Diagnosticar os elementos que influenciam a atuação organizacional é um passo essencial para trabalhar o desempenho em mercados cada vez mais competitivos. Dentre esses elementos, a produção, a demanda, os recursos financeiros, entre outros, são variáveis que devem sempre equacionar o ritmo e a intensidade das relações intra e interorganizacionais. O processo de planejamento de vendas e operações (S&OP) vai ao encontro dessa necessidade, porventura tática, de balancear as competências e forças internas (e.g. capacidades de produção, P&D, etc.) com as externas, (e.g. oportunidades de negócio, comportamento de demanda, etc.) nas Organizações. Com base nesse contexto procura-se desenvolver um modelo de referência baseado no EKD, para estruturar a execução do planejamento de vendas e operações (S&OP) utilizando os conceitos de redes dinâmicas (formação de redes), em um ambiente empresarial que emprega vários sistemas produtivos para atuar no mercado. / Diagnose the elements that influence the organizational acting is the essential step to work the performance in competitive market. Among these elements, the production, the demand, the financial resources, and others, are variables that must have always equating the rhythm and intensity of intra and Interorganizational interaction. The process of Sales and Operations Planning (S&OP) is in the line with this necessity, possibly tactic, of competent and internal forces balance (e.g. production capacity, R&D, etc.) with the external (e.g. business opportunities, demand behavior, etc) in the organizations. Based on that context, the present work aims to develop a EKD\'s reference model for Sales & Operations Planning (S&OP) with dynamic networks concepts in an empresarial environment that uses a diversity of production systems.

Content delivery through service overlay networks has gained popularity due to the overlays’ abilities to provide effective and reliable services. Inefficiencies of one-to-one matching of user requirements to a single service have given rise to service composition. Customized media delivery can be achieved through dynamic compositions of Service Specific Overlay Networks (SSONs). However, the presence of SSONs in dynamic environments raises the possibility of unexpected failures and quality degradations. Thus constructing, managing, and repairing corrupted service paths are challenging dilemmas. This thesis investigates the problem of autonomous SSON construction and management and identifies the drawbacks of current approaches. A novel multi-layered, autonomous, self-adaptive framework for constructing SSONs is presented. The framework includes a Hybrid Service Overlay Network layer (H-SON). The H-SON is a dynamic hybrid overlay dedicated to service composition for multimedia delivery in dynamic networks. Node placement in the overlay depends on the node’s stability, types and quality of provided services. Changes in stability and QoS of service nodes are reflected by dynamic re-organizations of the overlay. The H-SON permits fast and efficient searches for component services that meet client functional and quality expectations. Self-managed overlay nodes coordinate their behaviors to formulate a service composition path that meets the client’s requirements. Two approaches are presented in this work. The first illustrates how SSONs are established through dynamically adaptable MS-designed plans. The imprecise nature of nonfunctional service characteristics, such as QoS, is modeled using a fuzzy logic system. Moreover, semantic similarity evaluations enable us to include, in compositions, those services whose operations match, semantically, the requirements of the composition plan. Plan-based composition solutions restrict service discovery to defined abstract models. Our second composition approach introduces a semantic similarity and nearness SSON composition method. The objective is to free service nodes from the adherence to restrictive composition plans. The presented work illustrates a service composition solution that semantically advances service composition paths towards meeting users’ needs with each service hop while simultaneously guaranteeing user-acceptable QoS levels. Simulation results showcase the effectiveness of the presented work. Gathered results validate the success of our service composition methods while meeting user requirements.

With the proliferation of laptops, smart phones, sensors and other small devices, our physical environment is increasingly networked. Applications in a variety of problem domains (e.g., intelligent construction, traffic monitoring, smart homes, etc.) need to efficiently and seamlessly execute on top of such emerging infrastructure. Such infrastructure tends to be unreliable, and the network configuration changes constantly (network hosts depart and reemerge frequently). Consequently, software has to be able to react to these changes continuously and change its behaviors accordingly. In this dissertation, I introduce PAQ (Persistent Adaptive Query), a middleware designed to ease the programming burden associated with writing such applications. PAQ employs a novel style of query-driven application development that allows programmers to build pervasive applications by employing persistent queries--queries that continuously monitor the environment. The dissertation discusses the design and implementation of a new middleware model that allows programmers to write high level specifications abstracting away several tedious implementation details. PAQ employs both novel protocols that automatically tag the quality of information obtained from the network and statistical techniques to post-process and smooth the data. The goal of this research is to ease the software engineering challenges encountered during the construction and deployment of several applications in emerging pervasive computing environments thorough the use of a query-driven application development paradigm. / text

Content delivery through service overlay networks has gained popularity due to the overlays’ abilities to provide effective and reliable services. Inefficiencies of one-to-one matching of user requirements to a single service have given rise to service composition. Customized media delivery can be achieved through dynamic compositions of Service Specific Overlay Networks (SSONs). However, the presence of SSONs in dynamic environments raises the possibility of unexpected failures and quality degradations. Thus constructing, managing, and repairing corrupted service paths are challenging dilemmas. This thesis investigates the problem of autonomous SSON construction and management and identifies the drawbacks of current approaches. A novel multi-layered, autonomous, self-adaptive framework for constructing SSONs is presented. The framework includes a Hybrid Service Overlay Network layer (H-SON). The H-SON is a dynamic hybrid overlay dedicated to service composition for multimedia delivery in dynamic networks. Node placement in the overlay depends on the node’s stability, types and quality of provided services. Changes in stability and QoS of service nodes are reflected by dynamic re-organizations of the overlay. The H-SON permits fast and efficient searches for component services that meet client functional and quality expectations. Self-managed overlay nodes coordinate their behaviors to formulate a service composition path that meets the client’s requirements. Two approaches are presented in this work. The first illustrates how SSONs are established through dynamically adaptable MS-designed plans. The imprecise nature of nonfunctional service characteristics, such as QoS, is modeled using a fuzzy logic system. Moreover, semantic similarity evaluations enable us to include, in compositions, those services whose operations match, semantically, the requirements of the composition plan. Plan-based composition solutions restrict service discovery to defined abstract models. Our second composition approach introduces a semantic similarity and nearness SSON composition method. The objective is to free service nodes from the adherence to restrictive composition plans. The presented work illustrates a service composition solution that semantically advances service composition paths towards meeting users’ needs with each service hop while simultaneously guaranteeing user-acceptable QoS levels. Simulation results showcase the effectiveness of the presented work. Gathered results validate the success of our service composition methods while meeting user requirements.

We propose a statistical model for weighted temporal networks capable of measuring the level of heterogeneity in a financial system. Our model focuses on the level of diversification of financial institutions; that is, whether they are more inclined to distribute their assets equally among partners, or if they rather concentrate their commitment towards a limited number of institutions. Crucially, a Markov property is introduced to capture time dependencies and to make our measures comparable across time. We apply the model on an original dataset of Austrian interbank exposures. The temporal span encompasses the onset and development of the financial crisis in 2008 as well as the beginnings of European sovereign debt crisis in 2011. Our analysis highlights an overall increasing trend for network homogeneity, whereby core banks have a tendency to distribute their market exposures more equally across their partners.

De nos jours, les interactions ont une part prépondérante dans notre vie. Ces interactions peuvent représenter la diffusion de rumeurs, de maladies, etc. Comprendre comment ces interactions affectent notre vie est important. Une façon naturelle de faire est d'utiliser la théorie des graphes. Néanmoins, comme le montrent certaines études, l'aspect temporel ne doit pas être négligé. Dans ce travail, nous nous sommes concentrés sur la détection d'individus importants dans ces graphes en utilisant des métriques de centralité qui prennent en compte l'aspect temporel. Nous avons proposé un protocole de comparaison qui compare les différentes mesures de centralité existantes. Nous l'avons appliqué sur plusieurs graphes, ce qui nous a donné un aperçu de la façon dont les différentes métriques agissent. Ensuite, nous avons observé le besoin de calcul élevé de ces métriques de centralité. Dès lors, nous avons introduit une méthode qui réduit ce besoin. Finalement, nous avons introduit une nouvelle mesure de centralité, appelée ego-betweenness centrality. / Nowadays, interactions are a huge part of our daily life. These interactions can represent the diffusion of rumors, diseases, etc. Understanding how these interactions affect our life is quite important. A natural way to do so is using graph theory. However, this is not straightforward as studies show the temporal aspect, in other words, the order of interactions, should be taken into account. In this work, we concentrated on detecting the important individuals in these graphs using centrality metrics that take into account the temporal aspect. We proposed a comparison protocol that compares the different centrality metrics that exist. We applied it on several networks, which gave us insight on how the different metrics react. Secondly, we observed the high computational need of these centrality metrics. Therefore, we introduced a method to reduce this need. And finally, we introduced a novel centrality metric that we call ego-betweenness centrality.

Content delivery through service overlay networks has gained popularity due to the overlays’ abilities to provide effective and reliable services. Inefficiencies of one-to-one matching of user requirements to a single service have given rise to service composition. Customized media delivery can be achieved through dynamic compositions of Service Specific Overlay Networks (SSONs). However, the presence of SSONs in dynamic environments raises the possibility of unexpected failures and quality degradations. Thus constructing, managing, and repairing corrupted service paths are challenging dilemmas. This thesis investigates the problem of autonomous SSON construction and management and identifies the drawbacks of current approaches. A novel multi-layered, autonomous, self-adaptive framework for constructing SSONs is presented. The framework includes a Hybrid Service Overlay Network layer (H-SON). The H-SON is a dynamic hybrid overlay dedicated to service composition for multimedia delivery in dynamic networks. Node placement in the overlay depends on the node’s stability, types and quality of provided services. Changes in stability and QoS of service nodes are reflected by dynamic re-organizations of the overlay. The H-SON permits fast and efficient searches for component services that meet client functional and quality expectations. Self-managed overlay nodes coordinate their behaviors to formulate a service composition path that meets the client’s requirements. Two approaches are presented in this work. The first illustrates how SSONs are established through dynamically adaptable MS-designed plans. The imprecise nature of nonfunctional service characteristics, such as QoS, is modeled using a fuzzy logic system. Moreover, semantic similarity evaluations enable us to include, in compositions, those services whose operations match, semantically, the requirements of the composition plan. Plan-based composition solutions restrict service discovery to defined abstract models. Our second composition approach introduces a semantic similarity and nearness SSON composition method. The objective is to free service nodes from the adherence to restrictive composition plans. The presented work illustrates a service composition solution that semantically advances service composition paths towards meeting users’ needs with each service hop while simultaneously guaranteeing user-acceptable QoS levels. Simulation results showcase the effectiveness of the presented work. Gathered results validate the success of our service composition methods while meeting user requirements.

Distributed ledger technology (DLT) is one of the latest in a long list of digital technologies, which appear to be heading towards a new industrial revolution. DLT has become very popular with the publication of the Bitcoin Blockchain in 2008. However, when we consider its suitability for dynamic networking environments, such as the Internet of Things, issues like transaction fees, scalability, and offline accessibility have not been resolved. The IOTA Foundation has designed the IOTA protocol, which is the data and value transfer layer for the Machine Economy. IOTA protocol uses an alternative blockless Blockchain which claims to solve the previous problems: the Tangle. This thesis first inquires into the theoretical concepts of both technologies Tangleand Blockchain, to understand them and identify the reasons to be compatible or not with the Internet of Things networking environments. After the analysis, the thesis focuses on the proposed implementation as a solution to address the connectivity issue suffered by the IOTA network. The answer to the problem is the development of a Neighbor Discovery algorithm, which has been designed to fulfill the requirements demanded by the IOTA application. Dealing with IOTA network setup can be very interesting for the community that is looking for new improvements at each release. Testing the solution in a peer-to-peer specific protocol (PeerSim), with different networking scenarios, allowed us to get valuable and more realistic information. Thus, after analyzing the results, we were able to determine the appropriate IOTA network configuration to build a more reliable and long-lasting network.

Networks are sets of objects that are connected in some way and appear abundantly in nature, sociology, and technology. For many centuries, network theory focused on static networks, which are networks that do not change. However, since all networks transform over time, static networks have limited applications. By comparison, dynamic networks model how connections between objects change over time. In this work, we will explore how connections in dynamic networks change and how we can leverage these changes to make predictions about future iterations of networks. We will do this by first considering the link prediction problem, using either Katz distance or effective resistance to predict future connections, and relate these two metrics. Then we will look at using bipartite network connections to predict group transitions in professional sports teams. Lastly, we will investigate how to use network connections to identify and predict roles in social networks.

Entrepreneurs need resources to organize new venture offerings into marketplace-acceptable forms. Entrepreneurs use others' assistance via networks to obtain these resources. Research indicates that firms face resource dependencies, that likely change over time, where they must respond to those controlling resources. Although some work has investigated implications of new ventures' networks at one time period, little work has investigated the dynamic nature and associated outcomes of networks as they change due to different resource requirements as the venture develops. This research examines the dynamic nature of networks, due different resource requirements over time, and how these changes impact entrepreneurial outcomes via interactions with entrepreneurs' existing networks. In order to account for the dynamic nature of entrepreneurial new ventures and their networks of resource providers, a model is presented that investigates antecedents to subsequent entrepreneurial network characteristics. The model also anticipates changes eminent to the founder as a consequence of interactions with their networks due to experiences associated with the new venture development process. This work relies on network theory integrated with resource dependence theory arguments, work that examines founder attributes as associated with entrepreneurial outcomes and research that investigates the stages of new venture development. Predictions developed from the model were tested in two studies. The first study utilized the Panel Study of Entrepreneurial Dynamics, an existing panel database containing information about nascent entrepreneurs, as its data source to test predictions examining the dynamics of entrepreneurs' networks across two time frames. The second study used a cross-sectional mass mail survey design to investigate all of the model's predictions on a random sample of newly incorporated firms in the state of Florida. The results of the studies provided support for about one third of the predictions and there were a few contrasting findings across studies. Overall, the results of the studies suggest that some conceptualizations presented in the theoretical model should be reevaluated and that the applicability of some constructs when studying firms in the organizing stages of development should be reconsidered.