Business Grid Services

Grid services have come to represent the synthesis of web services and grid computing paradigms. Web services provide the means to modularize software, enabling loosely coupled and novel synthesis. Grid computing removes the binding between functional software components and specific hosting hardware, enabling software to be deployed dynamically over a network (e.g. intra-, extra- or inter-net). Applying the constructs of grid computing to the service orientation of enterprise software will allow business service networks to utilize more specialized services. An upper service ontology that enables business grid services to be described and then related to the grid hosting platform is presented. Explicit knowledge is required for enterprise software, hosting servers and the domain that can then be utilized by both SLA and reservation systems. The ontology presented is derived from and validated using a collection of web services taken from leading investment banks

Differentiating Web Service Offerings

The advent of Service Oriented Architecture (SOA) paradigm and increasing use of Web Services (WS) implies that the future will see a large number of services transferred between providers and consumers, using many applications or agents working on behalf of humans. Discovering and using the services is the easy part. Negotiating and selecting the best services from amongst the plethora of similar ones, depending on their cost and quality, is the challenging issue. However, existing WS-I standards neither cater to provision of Service Level Agreements (SLAs), nor their exchange between parties. These standards are confined merely to WS description (WSDL). Once WS are discovered and selected, SLAs are merely used to monitor service compliance. We propose a novel method that allows service-providers to dynamically generate the SLAs, and then transfer them to clients for selection amongst competitive service providers. The clients use Application to Application (A2A) communication to choose the best service provider at run time, and then bind to it to available services. Our method complies with all WS-I standards, and hence does not require any modifications to the UDDI or WSDL. Instead of using the SLA as just a contractual document for compliance monitoring of the service, we also use it as a means of service selection. We demonstrate and validate our method using a prototype developed in laboratory settings, which uses multiple ‘Weather Service Providers’ to obtain various indicators for weather forecasting

Modelling Service Level Agreements for Business Process Outsourcing Services

Many proposals to model service level agreements (SLAs) have been elaborated in order to automate different stages of the service lifecycle such as monitoring, implementation or deployment. All of them have been designed for computational services and are not well–suited for other types of services such as business process outsourcing (BPO) services. However, BPO services suported by process–aware information systems could also benefit from modelling SLAs in tasks such as performance monitoring, human resource assignment or process configuration. In this paper, we identify the requirements for modelling such SLAs and detail how they can be faced by combining techniques used to model computational SLAs, business processes, and process performance indicators. Furthermore, our approach has been validated through the modelling of several real BPO SLAsMinisterio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-5906Junta de Andalucía P12-TIC-186

Contribution to the modelling and evaluation of radio network slicing solutions in 5G

Network slicing is a key feature of 5G architecture that allows the partitioning of the network into multiple logical networks, known as network slices, where each of them is customised according to the specific needs of a service or application. Thus, network slicing allows the materialisation of multi-tenant networks, in which a common network infrastructure is shared among multiple communication providers, acting as tenants and each of them using a different network slice. The support of multi-tenancy through slicing in the Radio Access Network (RAN), known as RAN slicing, is particularly challenging because it involves the configuration and operation of multiple and diverse RAN behaviours over the common pool of radio resources available at each of the RAN nodes. Moreover, this configuration needs to be performed in such a way that the specific requirements of each tenant are satisfied and, at the same time, the available radio resources are efficiently used. Therefore, new functionalities that allow the deployment of RAN slices are needed to be introduced at different levels, ranging from Radio Resource Management (RRM) functionalities that incorporate RAN slicing parameters to functionalities that support the lifecycle management of RAN slices. This thesis has addressed this need by proposing, developing and assessing diverse solutions for the support RAN slicing, which has allowed evaluating the capacities, requirements and limitations of network slicing in the RAN from diverse perspectives. Specifically, this thesis is firstly focused on the analytical assessment of RRM functionalities that support multi-tenant and multi-services scenarios, where services are defined according to their 5G QoS requirements. This assessment is conducted through the Markov modelling of admission control policies and the statistical modelling of the resourc allocation, both supporting multiple tenants and multiple services. Secondly, the thesis addresses the problem of slice admission control by proposing a methodology for the estimation of the radio resources required by a RAN slice based on data analytics. This methodology supports the decision on the admission or rejection of new RAN slice creation requests. Thirdly, the thesis explores the potential of artificial intelligence, and specifically, of Deep Reinforcement Learning (DRL) to deal with the capacity sharing problem in RAN slicing scenarios. To this end, a DRL-based capacity sharing solution that distributes the available capacity of a multi-cell scenario among multiple tenants is proposed and assessed. The solution consists in a Multi-Agent Reinforcement Learning (MARL) approach based on Deep Q-Network. Finally, this thesis discuses diverse implementation aspects of the DRL-based capacity sharing solution, including considerations on its compatibility with the standards, the impact of the training on the achieved performance, as well as the tools and technologies required for the deployment of the solution in the real network environment.El Network Slicing és una tecnologia clau de l’arquitectura del 5G que permet dividir la xarxa en múltiples xarxes lògiques, conegudes com a network slices, on cada una es configura d’acord a les necessitats d’un servei o aplicació específic. Així, el network slicing permet la materialització de les xarxes amb múltiples inquilins, on una infraestructura de xarxa comuna es comparteix entre diferents proveïdors de comunicacions, que actuen com a inquilins i utilitzen network slices diferents. El suport de múltiples inquilins mitjançant l’ús del network slicing a la xarxa d’accés ràdio (RAN), que es coneix com a RAN slicing, és un gran repte tecnològic, ja que comporta la configuració i operació de múltiples i diversos comportaments sobre els recursos ràdio disponibles a cadascun dels nodes de la xarxa d’accés. A més a més, aquesta configuració s’ha de portar a terme de forma que els requisits específics de cada inquilí es satisfacin i, al mateix temps, els recursos ràdio disponibles s’utilitzin eficientment. Per tant, és necessari introduir noves funcionalitats a diferents nivells que permetin el desplegament de les RAN slices, des de funcionalitats relacionades amb la gestió dels recursos ràdio (RRM) que incorporin paràmetres per al RAN slicing a funcionalitats que proporcionin suport a la gestió del cicle de vida de les RAN slices. Aquesta tesi ha adreçat aquesta necessitat proposant, desenvolupant i avaluant diverses solucions pel suport del RAN slicing, que han permès analitzar les capacitats, requisits i limitacions del RAN slicing des de diferents perspectives. Específicament, aquesta tesi es centra, en primer lloc, en realitzar una anàlisi de les funcionalitats de RRM que suporten escenaris amb múltiples inquilins i múltiples serveis, on els serveis es defineixen d’acord amb els seus requisits de 5G QoS. Aquesta anàlisi es porta a terme mitjançant la caracterització de polítiques de control d’admissió amb un model de Markov i el modelat estadístic de l’assignació de recursos, ambdós suportant múltiples inquilins i múltiples serveis. En segon lloc, la tesi aborda el problema del control d’admissió de network slices proposant una metodologia per l¿estimació dels recursos requerits per una RAN slice, que es basa en la anàlisi de dades. Aquesta metodologia dona suport a la decisió sobre l’admissió o rebuig de noves sol·licituds de creació de RAN slices. En tercer lloc, la tesi explora el potencial de la intel·ligència artificial, concretament, de les tècniques de Deep Reinforcement Learning (DRL) per a tractar el problema de la compartició de capacitat en escenaris amb RAN slicing. Amb aquest objectiu, es proposa i s’avalua una solució de compartició de capacitat basada en DRL que distribueix la capacitat disponible en un escenari multicel·lular entre múltiples inquilins. Aquesta solució es planteja com una solución de Multi-Agent Reinforcement Learning (MARL) basat en Deep Q-Network. Finalment, aquesta tesi tracta diversos aspectes relacionats amb la implementació de la solució de compartició de capacitat basada en DRL, incloent-hi consideracions sobre la compatibilitat de la solució amb els estàndards, l’impacte de l’entrenament de la solució al seu comportament i rendiment, així com les eines i tecnologies necessàries per al desplegament de la solució en un entorn de xarxa real.El Network Slicing es una tecnología clave de la arquitectura del 5G que permite dividir la red en múltiples redes lógicas, conocidas como network slices, que se configuran de acuerdo a las necesidades de servicios y aplicaciones específicas. Así, el network slicing permite la materialización de las redes con múltiples inquilinos, donde una infraestructura de red común se comparte entre diferentes proveedores de comunicaciones, que actúan como inquilinos y que usan network slices diferentes. El soporte de múltiples inquilinos mediante el uso del network slicing en la red de acceso radio (RAN), que se conoce como RAN slicing, es un gran reto tecnológico, ya que comporta la configuración y operación de múltiples y diversos comportamientos sobre los recursos radio disponibles en cada uno de los nodos de la red de acceso. Además, esta configuración debe realizarse de tal manera que los requisitos específicos de cada inquilino se satisfagan y, al mismo tiempo, los recursos radio disponibles se utilicen eficazmente. Por lo tanto, es necesario introducir nuevas funcionalidades a diferentes niveles que permitan el despliegue de las RAN slices, desde funcionalidades relacionadas con la gestión de recursos radio (RRM) que incorporen parámetros para el RAN slicing a funcionalidades que proporcionen soporte a la gestión del ciclo de vida de las RAN slices. Esta tesis ha abordado esta necesidad proponiendo, desarrollando y evaluando diversas soluciones para el soporte del RAN slicing, lo que ha permitido analizar las capacidades, requisitos y limitaciones del RAN slicing desde diversas perspectivas. Específicamente, esta tesis se centra, en primer lugar, en realizar un análisis de funcionalidades de RRM que soportan escenarios con múltiples inquilinos y múltiples servicios, donde los servicios se definen según sus requisitos de 5G QoS. Este análisis se lleva a cabo mediante la caracterización de políticas de control de admisión mediante un modelo de Markov y el modelado a nivel estadístico de la asignación de recursos, ambos soportando múltiples inquilinos y múltiples servicios. En segundo lugar, la tesis aborda el problema del control de admisión de network slices proponiendo una metodología para la estimación de los recursos radio requeridos por una RAN slice que se basa en análisis de datos. Esta metodología da soporte a la decisión sobre la admisión o el rechazo de nuevas solicitudes de creación de RAN slice. En tercer lugar, la tesis explora el potencial de la inteligencia artificial, y en concreto, de las técnicas de Deep Reinforcement Learning (DRL) para tratar el problema de compartición de capacidad en escenarios de RAN slicing. Para ello, se propone y evalúa una solución de compartición de capacidad basada en DRL que distribuye la capacidad disponible de un escenario multicelular entre múltiples inquilinos. Esta solución se plantea como una solución de Multi-Agent Reinforcement Learning (MARL) basado en Deep Q-Network. Finalmente, en esta tesis se tratan diversos aspectos relacionados con la implementación de la solución de reparto de capacidad basada en DRL, incluyendo consideraciones sobre su compatibilidad con los estándares, el impacto del entrenamiento en el comportamiento y rendimiento conseguido, así como las herramientas y tecnologías necesarias para su despliegue en un entorno de red real.Postprint (published version

E2SP. The Business Case of an Environmental Information System for Decision Support in ASP Mode

According to PSR (OECD) and DPSIR (EEA) models, Environmental Agencies are in charge of measuring the State and Pressure and evaluate the Impact in order to define the most suitable Responses; this implies data analysis and reporting activities, as one of their core responsibilities. Environmental Information Systems (EIS) support these activities by combining the advantages of first-rate consolidated technology (such asBusiness Intelligence and Data Warehouses) to specific technical architectures tailored to environmental management tasks. E2SP (Environmental Enterprise Service Provider) is a online reporting and forecasting platform, providing a cost effective, Internet based EIS and Decision Support System in ASP (Application Service Provider) mode. Tasks such as data integration, data analysis through OLAP (On Line Analytical Processing), impact analysis and forecasts through mathematical models, emission inventories, indices/indicators calculation, reporting, are supplied in an integrated environment as on line services to public authorities and private industries. E2SP project, funded by the eTEN program of the European Commission, allowed to deploy two service centres and to develop the business case study, described in this paper, to verify the viability of the ASP approach to EIS in a trans-national context, starting from the air quality theme

Tradable Service Level Agreements to Manage Network Resources for Streaming Internet Services

In recent years, supply and demand of streaming applications via the Internet (e.g., video-on-demand, live TV coverage, video conferencing) have increased. The idea behind streaming Internet services is to avoid a time-consuming download, and instead, make the user view streaming content in real-time without delay. However, today’s Internet traffic is routed on a best effort basis without any support for guaranteed service provisioning. Missing traffic prioritization mechanisms to guarantee Quality of Service (QoS) and, additionally, the fact that traffic passes several Internet Service Providers (ISP) during transmission is very disadvantageous for the performance of streaming Internet services. Therefore, a solution is presented to enhance existing protocols with QoS mechanisms. Service Level Agreements (SLA) and Operational Level Agreements (OLA) between service providers and service customers are proposed to enforce service guarantees on an economic base and they serve ISPs and Content Service Providers (CSP) to efficiently manage network resources. The concatenation of such contractual agreements between ISPs enables end-to-end-based service provisioning with QoS assurance. A contracting protocol is introduced to control the settlement of contracts and user demands. With the help of service brokers, SLAs could even be traded in a marketplace established for efficient use of limited resources