1,395 research outputs found

    Challenges in Complex Systems Science

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    FuturICT foundations are social science, complex systems science, and ICT. The main concerns and challenges in the science of complex systems in the context of FuturICT are laid out in this paper with special emphasis on the Complex Systems route to Social Sciences. This include complex systems having: many heterogeneous interacting parts; multiple scales; complicated transition laws; unexpected or unpredicted emergence; sensitive dependence on initial conditions; path-dependent dynamics; networked hierarchical connectivities; interaction of autonomous agents; self-organisation; non-equilibrium dynamics; combinatorial explosion; adaptivity to changing environments; co-evolving subsystems; ill-defined boundaries; and multilevel dynamics. In this context, science is seen as the process of abstracting the dynamics of systems from data. This presents many challenges including: data gathering by large-scale experiment, participatory sensing and social computation, managing huge distributed dynamic and heterogeneous databases; moving from data to dynamical models, going beyond correlations to cause-effect relationships, understanding the relationship between simple and comprehensive models with appropriate choices of variables, ensemble modeling and data assimilation, modeling systems of systems of systems with many levels between micro and macro; and formulating new approaches to prediction, forecasting, and risk, especially in systems that can reflect on and change their behaviour in response to predictions, and systems whose apparently predictable behaviour is disrupted by apparently unpredictable rare or extreme events. These challenges are part of the FuturICT agenda

    Network resilience

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    Many systems on our planet are known to shift abruptly and irreversibly from one state to another when they are forced across a "tipping point," such as mass extinctions in ecological networks, cascading failures in infrastructure systems, and social convention changes in human and animal networks. Such a regime shift demonstrates a system's resilience that characterizes the ability of a system to adjust its activity to retain its basic functionality in the face of internal disturbances or external environmental changes. In the past 50 years, attention was almost exclusively given to low dimensional systems and calibration of their resilience functions and indicators of early warning signals without considerations for the interactions between the components. Only in recent years, taking advantages of the network theory and lavish real data sets, network scientists have directed their interest to the real-world complex networked multidimensional systems and their resilience function and early warning indicators. This report is devoted to a comprehensive review of resilience function and regime shift of complex systems in different domains, such as ecology, biology, social systems and infrastructure. We cover the related research about empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also discuss some ambiguous definitions, such as robustness, resilience, and stability.Comment: Review chapter

    Perspectives on adaptive dynamical systems

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    Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges, and give perspectives on future research directions, looking to inspire interdisciplinary approaches.Comment: 46 pages, 9 figure

    A framework for the dynamic management of Peer-to-Peer overlays

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    Peer-to-Peer (P2P) applications have been associated with inefficient operation, interference with other network services and large operational costs for network providers. This thesis presents a framework which can help ISPs address these issues by means of intelligent management of peer behaviour. The proposed approach involves limited control of P2P overlays without interfering with the fundamental characteristics of peer autonomy and decentralised operation. At the core of the management framework lays the Active Virtual Peer (AVP). Essentially intelligent peers operated by the network providers, the AVPs interact with the overlay from within, minimising redundant or inefficient traffic, enhancing overlay stability and facilitating the efficient and balanced use of available peer and network resources. They offer an “insider‟s” view of the overlay and permit the management of P2P functions in a compatible and non-intrusive manner. AVPs can support multiple P2P protocols and coordinate to perform functions collectively. To account for the multi-faceted nature of P2P applications and allow the incorporation of modern techniques and protocols as they appear, the framework is based on a modular architecture. Core modules for overlay control and transit traffic minimisation are presented. Towards the latter, a number of suitable P2P content caching strategies are proposed. Using a purpose-built P2P network simulator and small-scale experiments, it is demonstrated that the introduction of AVPs inside the network can significantly reduce inter-AS traffic, minimise costly multi-hop flows, increase overlay stability and load-balancing and offer improved peer transfer performance

    Network Behavior in Thin Film Growth Dynamics

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    Understanding patterns and components in thin film growth is crucial for many engineering applications. Further, the growth dynamics (e.g., shadowing and re-emission effects) of thin films exist in several other natural and man-made phenomena. Recent work developed network science techniques to study the growth dynamics of thin films and nanostructures. These efforts used a grid network model (i.e. viewing of each point on the thin film as an intersection point of a grid) via Monte Carlo simulation methods to study the shadowing and re-emission effects in the growth. These effects are crucial in understanding the relationships between growth dynamics and the resulting structural properties of the film to be grown. In this dissertation, we use a cluster-based network model with Monte Carlo simulation method to study these effects in thin film growth. We use image processing to identify clusters of points on the film and establish a network model of these clusters. Monte Carlo simulations are used to grow films and dynamically track the trajectories of re-emitted particles. We treat the points on the film substrate and cluster formations from the deposition of adatoms / particles on the surface of the substrate as the nodes of network, and movement of particles between these points or clusters as the traffic of the network. Then, graph theory is used to study various network statistics and characteristics that would explain various important phenomena in the thin film growth. We compare the cluster-based results with the grid-based results to determine which method is better suited to study the underlying characteristics of the thin film. Based on the clusters and the points on the substrate, we also develop a network traffic model to study the characteristics and phenomena like fractal behavior in the count and inter-arrival time of the particles. Our results show that the network theory of the growth process explains some of the underlying phenomena in film growth better than the existing theoretical and statistical models

    New Challenges on Web Architectures for the Homogenization of the Heterogeneity of Smart Objects in the Internet of Things

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    Aquesta tesi tracta de dues de les noves tecnologies relacionades amb la Internet of Things (IoT) i la seva integraciĂł amb el camp de les Smart Grids (SGs); aquestes tecnologies son la Web of Things (WoT) i la Social Internet of Things (SIoT). La WoT Ă©s una tecnologia que s’espera que proveeixi d’un entorn escalable i interoperable a la IoT usant la infraestructura web existent, els protocols web y la web semĂ ntica. TambĂ© s’espera que la SIoT contribueixi a solucionar els reptes d’escalabilitat i capacitat de descobriment creant una xarxa social d’agents (objectes i humans). Per explorar la sinergia entre aquestes tecnologies, l’objectiu Ă©s el de proporcionar evidĂšncia prĂ ctica i empĂ­rica, generalment en forma de prototips d’implementaciĂł i experimentaciĂł empĂ­rica. En relaciĂł amb la WoT i les SGs, s’ha creat un prototip per al Web of Energy (WoE) que tĂ© com a objectiu abordar els desafiaments presents en el domini les SGs. El prototip Ă©s capaç de proporcionar interoperabilitat i homogeneĂŻtat entre diversos protocols. El disseny d’implementaciĂł es basa en el Model d’Actors, que tambĂ© proporciona escalabilitat del prototip. L’experimentaciĂł mostra que el prototip pot gestionar la transmissiĂł de missatges per a aplicacions de les SGs que requereixen que la comunicaciĂł es realitzi sota llindars de temps crĂ­tics. TambĂ© es pren una altra direcciĂł d’investigaciĂł similar, menys centrada en les SGs, perĂČ per a una gamma mĂ©s Ă mplia de dominis d’aplicaciĂł. S’integra la descripciĂł dels fluxos d’execuciĂł com a mĂ quines d’estats finits utilitzant ontologies web (Resource Description Framework (RDF)) i metodologies de la WoT (les accions es realitzen basant-se en peticions Hyper-Text Transfer Protocol/Secure (HTTP/S) a Uniform Resource Locators (URLs)). Aquest flux d’execuciĂł, que tambĂ© pot ser un plantilla per a permetre una configuraciĂł flexible en temps d’execuciĂł, s’implementa i interpreta com si fos (i mitjançant) un Virtual Object (VO). L’objectiu de la plantilla Ă©s ser reutilitzable i poder-se compartir entre mĂșltiples desplegaments de la IoT dins el mateix domini d’aplicaciĂł. A causa de les tecnologies utilitzades, la soluciĂł no Ă©s adequada per a aplicacions de temps crĂ­tic (llindar de temps relativament baix i rĂ­gid). No obstant aixĂČ, Ă©s adequat per a aplicacions que no demanden resposta en un temps crĂ­tic i que requereixen el desplegament de VOs similars en el que fa referĂšncia al flux d’execuciĂł. Finalment, el treball s’enfoca en una altra tecnologia destinada a millorar l’escalabilitat i la capacitat de descobriment en la IoT. La SIoT estĂ  sorgint com una nova estructura de la IoT que uneix els nodes a travĂ©s de relacions significatives. Aquestes relacions tenen com a objectiu millorar la capacitat de descobriment; en conseqĂŒĂšncia, millora la escalabilitat d’una xarxa de la IoT. En aquest treball s’aplica aquest nou paradigma per optimitzar la gestiĂł de l’energia en el costat de la demanda a les SGs. L’objectiu Ă©s aprofitar les caracterĂ­stiques de la SIoT per ajudar a la creaciĂł de Prosumer Community Groups (PCGs) (grups d’usuaris que consumeixen o produeixen energia) amb el mateix objectiu d’optimitzaciĂł en l’Ășs de l’energia. La sinergia entre la SIoT i les SGs s’ha anomenat Social Internet of Energy (SIoE). Per tant, amb la SIoE i amb el focus en un desafiament especĂ­fic, s’estableix la base conceptual per a la integraciĂł entre la SIoT i les SGs. Els experiments inicials mostren resultats prometedors i aplanen el camĂ­ per a futures investigacions i avaluacions de la proposta. Es conclou que el WoT i la SIoT sĂłn dos paradigmes complementaris que nodreixen l’evoluciĂł de la propera generaciĂł de la IoT. S’espera que la propera generaciĂł de la IoT sigui un Multi-Agent System (MAS) generalitzat. Alguns investigadors ja estan apuntant a la Web i les seves tecnologies (per exemple, Web SemĂ ntica, HTTP/S)—i mĂ©s concretamente a la WoT — com a l’entorn que nodreixi a aquests agents. La SIoT pot millorar tant l’entorn com les relacions entre els agents en aquesta fusiĂł. Les SGs tambĂ© poden beneficiar-se dels avenços de la IoT, ja que es poden considerar com una aplicaciĂł especĂ­fica d’aquesta Ășltima.  Esta tesis trata de dos de las novedosas tecnologĂ­as relacionadas con la Internet of Things (IoT) y su integraciĂłn con el campo de las Smart Grids (SGs); estas tecnologĂ­as son laWeb of Things (WoT) y la Social Internet of Things (SIoT). La WoT es una tecnologĂ­a que se espera que provea de un entorno escalable e interoperable a la IoT usando la infraestructura web existente, los protocolos web y la web semĂĄntica. TambiĂ©n se espera que la SIoT contribuya a solucionar los retos de escalabilidad y capacidad de descubrimiento creando una red social de agentes (objetos y humanos). Para explorar la sinergia entre estas tecnologĂ­as, el objetivo es el de proporcionar evidencia prĂĄctica y empĂ­rica, generalmente en forma de prototipos de implementaciĂłn y experimentaciĂłn empĂ­rica. En relaciĂłn con la WoT y las SGs, se ha creado un prototipo para la Web of Energy (WoE) que tiene como objetivo abordar los desafĂ­os presentes en el dominio las SGs. El prototipo es capaz de proporcionar interoperabilidad y homogeneidad entre diversos protocolos. El diseño de implementaciĂłn se basa en el Modelo de Actores, que tambiĂ©n proporciona escalabilidad del prototipo. La experimentaciĂłn muestra que el prototipo puede manejar la transmisiĂłn de mensajes para aplicaciones de las SGs que requieran que la comunicaciĂłn se realice bajo umbrales de tiempo crĂ­ticos. TambiĂ©n se toma otra direcciĂłn de investigaciĂłn similar, menos centrada en las SGs, pero para una gama mĂĄs amplia de dominios de aplicaciĂłn. Se integra la descripciĂłn de los flujos de ejecuciĂłn como mĂĄquinas de estados finitos utilizando ontologĂ­as web (Resource Description Framework (RDF)) y metodologĂ­as de la WoT (las acciones se realizan basĂĄndose en peticiones Hyper-Text Transfer Protocol/Secure (HTTP/S) a Uniform Resource Locators (URLs)). Este flujo de ejecuciĂłn, que tambiĂ©n puede ser una plantilla para permitir una configuraciĂłn flexible en tiempo de ejecuciĂłn, se implementa e interpreta como si fuera (y a travĂ©s de) un Virtual Object (VO). El objetivo de la plantilla es que sea reutilizable y se pueda compartir entre mĂșltiples despliegues de la IoT dentro del mismo dominio de aplicaciĂłn. Debido a las tecnologĂ­as utilizadas, la soluciĂłn no es adecuada para aplicaciones de tiempo crĂ­tico (umbral de tiempo relativamente bajo y rĂ­gido). Sin embargo, es adecuado para aplicaciones que no demandan respuesta en un tiempo crĂ­tico y que requieren el despliegue de VOs similares en cuanto al flujo de ejecuciĂłn. Finalmente, el trabajo se enfoca en otra tecnologĂ­a destinada a mejorar la escalabilidad y la capacidad de descubrimiento en la IoT. La SIoT estĂĄ emergiendo como una nueva estructura de la IoT que une los nodos a travĂ©s de relaciones significativas. Estas relaciones tienen como objetivo mejorar la capacidad de descubrimiento; en consecuencia, mejora la escalabilidad de una red de la IoT. En este trabajo se aplica este nuevo paradigma para optimizar la gestiĂłn de la energĂ­a en el lado de la demanda en las SGs. El objetivo es aprovechar las caracterĂ­sticas de la SIoT para ayudar en la creaciĂłn de Prosumer Community Groups (PCGs) (grupos de usuarios que consumen o producen energĂ­a) con el mismo objetivo de optimizaciĂłn en el uso de la energĂ­a. La sinergia entre la SIoT y las SGs ha sido denominada Social Internet of Energy (SIoE). Por lo tanto, con la SIoE y con el foco en un desafĂ­o especĂ­fico, se establece la base conceptual para la integraciĂłn entre la SIoT y las SG. Los experimentos iniciales muestran resultados prometedores y allanan el camino para futuras investigaciones y evaluaciones de la propuesta. Se concluye que la WoT y la SIoT son dos paradigmas complementarios que nutren la evoluciĂłn de la prĂłxima generaciĂłn de la IoT. Se espera que la prĂłxima generaciĂłn de la IoT sea un Multi-Agent System (MAS) generalizado. Algunos investigadores ya estĂĄn apuntando a la Web y sus tecnologĂ­as (por ejemplo,Web SemĂĄntica, HTTP/S)—y mĂĄs concretamente a la WoT — como el entorno que nutra a estos agentes. La SIoT puede mejorar tanto el entorno como las relaciones entre los agentes en esta fusiĂłn. Como un campo especĂ­fico de la IoT, las SGs tambiĂ©n pueden beneficiarse de los avances de la IoT.This thesis deals with two novel Internet of Things (IoT) technologies and their integration to the field of the Smart Grid (SG); these technologies are the Web of Things (WoT) and the Social Internet of Things (SIoT). The WoT is an enabling technology expected to provide a scalable and interoperable environment to the IoT using the existing web infrastructure, web protocols and the semantic web. The SIoT is expected to expand further and contribute to scalability and discoverability challenges by creating a social network of agents (objects and humans). When exploring the synergy between those technologies, we aim at providing practical and empirical evidence, usually in the form of prototype implementations and empirical experimentation. In relation to the WoT and SG, we create a prototype for the Web of Energy (WoE), that aims at addressing challenges present in the SG domain. The prototype is capable of providing interoperability and homogeneity among diverse protocols. The implementation design is based on the Actor Model, which also provides scalability in regards to the prototype. Experimentation shows that the prototype can handle the transmission of messages for time-critical SG applications. We also take another similar research direction less focused on the SG, but for a broader range of application domains. We integrate the description of flows of execution as Finite-State Machines (FSMs) using web ontologies (Resource Description Framework (RDF)) and WoT methodologies (actions are performed on the basis of calls Hyper Text Transfer Protocol/ Secure (HTTP/S) to a Uniform Resource Locator (URL)). This execution flow, which can also be a template to allow flexible configuration at runtime, is deployed and interpreted as (and through) a Virtual Object (VO). The template aims to be reusable and shareable among multiple IoT deployments within the same application domain. Due to the technologies used, the solution is not suitable for time-critical applications. Nevertheless, it is suitable for non-time-critical applications that require the deployment of similar VOs. Finally, we focus on another technology aimed at improving scalability and discoverability in IoT. The SIoT is emerging as a new IoT structure that links nodes through meaningful relationships. These relationships aim at improving discoverability; consequently, improving the scalability of an IoT network. We apply this new paradigm to optimize energy management at the demand side in a SG. Our objective is to harness the features of the SIoT to aid in the creation of Prosumer Community Group (PCG) (groups of energy users that consume or produce energy) with the same Demand Side Management (DSM) goal. We refer to the synergy between SIoT and SG as Social Internet of Energy (SIoE). Therefore, with the SIoE and focusing on a specific challenge, we set the conceptual basis for the integration between SIoT and SG. Initial experiments show promising results and pave the way for further research and evaluation of the proposal. We conclude that the WoT and the SIoT are two complementary paradigms that nourish the evolution of the next generation IoT. The next generation IoT is expected to be a pervasive Multi-Agent System (MAS). Some researchers are already pointing at the Web and its technologies (e.g. Semantic Web, HTTP/S) — and more concretely at the WoT — as the environment nourishing the agents. The SIoT can enhance both the environment and the relationships between agents in this fusion. As a specific field of the IoT, the SG can also benefit from IoT advancements

    New Challenges on Web Architectures for the Homogenization of the Heterogeneity of Smart Objects in the Internet of Things

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    Aquesta tesi tracta de dues de les noves tecnologies relacionades amb la Internet of Things (IoT) i la seva integraciĂł amb el camp de les Smart Grids (SGs); aquestes tecnologies son la Web of Things (WoT) i la Social Internet of Things (SIoT). La WoT Ă©s una tecnologia que s’espera que proveeixi d’un entorn escalable i interoperable a la IoT usant la infraestructura web existent, els protocols web y la web semĂ ntica. TambĂ© s’espera que la SIoT contribueixi a solucionar els reptes d’escalabilitat i capacitat de descobriment creant una xarxa social d’agents (objectes i humans). Per explorar la sinergia entre aquestes tecnologies, l’objectiu Ă©s el de proporcionar evidĂšncia prĂ ctica i empĂ­rica, generalment en forma de prototips d’implementaciĂł i experimentaciĂł empĂ­rica. En relaciĂł amb la WoT i les SGs, s’ha creat un prototip per al Web of Energy (WoE) que tĂ© com a objectiu abordar els desafiaments presents en el domini les SGs. El prototip Ă©s capaç de proporcionar interoperabilitat i homogeneĂŻtat entre diversos protocols. El disseny d’implementaciĂł es basa en el Model d’Actors, que tambĂ© proporciona escalabilitat del prototip. L’experimentaciĂł mostra que el prototip pot gestionar la transmissiĂł de missatges per a aplicacions de les SGs que requereixen que la comunicaciĂł es realitzi sota llindars de temps crĂ­tics. TambĂ© es pren una altra direcciĂł d’investigaciĂł similar, menys centrada en les SGs, perĂČ per a una gamma mĂ©s Ă mplia de dominis d’aplicaciĂł. S’integra la descripciĂł dels fluxos d’execuciĂł com a mĂ quines d’estats finits utilitzant ontologies web (Resource Description Framework (RDF)) i metodologies de la WoT (les accions es realitzen basant-se en peticions Hyper-Text Transfer Protocol/Secure (HTTP/S) a Uniform Resource Locators (URLs)). Aquest flux d’execuciĂł, que tambĂ© pot ser un plantilla per a permetre una configuraciĂł flexible en temps d’execuciĂł, s’implementa i interpreta com si fos (i mitjançant) un Virtual Object (VO). L’objectiu de la plantilla Ă©s ser reutilitzable i poder-se compartir entre mĂșltiples desplegaments de la IoT dins el mateix domini d’aplicaciĂł. A causa de les tecnologies utilitzades, la soluciĂł no Ă©s adequada per a aplicacions de temps crĂ­tic (llindar de temps relativament baix i rĂ­gid). No obstant aixĂČ, Ă©s adequat per a aplicacions que no demanden resposta en un temps crĂ­tic i que requereixen el desplegament de VOs similars en el que fa referĂšncia al flux d’execuciĂł. Finalment, el treball s’enfoca en una altra tecnologia destinada a millorar l’escalabilitat i la capacitat de descobriment en la IoT. La SIoT estĂ  sorgint com una nova estructura de la IoT que uneix els nodes a travĂ©s de relacions significatives. Aquestes relacions tenen com a objectiu millorar la capacitat de descobriment; en conseqĂŒĂšncia, millora la escalabilitat d’una xarxa de la IoT. En aquest treball s’aplica aquest nou paradigma per optimitzar la gestiĂł de l’energia en el costat de la demanda a les SGs. L’objectiu Ă©s aprofitar les caracterĂ­stiques de la SIoT per ajudar a la creaciĂł de Prosumer Community Groups (PCGs) (grups d’usuaris que consumeixen o produeixen energia) amb el mateix objectiu d’optimitzaciĂł en l’Ășs de l’energia. La sinergia entre la SIoT i les SGs s’ha anomenat Social Internet of Energy (SIoE). Per tant, amb la SIoE i amb el focus en un desafiament especĂ­fic, s’estableix la base conceptual per a la integraciĂł entre la SIoT i les SGs. Els experiments inicials mostren resultats prometedors i aplanen el camĂ­ per a futures investigacions i avaluacions de la proposta. Es conclou que el WoT i la SIoT sĂłn dos paradigmes complementaris que nodreixen l’evoluciĂł de la propera generaciĂł de la IoT. S’espera que la propera generaciĂł de la IoT sigui un Multi-Agent System (MAS) generalitzat. Alguns investigadors ja estan apuntant a la Web i les seves tecnologies (per exemple, Web SemĂ ntica, HTTP/S)—i mĂ©s concretamente a la WoT — com a l’entorn que nodreixi a aquests agents. La SIoT pot millorar tant l’entorn com les relacions entre els agents en aquesta fusiĂł. Les SGs tambĂ© poden beneficiar-se dels avenços de la IoT, ja que es poden considerar com una aplicaciĂł especĂ­fica d’aquesta Ășltima.  Esta tesis trata de dos de las novedosas tecnologĂ­as relacionadas con la Internet of Things (IoT) y su integraciĂłn con el campo de las Smart Grids (SGs); estas tecnologĂ­as son laWeb of Things (WoT) y la Social Internet of Things (SIoT). La WoT es una tecnologĂ­a que se espera que provea de un entorno escalable e interoperable a la IoT usando la infraestructura web existente, los protocolos web y la web semĂĄntica. TambiĂ©n se espera que la SIoT contribuya a solucionar los retos de escalabilidad y capacidad de descubrimiento creando una red social de agentes (objetos y humanos). Para explorar la sinergia entre estas tecnologĂ­as, el objetivo es el de proporcionar evidencia prĂĄctica y empĂ­rica, generalmente en forma de prototipos de implementaciĂłn y experimentaciĂłn empĂ­rica. En relaciĂłn con la WoT y las SGs, se ha creado un prototipo para la Web of Energy (WoE) que tiene como objetivo abordar los desafĂ­os presentes en el dominio las SGs. El prototipo es capaz de proporcionar interoperabilidad y homogeneidad entre diversos protocolos. El diseño de implementaciĂłn se basa en el Modelo de Actores, que tambiĂ©n proporciona escalabilidad del prototipo. La experimentaciĂłn muestra que el prototipo puede manejar la transmisiĂłn de mensajes para aplicaciones de las SGs que requieran que la comunicaciĂłn se realice bajo umbrales de tiempo crĂ­ticos. TambiĂ©n se toma otra direcciĂłn de investigaciĂłn similar, menos centrada en las SGs, pero para una gama mĂĄs amplia de dominios de aplicaciĂłn. Se integra la descripciĂłn de los flujos de ejecuciĂłn como mĂĄquinas de estados finitos utilizando ontologĂ­as web (Resource Description Framework (RDF)) y metodologĂ­as de la WoT (las acciones se realizan basĂĄndose en peticiones Hyper-Text Transfer Protocol/Secure (HTTP/S) a Uniform Resource Locators (URLs)). Este flujo de ejecuciĂłn, que tambiĂ©n puede ser una plantilla para permitir una configuraciĂłn flexible en tiempo de ejecuciĂłn, se implementa e interpreta como si fuera (y a travĂ©s de) un Virtual Object (VO). El objetivo de la plantilla es que sea reutilizable y se pueda compartir entre mĂșltiples despliegues de la IoT dentro del mismo dominio de aplicaciĂłn. Debido a las tecnologĂ­as utilizadas, la soluciĂłn no es adecuada para aplicaciones de tiempo crĂ­tico (umbral de tiempo relativamente bajo y rĂ­gido). Sin embargo, es adecuado para aplicaciones que no demandan respuesta en un tiempo crĂ­tico y que requieren el despliegue de VOs similares en cuanto al flujo de ejecuciĂłn. Finalmente, el trabajo se enfoca en otra tecnologĂ­a destinada a mejorar la escalabilidad y la capacidad de descubrimiento en la IoT. La SIoT estĂĄ emergiendo como una nueva estructura de la IoT que une los nodos a travĂ©s de relaciones significativas. Estas relaciones tienen como objetivo mejorar la capacidad de descubrimiento; en consecuencia, mejora la escalabilidad de una red de la IoT. En este trabajo se aplica este nuevo paradigma para optimizar la gestiĂłn de la energĂ­a en el lado de la demanda en las SGs. El objetivo es aprovechar las caracterĂ­sticas de la SIoT para ayudar en la creaciĂłn de Prosumer Community Groups (PCGs) (grupos de usuarios que consumen o producen energĂ­a) con el mismo objetivo de optimizaciĂłn en el uso de la energĂ­a. La sinergia entre la SIoT y las SGs ha sido denominada Social Internet of Energy (SIoE). Por lo tanto, con la SIoE y con el foco en un desafĂ­o especĂ­fico, se establece la base conceptual para la integraciĂłn entre la SIoT y las SG. Los experimentos iniciales muestran resultados prometedores y allanan el camino para futuras investigaciones y evaluaciones de la propuesta. Se concluye que la WoT y la SIoT son dos paradigmas complementarios que nutren la evoluciĂłn de la prĂłxima generaciĂłn de la IoT. Se espera que la prĂłxima generaciĂłn de la IoT sea un Multi-Agent System (MAS) generalizado. Algunos investigadores ya estĂĄn apuntando a la Web y sus tecnologĂ­as (por ejemplo,Web SemĂĄntica, HTTP/S)—y mĂĄs concretamente a la WoT — como el entorno que nutra a estos agentes. La SIoT puede mejorar tanto el entorno como las relaciones entre los agentes en esta fusiĂłn. Como un campo especĂ­fico de la IoT, las SGs tambiĂ©n pueden beneficiarse de los avances de la IoT.This thesis deals with two novel Internet of Things (IoT) technologies and their integration to the field of the Smart Grid (SG); these technologies are the Web of Things (WoT) and the Social Internet of Things (SIoT). The WoT is an enabling technology expected to provide a scalable and interoperable environment to the IoT using the existing web infrastructure, web protocols and the semantic web. The SIoT is expected to expand further and contribute to scalability and discoverability challenges by creating a social network of agents (objects and humans). When exploring the synergy between those technologies, we aim at providing practical and empirical evidence, usually in the form of prototype implementations and empirical experimentation. In relation to the WoT and SG, we create a prototype for the Web of Energy (WoE), that aims at addressing challenges present in the SG domain. The prototype is capable of providing interoperability and homogeneity among diverse protocols. The implementation design is based on the Actor Model, which also provides scalability in regards to the prototype. Experimentation shows that the prototype can handle the transmission of messages for time-critical SG applications. We also take another similar research direction less focused on the SG, but for a broader range of application domains. We integrate the description of flows of execution as Finite-State Machines (FSMs) using web ontologies (Resource Description Framework (RDF)) and WoT methodologies (actions are performed on the basis of calls Hyper Text Transfer Protocol/ Secure (HTTP/S) to a Uniform Resource Locator (URL)). This execution flow, which can also be a template to allow flexible configuration at runtime, is deployed and interpreted as (and through) a Virtual Object (VO). The template aims to be reusable and shareable among multiple IoT deployments within the same application domain. Due to the technologies used, the solution is not suitable for time-critical applications. Nevertheless, it is suitable for non-time-critical applications that require the deployment of similar VOs. Finally, we focus on another technology aimed at improving scalability and discoverability in IoT. The SIoT is emerging as a new IoT structure that links nodes through meaningful relationships. These relationships aim at improving discoverability; consequently, improving the scalability of an IoT network. We apply this new paradigm to optimize energy management at the demand side in a SG. Our objective is to harness the features of the SIoT to aid in the creation of Prosumer Community Group (PCG) (groups of energy users that consume or produce energy) with the same Demand Side Management (DSM) goal. We refer to the synergy between SIoT and SG as Social Internet of Energy (SIoE). Therefore, with the SIoE and focusing on a specific challenge, we set the conceptual basis for the integration between SIoT and SG. Initial experiments show promising results and pave the way for further research and evaluation of the proposal. We conclude that the WoT and the SIoT are two complementary paradigms that nourish the evolution of the next generation IoT. The next generation IoT is expected to be a pervasive Multi-Agent System (MAS). Some researchers are already pointing at the Web and its technologies (e.g. Semantic Web, HTTP/S) — and more concretely at the WoT — as the environment nourishing the agents. The SIoT can enhance both the environment and the relationships between agents in this fusion. As a specific field of the IoT, the SG can also benefit from IoT advancements

    The Kuramoto model in complex networks

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    181 pages, 48 figures. In Press, Accepted Manuscript, Physics Reports 2015 Acknowledgments We are indebted with B. Sonnenschein, E. R. dos Santos, P. Schultz, C. Grabow, M. Ha and C. Choi for insightful and helpful discussions. T.P. acknowledges FAPESP (No. 2012/22160-7 and No. 2015/02486-3) and IRTG 1740. P.J. thanks founding from the China Scholarship Council (CSC). F.A.R. acknowledges CNPq (Grant No. 305940/2010-4) and FAPESP (Grants No. 2011/50761-2 and No. 2013/26416-9) for financial support. J.K. would like to acknowledge IRTG 1740 (DFG and FAPESP).Peer reviewedPreprin
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