916 resultados para Dynamic Bayesian Networks


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Wireless sensor network (WSN) Is a technology that can be used to monitor and actuate on environments in a non-intrusive way. The main difference from WSN and traditional sensor networks is the low dependability of WSN nodes. In this way, WSN solutions are based on a huge number of cheap tiny nodes that can present faults in hardware, software and wireless communication. The deployment of hundreds of nodes can overcome the low dependability of individual nodes, however this strategy introduces a lot of challenges regarding network management, real-time requirements and self-optimization. In this paper we present a simulated annealing approach that self-optimize large scale WSN. Simulation results indicate that our approach can achieve self-optimization characteristics in a dynamic WSN. © 2012 IEEE.

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Includes bibliography

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The proliferation of multimedia content and the demand for new audio or video services have fostered the development of a new era based on multimedia information, which allowed the evolution of Wireless Multimedia Sensor Networks (WMSNs) and also Flying Ad-Hoc Networks (FANETs). In this way, live multimedia services require realtime video transmissions with a low frame loss rate, tolerable end-to-end delay, and jitter to support video dissemination with Quality of Experience (QoE) support. Hence, a key principle in a QoE-aware approach is the transmission of high priority frames (protect them) with a minimum packet loss ratio, as well as network overhead. Moreover, multimedia content must be transmitted from a given source to the destination via intermediate nodes with high reliability in a large scale scenario. The routing service must cope with dynamic topologies caused by node failure or mobility, as well as wireless channel changes, in order to continue to operate despite dynamic topologies during multimedia transmission. Finally, understanding user satisfaction on watching a video sequence is becoming a key requirement for delivery of multimedia content with QoE support. With this goal in mind, solutions involving multimedia transmissions must take into account the video characteristics to improve video quality delivery. The main research contributions of this thesis are driven by the research question how to provide multimedia distribution with high energy-efficiency, reliability, robustness, scalability, and QoE support over wireless ad hoc networks. The thesis addresses several problem domains with contributions on different layers of the communication stack. At the application layer, we introduce a QoE-aware packet redundancy mechanism to reduce the impact of the unreliable and lossy nature of wireless environment to disseminate live multimedia content. At the network layer, we introduce two routing protocols, namely video-aware Multi-hop and multi-path hierarchical routing protocol for Efficient VIdeo transmission for static WMSN scenarios (MEVI), and cross-layer link quality and geographical-aware beaconless OR protocol for multimedia FANET scenarios (XLinGO). Both protocols enable multimedia dissemination with energy-efficiency, reliability and QoE support. This is achieved by combining multiple cross-layer metrics for routing decision in order to establish reliable routes.

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The use of wireless local area networks, called WLANs, as well as the proliferation of the use of multimedia applications have grown rapidly in recent years. Some factors affect the quality of service (QoS) received by the user and interference is one of them. This work presents strategies for planning and performance evaluation through an empirical study of the QoS parameters of a voice over Internet Protocol (VoIP) application in an interference network, as well as the relevance in the design of wireless networks to determine the coverage area of an access point, taking into account several parameters such as power, jitter, packet loss, delay, and PMOS. Another strategy is based on a hybrid approach that considers measuring and Bayesian inference applied to wireless networks, taking into consideration QoS parameters. The models take into account a cross layer vision of networks, correlating aspects of the physical environment, on the signal propagation (power or distance) with aspects of VoIP applications (e.g., jitter and packet loss). Case studies were carried out for two indoor environments and two outdoor environments, one of them displaying main characteristics of the Amazon region (e.g., densely arboreous environments). This last test bed was carried out in a real system because the Government of the State of Pará has a digital inclusion program called NAVEGAPARÁ.

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Heterogeneous waveband switching (HeteroWBS) in WDM networks reduces the network operational costs. We propose an autonomous clustering-based HeteroWBS architecture to support the design of efficient HeteroWBS algorithms under dynamic traffic requests in such a network.

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We investigate the problem of waveband switching (WBS) in a wavelength-division multiplexing (WDM) mesh network with dynamic traffic requests. To solve the WBS problem in a homogeneous dynamic WBS network, where every node is a multi-granular optical cross-connect (MG-OXC), we construct an auxiliary graph. Based on the auxiliary graph, we develop two heuristic on-line WBS algorithms with different grouping policies, namely the wavelength-first WBS algorithm based on the auxiliary graph (WFAUG) and the waveband-first WBS algorithm based on the auxiliary graph (BFAUG). Our results show that the WFAUG algorithm outperforms the BFAUG algorithm.

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As wavelength-division multiplexing (WDM) evolves towards practical applications in optical transport networks, waveband switching (WBS) has been introduced to cut down the operational costs and to reduce the complexities and sizes of network components, e.g., optical cross-connects (OXCs). This paper considers the routing, wavelength assignment and waveband assignment (RWWBA) problem in a WDM network supporting mixed waveband and wavelength switching. First, the techniques supporting waveband switching are studied, where a node architecture enabling mixed waveband and wavelength switching is proposed. Second, to solve the RWWBA problem with reduced switching costs and improved network throughput, the cost savings and call blocking probabilities along intermediate waveband-routes are analyzed. Our analysis reveals some important insights about the cost savings and call blocking probability in relation to the fiber capacity, the candidate path, and the traffic load. Third, based on our analysis, an online integrated intermediate WBS algorithm (IIWBS) is proposed. IIWBS determines the waveband switching route for a call along its candidate path according to the node connectivity, the link utilization, and the path length information. In addition, the IIWBS algorithm is adaptive to real network applications under dynamic traffic requests. Finally, our simulation results show that IIWBS outperforms a previous intermediate WBS algorithm and RWA algorithms in terms of network throughput and cost efficiency.

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We propose an efficient scheduling scheme that optimizes advance-reserved lightpath services in reconfigurable WDM networks. A re-optimization approach is devised to reallocate network resources for dynamic service demands while keeping determined schedule unchanged.

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Sparse traffic grooming is a practical problem to be addressed in heterogeneous multi-vendor optical WDM networks where only some of the optical cross-connects (OXCs) have grooming capabilities. Such a network is called as a sparse grooming network. The sparse grooming problem under dynamic traffic in optical WDM mesh networks is a relatively unexplored problem. In this work, we propose the maximize-lightpath-sharing multi-hop (MLS-MH) grooming algorithm to support dynamic traffic grooming in sparse grooming networks. We also present an analytical model to evaluate the blocking performance of the MLS-MH algorithm. Simulation results show that MLSMH outperforms an existing grooming algorithm, the shortest path single-hop (SPSH) algorithm. The numerical results from analysis show that it matches closely with the simulation. The effect of the number of grooming nodes in the network on the blocking performance is also analyzed.

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Data visualization techniques are powerful in the handling and analysis of multivariate systems. One such technique known as parallel coordinates was used to support the diagnosis of an event, detected by a neural network-based monitoring system, in a boiler at a Brazilian Kraft pulp mill. Its attractiveness is the possibility of the visualization of several variables simultaneously. The diagnostic procedure was carried out step-by-step going through exploratory, explanatory, confirmatory, and communicative goals. This tool allowed the visualization of the boiler dynamics in an easier way, compared to commonly used univariate trend plots. In addition it facilitated analysis of other aspects, namely relationships among process variables, distinct modes of operation and discrepant data. The whole analysis revealed firstly that the period involving the detected event was associated with a transition between two distinct normal modes of operation, and secondly the presence of unusual changes in process variables at this time.

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Social networks are static illustrations of dynamic societies, within which social interactions are constantly changing. Fundamental sources of variation include ranging behaviour and temporal demographic changes. Spatiotemporal dynamics can favour or limit opportunities for individuals to interact, and then a network may not essentially represent social processes. We examined whether a social network can embed such nonsocial effects in its topology, whereby emerging modules depict spatially or temporally segregated individuals. To this end, we applied a combination of spatial, temporal and demographic analyses to a long-term study of the association patterns of Guiana dolphins, Sotalia guianensis. We found that association patterns are organized into a modular social network. Space use was unlikely to reflect these modules, since dolphins' ranging behaviour clearly overlapped. However, a temporal demographic turnover, caused by the exit/entrance of individuals (most likely emigration/immigration), defined three modules of associations occurring at different times. Although this factor could mask real social processes, we identified the temporal scale that allowed us to account for these demographic effects. By looking within this turnover period (32 months), we assessed fission-fusion dynamics of the poorly known social organization of Guiana dolphins. We highlight that spatiotemporal dynamics can strongly influence the structure of social networks. Our findings show that hypothetical social units can emerge due to the temporal opportunities for individuals to interact. Therefore, a thorough search for a satisfactory spatiotemporal scale that removes such nonsocial noise is critical when analysing a social system. (C) 2012 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

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Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

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This work clarifies the relationship between network circuit (topology) and behavior (information transmission and synchronization) in active networks, e. g. neural networks. As an application, we show how to determine a network topology that is optimal for information transmission. By optimal, we mean that the network is able to transmit a large amount of information, it possesses a large number of communication channels, and it is robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

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Large scale wireless adhoc networks of computers, sensors, PDAs etc. (i.e. nodes) are revolutionizing connectivity and leading to a paradigm shift from centralized systems to highly distributed and dynamic environments. An example of adhoc networks are sensor networks, which are usually composed by small units able to sense and transmit to a sink elementary data which are successively processed by an external machine. Recent improvements in the memory and computational power of sensors, together with the reduction of energy consumptions, are rapidly changing the potential of such systems, moving the attention towards datacentric sensor networks. A plethora of routing and data management algorithms have been proposed for the network path discovery ranging from broadcasting/floodingbased approaches to those using global positioning systems (GPS). We studied WGrid, a novel decentralized infrastructure that organizes wireless devices in an adhoc manner, where each node has one or more virtual coordinates through which both message routing and data management occur without reliance on either flooding/broadcasting operations or GPS. The resulting adhoc network does not suffer from the deadend problem, which happens in geographicbased routing when a node is unable to locate a neighbor closer to the destination than itself. WGrid allow multidimensional data management capability since nodes' virtual coordinates can act as a distributed database without needing neither special implementation or reorganization. Any kind of data (both single and multidimensional) can be distributed, stored and managed. We will show how a location service can be easily implemented so that any search is reduced to a simple query, like for any other data type. WGrid has then been extended by adopting a replication methodology. We called the resulting algorithm WRGrid. Just like WGrid, WRGrid acts as a distributed database without needing neither special implementation nor reorganization and any kind of data can be distributed, stored and managed. We have evaluated the benefits of replication on data management, finding out, from experimental results, that it can halve the average number of hops in the network. The direct consequence of this fact are a significant improvement on energy consumption and a workload balancing among sensors (number of messages routed by each node). Finally, thanks to the replications, whose number can be arbitrarily chosen, the resulting sensor network can face sensors disconnections/connections, due to failures of sensors, without data loss. Another extension to {WGrid} is {W*Grid} which extends it by strongly improving network recovery performance from link and/or device failures that may happen due to crashes or battery exhaustion of devices or to temporary obstacles. W*Grid guarantees, by construction, at least two disjoint paths between each couple of nodes. This implies that the recovery in W*Grid occurs without broadcasting transmissions and guaranteeing robustness while drastically reducing the energy consumption. An extensive number of simulations shows the efficiency, robustness and traffic road of resulting networks under several scenarios of device density and of number of coordinates. Performance analysis have been compared to existent algorithms in order to validate the results.

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Nowadays, computing is migrating from traditional high performance and distributed computing to pervasive and utility computing based on heterogeneous networks and clients. The current trend suggests that future IT services will rely on distributed resources and on fast communication of heterogeneous contents. The success of this new range of services is directly linked to the effectiveness of the infrastructure in delivering them. The communication infrastructure will be the aggregation of different technologies even though the current trend suggests the emergence of single IP based transport service. Optical networking is a key technology to answer the increasing requests for dynamic bandwidth allocation and configure multiple topologies over the same physical layer infrastructure, optical networks today are still “far” from accessible from directly configure and offer network services and need to be enriched with more “user oriented” functionalities. However, current Control Plane architectures only facilitate efficient end-to-end connectivity provisioning and certainly cannot meet future network service requirements, e.g. the coordinated control of resources. The overall objective of this work is to provide the network with the improved usability and accessibility of the services provided by the Optical Network. More precisely, the definition of a service-oriented architecture is the enable technology to allow user applications to gain benefit of advanced services over an underlying dynamic optical layer. The definition of a service oriented networking architecture based on advanced optical network technologies facilitates users and applications access to abstracted levels of information regarding offered advanced network services. This thesis faces the problem to define a Service Oriented Architecture and its relevant building blocks, protocols and languages. In particular, this work has been focused on the use of the SIP protocol as a inter-layers signalling protocol which defines the Session Plane in conjunction with the Network Resource Description language. On the other hand, an advantage optical network must accommodate high data bandwidth with different granularities. Currently, two main technologies are emerging promoting the development of the future optical transport network, Optical Burst and Packet Switching. Both technologies respectively promise to provide all optical burst or packet switching instead of the current circuit switching. However, the electronic domain is still present in the scheduler forwarding and routing decision. Because of the high optics transmission frequency the burst or packet scheduler faces a difficult challenge, consequentially, high performance and time focused design of both memory and forwarding logic is need. This open issue has been faced in this thesis proposing an high efficiently implementation of burst and packet scheduler. The main novelty of the proposed implementation is that the scheduling problem has turned into simple calculation of a min/max function and the function complexity is almost independent of on the traffic conditions.