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We address the problem of optical propagation in random lattices. This can be relevant in characterizing, among other phenomena, the urban shortwave channels such as those involved in cellular communications. We consider an ensemble of optical rays, generated by an isotropic source, that propagates in a two-dimensional disordered medium whose characteristic parameter is the density of inner square reflectors. The statistical characterization of the propagation mechanism is our aim. In a previous work [ G. Franceschetti , IEEE Trans. Antennas Propag.47(7) (1999)], a quite similar scenario has been considered, with a ray impinging on a semi-infinite layer of reflectors and with a Markov chain formulation. We report the extension of such an approach to the internal-source scenario and point out how the independence assumption of the ray characterization may not lead to particularly accurate results. Therefore we propose a different approach, based solely on the geometry of the random lattice. We exploit the intuition that the relevant geometry in such a propagation problem should be based on the city-block distance rather than on the usual Euclidean distance. This allows us to obtain a simple analytical solution in the form of a parametric family of distribution functions. This basic result is validated by means of computer simulations.

A new phase unwrapping algorithm is presented that implements phase retrieval without any need for preliminary cuts or weights of the wrapped phase diagram. Excellent results on simulated as well as real data validate the proposed technique.

The classic polynomial interpolation approach is used to derive a sampling theorem for the class of signals that are the response of systems described by differential equations with constant coefficients. In particular, the polynomial that interpolates the signal between the sampling points for increasing order will give increasing accuracy for stable one-sided sequences, if the sampling rate is at least six times the highest pole frequency (Bolgiano sampling rate [7]). The convergence is ensured also for nonstable poles that lie in a certain region of the complex plane. If, instead, we use the symmetrical polynomial approach, it is enough to sample at a rate that is just two times the highest pole frequency (Nyquist sampling rate), with some constraints on the real part of the poles. A bound for the error is derived for both cases and a comparison to the Shannon-Whittaker sampling theorem is presented.

The Ll-filters are introduced to generate the order statistic filters (L-filters) and the nonrecursive linear, or finite-duration impulse-response (FIR), filters. Such estimators are particularly effective filtering signals that do not necessarily follow Gaussian distributions. They can be designed to restore one-dimensional or multidimensional signals corrupted by noise of impulsive type. Such filters are appealing since they are suitable for being made robust against the presence of spurious outliers in the data. >

A three-layer neural network is used to solve the problem of extracting relative azimuth and elevation positional information from signals detected by two spatially separate, directional receivers. This is analogous to the ability of owls to localize the position of sound based solely on the properties of the signals reaching their ears. A simple model of the acoustical environment was used to generate simulated data for training the network. The neural network was trained using the multiple extended Kalman algorithm (MEKA). MEKA enabled the network to be trained without constant user intervention for adjustment of the critical parameters of the model. >

The computational Grid concept is gaining great popularity as the best way to deliver access to a wide range of distributed computing and data resources. But, as Grids move from an experimental phase to real production and their deployment in the Internet significantly increases, controlling the security of a Grid application becomes imperative. The most significant Grid security issue is that the different sites composing the Grid will generally be managed by different organizations each with their own security mechanisms and policies. This makes any communication security arrangement on the entities participating to the Grid generally more difficult than if they were on the same LAN. In this paper, we propose a novel network resource abstraction for delivering dynamic on-demand Virtual Private Overlay connection services, into large-scale Grid environments. Such facility provides to Grid applications an illusion of dedicated layer-2 LAN connections that are fully comparable to a private network in performance, reliability, security and Quality of Service, but also provide topology and control plane virtualization to ensure better isolation also at the protocol and address space level. It may represent a technological breakthrough that can transform the overall connection paradigm in modern Grids, by reducing infrastructure costs, with the elimination of private circuits and long-distance direct connections, and increasing network coverage and flexibility by leveraging the Internet usage. As a proof of concept, the proposed facility has been implemented in a Grid Information Service prototype which was successfully tested on a small dedicated testbed infrastructure.

Cooperative transmission schemes have recently been proposed to improve the uplink performance of wireless communications systems by increasing diversity without requiring use of multiple transmit antennas. We here propose a novel cooperative scheme that performs distributed coding of user data, uses only one channel per user and allows a flexible tradeoff between rate and diversity, thus achieving higher data rates than previously proposed coded cooperative schemes. The point of operation of the system on the diversity-rate curve can be arbitrarily chosen according to the number of cooperating users. A trade-off is increased complexity as more users are required to be simultaneously decoded by the BS. We describe the construction of the distributed code for a n-user system, that results in reduced complexity decoding operations at the BS. The performance of the proposed method is studied via analytical bounds and numerical simulations.

In an increasingly hostile environment, the need for security in network infrastructure is stronger than ever, especially for Multi-Protocol Label Switching (MPLS), widely used to provide most of the new-generation network infrastructure-level services in the Internet. Unfortunately, the MPLS control plane lacks scalable verification for the authenticity and legitimacy of signaling messages and communication between peer routers is subject to active and passive forgery, hijacking and wiretapping activities. In this paper, we propose a robust framework for MPLS-based network survivability against security threats. The security of MPLS control plane protocols can be greatly enhanced by requiring digital signature of all the signaling messages, in accordance with a common security paradigm valid for all the protocols. Our design goals include integrity safeguarding, protection against replay attacks, and gradual deployment, with routers not supporting authentication breaking the trust chain but operating undisturbed under any other respect.

Performance of real-time applications on network communication channels are strongly related to losses and temporal delays. Several studies showed that these network features may be correlated and present a certain degree of memory such as bursty losses and delays. The memory and the statistical dependence between losses and temporal delays suggest that the channel may be well modelled by a Dynamic Bayesian Network with an appropriate hidden variable that captures the current state of the network. In this paper we propose a Bayesian model that, trained with a version of the EM-algorithm, seems to be effective in modelling typical channel behaviors.

A neural network system is implemented that uses binaural time/intensity cues for determining azimuth/elevation of a sound source. The system is designed to approximately mimic the sound localization behavior of the owl. The network is trained in a supervised learning mode. The errors between the estimated position (from the neural net) and the actual position (from an ideal optical sensor) are used to determine adaptively the synaptic connections. The learning paradigm used is the multiple extended Kalman algorithm, which allows training with no parameter adjustments. >

The large potential bandwidth available in wavelength-division multiplexed optical networks makes this technology of crucial importance for satisfying the ever increasing capacity requirements of the next-generation Internet. In this scenario, the routing and wavelength assignment (RWA) problem that concerns deter- mining the optical paths and wavelengths to be used for connection establishment in a wavelength-routed network, is still one of the most important open issues. In this paper we propose a new on- line dynamic grooming-capable RWA heuristic scheme working on wavelength division multiplexing (WDM) networks as a multistage selection process. The proposed algorithm is transparent with respect to the presence of wavelength converters, achieves very low connection rejection ratios with minimal computational complexity and is appropriate for the modern multilayer optical circuit and wavelength switched networks with sparse wavelength conversion capability.

A theoretical approach to the determination of the number of training examples for a neural network architecture is provided by the theory of Vapnik and Chervonenkis on the minimization of the empirical risk. We report here a new bound on the joint probability that both the approximation error between the binary function learned by the input/output examples and the target binary function is larger than /spl epsiv/ and the empirical error on the examples is smaller than a fixed non-null fraction of /spl epsiv/. The given bounds are independent of the probability distribution on the input space and improve some existing results on the generalization abilities of an adaptive binary function.

Performance of real-time applications on network communication channels are strongly related to losses and temporal delays. Several studies showed that these network features may be correlated and exhibit a certain degree of memory such as bursty losses and delays. The memory and the statistical dependence between losses and temporal delays suggest that the channel may be well modelled by a Hidden Markov Model (HMM) with appropriate hidden variables that capture the current state of the network. In this paper we discuss on the effectiveness of using an HMM to model jointly loss and delay behavior of real communication channel. Excellent performance in modelling typical channel behavior in a set of real packet links are observed. The system parameters are found via a modified version of the EM algorithm. Hidden state analysis shows how the state variables characterize channel dynamics. State-sequence estimation is obtained by use of the Viterbi algorithm. Real-time modelling of the channel is the first step to implement adaptive communication strategies.

It is quite easy to foresee that in the next years, the future generation ultra-high speed network infrastructures and equipments will be no longer constrained only by their pure transport capacity, but also by their energy consumption costs and environmental effects. In particular, large network infrastructures are now widely recognized to play a fundamental role in the emission of greenhouse gases in the atmosphere, significantly affecting the environmental sustainability of new evolutions in network architectures as well as technological developments in communication devices. In this paper, a novel eco-sustainable routing and wavelength assignment algorithm, based on shortest path routing with an adaptive link weighting function relying on an extension of the OSPF-TE protocol to convey carbon footprint information, has been proposed to decrease the network ecological impact while balancing the traffic load and maintaining acceptable connection-blocking rate. The trade-off between load balancing and carbon footprint is also analyzed to evaluate the effectiveness of the proposed strategy within the context of a real world network.

In overloaded CDMA decision-feedback receivers may have a bit error probability of at least one user that "floors", i.e. cannot be reduced to zero when the signal-to-noise ratio increases. This problem is a consequence of the overloaded nature of the CDMA system, characterized by a very high correlation among users' signatures and corresponding high multiuser interference that the receiver is not able to cancel. In this paper we show that "floors" can be avoided by properly controlling each users' gain and propose an algorithm that, grouping users, sets gains in such a way that all users have a BER that vanishes. Simulations show that group decision-feedback receivers with simple conventional receivers as constituent blocks, have performances very close to those of the optimal ML receiver.

With an enormous range of applications, Internet of Things (IoT) has magnetized industries and academicians from everywhere. IoT facilitates operations through ubiquitous connectivity by providing Internet access to all the devices with computing capabilities. With the evolution of wireless infrastructure, the focus from simple IoT has been shifted to smart, connected and mobile IoT (M-IoT) devices and platforms, which can enable low-complexity, low-cost and efficient computing through sensors, machines, and even crowdsourcing. All these devices can be grouped under a common term of M-IoT. Even though the positive impact on applications has been tremendous, security, privacy and trust are still the major concerns for such networks and an insufficient enforcement of these requirements introduces non-negligible threats to M-IoT devices and platforms. Thus, it is important to understand the range of solutions which are available for providing a secure, privacy-compliant, and trustworthy mechanism for M-IoT. There is no direct survey available, which focuses on security, privacy, trust, secure protocols, physical layer security and handover protections in M-IoT. This paper covers such requisites and presents comparisons of state-the-art solutions for IoT which are applicable to security, privacy, and trust in smart and connected M-IoT networks. Apart from these, various challenges, applications, advantages, technologies, standards, open issues, and roadmap for security, privacy and trust are also discussed in this paper., 13 figures, 11 tables

In the last years, the research efforts in smart grids (SG) and telecommunication networks (TN) have been considerable but never converged to a common view and, due to the lack of strong interactions between the two worlds, only limited benefits have been achieved. We envision in this paper that future TN (as well as any other ICT application) will interact with the SG, enabling (1) the TN to know the energy source and cost that is currently powering its equipment, (2) to turn the TN into an active client which can request to the SG the quantity and quality (e.g. green) of energy that it needs, and (3) a service orchestration between SG supply system and TN operations. As a consequence, the enabled interoperability between TN and SG would allow TN to take energy-aware management decisions in function of energy-related information provided by the SG. For example, TN can route packets with the objective of optimizing green criteria, while SG can route the energy towards the TN clients with the objective of not wasting surpluses of green energy. These new energy and data routing capabilities can be exploited not only by SG operators and telecom carriers but also by any energy consumer/producer within the ICT world. This may include industry and institutional ICT premises, datacenters, home automation, wireless and mobile cellular networks, which will be able to implement their own energy-aware management and operations (M&O) by considering the quantity, quality and cost of the energy currently provided by the smart grid.

Human ability to foresee the near future plays a key role in everyone's life to prevent potentially dangerous situations. To be able to make predictions is crucial when people have to interact with the surrounding environment. Modeling such capability can lead to the design of automated warning systems and provide moving robots with an intelligent way of interaction with changing situation. In this work we focus on a typical urban human-scene where we aim at predicting an agent's behavior using a stochastic model. In this approach, we fuse the various factors that would contribute to a human motion in different contexts. Our method uses previously observed trajectories to build point-wise circular distributions that after combination, provide a statistical smooth prediction towards the most likely areas. More specifically, a ray-launching procedure, based on a semantic segmentation, gives a coarse scene representation for collision avoidance; a nearly-constant velocity dynamic model smooths the acceleration progression and knowledge of the agent's destination may further steer the path prediction. Experimental results in structured scenes, validate the effectiveness of the method in predicting paths in comparison to actual trajectories.

In this paper we present EnergySave, a smart energy-saving system that, by leveraging the consolidated WoL (Wake on LAN) technology, allows the remote wake-up of PCs from a centralized management server, providing easy and secure power management capabilities for local or remote IP-based networks of personal computers (PCs). We also present a lightweight web-based platform implementing the remote management interface as less intrusively as possible. Finally, we model the mathematical saving functions to be used in order to evaluate through simulation the amount of potential energy savings, and hence the whole framework effectiveness, both in the general case and in a real case scenario. Results show that significant savings are achievable provided that the hardware supports the Wake-on-LAN specifications and that proper configuration of the Web server is set-up, allowing the WoL magic packet to travel to the destination hosts and wake them up only when they are really needed.

In modern optical networks, infrastructure management is faced with the challenge of using expensive equipment and communication resources as efficiently as possible. This now includes keeping power consumption costs at a minimum and using the available optical links in a balanced way, in addition to the traditional goals of providing the best possible performance to the end customers while meeting their quality requirements. Accordingly, this paper presents a heuristic single-step lightpath routing and wavelength assignment algorithm, handling online dynamic connection requests within a fully distributed network control plane. By using shortest path routing, the presented scheme determines the best compromise solution between the users' and carrier's objectives. The former can be mainly expressed in terms of connection QoS requirements, while the latter comprises network engineering (distributing the load in order to achieve near-optimum resource usage) and containing energy consumption. This approach is able to find, in a polynomial computing time, a multiobjective optimization solution that maximizes the carriers' return of investment and supports a high number of users' request while drastically reducing the network operational expenditures, as extensively demonstrated through a simulation.

Most treatments of decentralized estimation rely on some form of track fusion, in which local track estimates and their associated covariances are communicated. This implies a great deal of communication; and it was recently proposed that by an intelligent quantization directly of measurements, the communication needs could be considerably cut. However, several issues were not discussed. The first of these is that estimation with quantized measurements requires an update with a non-Gaussian distribution, reflecting the uncertainty within the quantization "bin."; In general this would be a difficult task for dynamic estimation, but Markov-chain Monte-Carlo (MCMC, and specifically here particle filtering) techniques appear quite appropriate since the resulting system is, in essence, a nonlinear filter. The second issue is that in a realistic sensor network it is to be expected that measurements should arrive out-of-sequence. Again, a particle filter is appropriate, since the recent literature has reported particle filter modifications that accommodate nonlinear-filter updates based on new past measurements, with the need to refilter obviated. We show results that indicate a compander/particle-filter combination is a natural fit, and specifically that quite good performance is achievable with only 2-3 bits per dimension per observation. The third issue is that intelligent quantization requires that both sensor and fuser share an understanding of the quantization rule. In dynamic estimation this is a problem since both quantizer and fuser are working with only partial information; if measurements arrive out-of-sequence the problem is compounded. We therefore suggest architectures, and comment on their suitabilities for the task. A scheme based on delta-modulation appears to be promising.

Development of network-sensing and congestion-control mechanisms is one of the focus topic in the modern society of information as consequence of the huge growth in types of services, data links and connectivity. A monitoring system based on hidden Markov model is proposed and implemented such to interact with distributed Internet generator. Preliminary experiments performed in a real testbed shows excellent results in the ability to manage the source-traffic generation and adapt to the channel conditions.

An approach based on percolation lattices for modeling wireless links in urban areas is considered. The model is quite promising, but its practical application requires some refinements related to some basic hypotheses made about our analytical derivations. We present partial results of this attempt after having reviewed some of the main relationships obtained with our model in recent years. We report what we believe are the relevant open problems which still wait for a solution, along with some research lines we are following to fill this gap.

We present a fragile colour image watermarking based on the greatest solution of a bilinear fuzzy relation equation. The original image is coded with fuzzy transforms and divided in sub-images of sizes 2 × 2 called blocks. The watermark is applied on these blocks. A pre-processing phase is used to determine the best compression rate for the coding process. We test this scheme in tamper detection analysis on a sample of colour images of different sizes. Comparisons with various block-based fragile watermarking methods are presented as well.

Cloud security, due to the lack of control over leased resources, is considered one of the main inhibitors to a wider adoption of the cloud paradigm. Recently, Security Service Level Agreements (Security SLAs), contracts among cloud service providers, and cloud service customers stating the granted level of security, appear to be the main way to address such an issue. Security (continuous) monitoring is one of the needs that must be technically solved to offer effective Security SLAs: cloud customers need a simple and effective way to measure the security level and to verify that grants are being respected. In this chapter, we outline the problems related to monitoring security in the cloud, and illustrate a Security SLA-based monitoring approach. Moreover, we provide concrete examples related to offering services protected against Denial of Service (DoS) attacks and provided with continuous scanning and management of existing software vulnerabilities. The presented examples rely on the adoption of the innovative SPECS framework. This framework, developed in the context of the FP7-ICT programme project SPECS, aims at offering Security-as-a-Service using an SLA-based approach.

O objetivo deste trabalho foi gerar subsídios para o planejamento agrícola de pequenas propriedades rurais inseridas em paisagens rurais montanhosas da Serra dos Órgãos, ocupada com agricultura familiar. Apoiado em técnicas de geoprocessamento e SIGs, o trabalho demonstra os procedimentos adotados para a avaliação da aptidão agroecológica das terras por unidade ambiental, enfatizando limitações e potencialidades com base nas ofertas e restrições ambientais apresentadas em cada unidade delimitada. Os procedimentos utilizados envolveram a geração de banco de dados digital no SIG e a geração de dados básicos no campo, através de mapeamentos temáticos do meio físico, que foram associados a informações socioeconômicas, de pluviosidade e de áreas protegidas por legislação específica ou reservas existentes, constituindo assim um conjunto de informações agrossocioambientais em meio digital, o que possibilitou a delimitação de unidades ambientais e a geração de mapas interpretativos úteis ao planejamento. Em cada uma das unidades defi nidas, foi associado um conjunto de indicações relativas às suas limitações e potencialidades, fragilidades e riscos. O modelo de aptidão agroecológica considerado é feito por unidades ambientais delimitadas, e envolve a indicação de uso, manejo e sugestão de alternativas sustentáveis de utilização, visando reduzir os efeitos negativos sobre o meio ambiente e incrementar a qualidade ambiental. Conclui-se que a metodologia apresentou- se adequada ao planejamento agroambiental de áreas com relevo movimentado, pois onde foi identifi cada a ocorrência de compartimentos mais frágeis e problemáticos, em função dos solos, declividade, maior suscetibilidade aos processos erosivos e maior grau de fragilidade ambiental, estes se encaixaram nas classes de aptidão inapta, restrita, preservação ambiental ou recomposição de matas. Made available in DSpace on 2018-03-29T00:34:40Z (GMT). No. of bitstreams: 1 CalderanoFilhoetal2007Aptidaoagroecologica.pdf: 851428 bytes, checksum: fd85c3c5ec129ad93b58558678f106cc (MD5) Previous issue date: 2011-01-24

Made available in DSpace on 2020-08-28T04:11:01Z (GMT). No. of bitstreams: 1 Alteracoes-da-cobertura-latossolica-sobre-rochas-calcarias-da-regiao-semi-arida-do-Estado-da-Bahia-1999.pdf: 4231099 bytes, checksum: 2f793e801e30aaff7b4eefb20b873fb0 (MD5) Previous issue date: 1999