock braking systems (ABSs) for semitrailers. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Solcost, solar hot water handbook : a simplified design method for sizing and costing residential and commercial solar service hot water systems /

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