A Fast and Fault-Tolerant Distributed Algorithm for Near-Optimal TDMA Scheduling in WSNs

The time division multiple access (TDMA) based channel access mechanisms perform better than the contention based channel access mechanisms, in terms of channel utilization, reliability and power consumption, specially for high data rate applications in wireless sensor networks (WSNs). Most of the existing distributed TDMA scheduling techniques can be classified as either static or dynamic. The primary purpose of static TDMA scheduling algorithms is to improve the channel utilization by generating a schedule of smaller length. But, they usually take longer time to schedule, and hence, are not suitable for WSNs, in which the network topology changes dynamically. On the other hand, dynamic TDMA scheduling algorithms generate a schedule quickly, but they are not efficient in terms of generated schedule length. In this paper, we propose a novel scheme for TDMA scheduling in WSNs, which can generate a compact schedule similar to static scheduling algorithms, while its runtime performance can be matched with those of dynamic scheduling algorithms. Furthermore, the proposed distributed TDMA scheduling algorithm has the capability to trade-off schedule length with the time required to generate the schedule. This would allow the developers of WSNs, to tune the performance, as per the requirement of prevalent WSN applications, and the requirement to perform re-scheduling. Finally, the proposed TDMA scheduling is fault-tolerant to packet loss due to erroneous wireless channel. The algorithm has been simulated using the Castalia simulator to compare its performance with those of others in terms of generated schedule length and the time required to generate the TDMA schedule. Simulation results show that the proposed algorithm generates a compact schedule in a very less time.

Community structure in real-world networks from a non-parametrical synchronization-based dynamical approach

[EN]This work analyzes the problem of community structure in real-world networks based on the synchronization of nonidentical coupled chaotic Rössler oscillators each one characterized by a defined natural frequency, and coupled according to a predefined network topology. The interaction scheme contemplates an uniformly increasing coupling force to simulate a society in which the association between the agents grows in time. To enhance the stability of the correlated states that could emerge from the synchronization process, we propose a parameterless mechanism that adapts the characteristic frequencies of coupled oscillators according to a dynamic connectivity matrix deduced from correlated data. We show that the characteristic frequency vector that results from the adaptation mechanism reveals the underlying community structure present in the network.

利用网络拓扑法计算网损微增率

本文提出一个计算网损微增率的新途径。应用网络拓扑方法得到的网损修正值的直接数学表达式,不仅可利用系统潮流进行直接计算,而且有明确的物理概念,可用于实时经济调度。文中给出了计算方法和实例。

Reti complesse e analisi del segnale elettroencefalografico

The identification of subject-specific traits extracted from patterns of brain activity still represents an important challenge. The need to detect distinctive brain features, which is relevant for biometric and brain computer interface systems, has been also emphasized in monitoring the effect of clinical treatments and in evaluating the progression of brain disorders. Graph theory and network science tools have revealed fundamental mechanisms of functional brain organization in resting-state M/EEG analysis. Nevertheless, it is still not clearly understood how several methodological aspects may bias the topology of the reconstructed functional networks. In this context, the literature shows inconsistency in the chosen length of the selected epochs, impeding a meaningful comparison between results from different studies. In this study we propose an approach which aims to investigate the existence of a distinctive functional core (sub-network) using an unbiased reconstruction of network topology. Brain signals from a public and freely available EEG dataset were analyzed using a phase synchronization based measure, minimum spanning tree and k-core decomposition. The analysis was performed for each classical brain rhythm separately. Furthermore, we aim to provide a network approach insensitive to the effects that epoch length has on functional connectivity (FC) and network reconstruction. Two different measures, the phase lag index (PLI) and the Amplitude Envelope Correlation (AEC), were applied to EEG resting-state recordings for a group of eighteen healthy volunteers. Weighted clustering coefficient (CCw), weighted characteristic path length (Lw) and minimum spanning tree (MST) parameters were computed to evaluate the network topology. The analysis was performed on both scalp and source-space data. Results about distinctive functional core, show highest classification rates from k-core decomposition in gamma (EER=0.130, AUC=0.943) and high beta (EER=0.172, AUC=0.905) frequency bands. Results from scalp analysis concerning the influence of epoch length, show a decrease in both mean PLI and AEC values with an increase in epoch length, with a tendency to stabilize at a length of 12 seconds for PLI and 6 seconds for AEC. Moreover, CCw and Lw show very similar behaviour, with metrics based on AEC more reliable in terms of stability. In general, MST parameters stabilize at short epoch lengths, particularly for MSTs based on PLI (1-6 seconds versus 4-8 seconds for AEC). At the source-level the results were even more reliable, with stability already at 1 second duration for PLI-based MSTs. Our results confirm that EEG analysis may represent an effective tool to identify subject-specific characteristics that may be of great impact for several bioengineering applications. Regarding epoch length, the present work suggests that both PLI and AEC depend on epoch length and that this has an impact on the reconstructed network topology, particularly at the scalp-level. Source-level MST topology is less sensitive to differences in epoch length, therefore enabling the comparison of brain network topology between different studies.

Identifying vibrations that destabilize crystals and characterize the glassy state

Greaves, George; Meneau, F.; Majerus, O.; Jones, D.G., (2005) 'Identifying vibrations that destabilize crystals and characterize the glassy state', Science 308(5726) pp.1299-1302 RAE2008

A randomized solution to BGP divergence

The Border Gateway Protocol (BGP) is an interdomain routing protocol that allows each Autonomous System (AS) to define its own routing policies independently and use them to select the best routes. By means of policies, ASes are able to prevent some traffic from accessing their resources, or direct their traffic to a preferred route. However, this flexibility comes at the expense of a possibility of divergence behavior because of mutually conflicting policies. Since BGP is not guaranteed to converge even in the absence of network topology changes, it is not safe. In this paper, we propose a randomized approach to providing safety in BGP. The proposed algorithm dynamically detects policy conflicts, and tries to eliminate the conflict by changing the local preference of the paths involved. Both the detection and elimination of policy conflicts are performed locally, i.e. by using only local information. Randomization is introduced to prevent synchronous updates of the local preferences of the paths involved in the same conflict.

Dynamic Server Selection in the Internet

As distributed information services like the World Wide Web become increasingly popular on the Internet, problems of scale are clearly evident. A promising technique that addresses many of these problems is service (or document) replication. However, when a service is replicated, clients then need the additional ability to find a "good" provider of that service. In this paper we report on techniques for finding good service providers without a priori knowledge of server location or network topology. We consider the use of two principal metrics for measuring distance in the Internet: hops, and round-trip latency. We show that these two metrics yield very different results in practice. Surprisingly, we show data indicating that the number of hops between two hosts in the Internet is not strongly correlated to round-trip latency. Thus, the distance in hops between two hosts is not necessarily a good predictor of the expected latency of a document transfer. Instead of using known or measured distances in hops, we show that the extra cost at runtime incurred by dynamic latency measurement is well justified based on the resulting improved performance. In addition we show that selection based on dynamic latency measurement performs much better in practice that any static selection scheme. Finally, the difference between the distribution of hops and latencies is fundamental enough to suggest differences in algorithms for server replication. We show that conclusions drawn about service replication based on the distribution of hops need to be revised when the distribution of latencies is considered instead.

Generating Representative ISP Technologies From First-Principles

Understanding and modeling the factors that underlie the growth and evolution of network topologies are basic questions that impact capacity planning, forecasting, and protocol research. Early topology generation work focused on generating network-wide connectivity maps, either at the AS-level or the router-level, typically with an eye towards reproducing abstract properties of observed topologies. But recently, advocates of an alternative "first-principles" approach question the feasibility of realizing representative topologies with simple generative models that do not explicitly incorporate real-world constraints, such as the relative costs of router configurations, into the model. Our work synthesizes these two lines by designing a topology generation mechanism that incorporates first-principles constraints. Our goal is more modest than that of constructing an Internet-wide topology: we aim to generate representative topologies for single ISPs. However, our methods also go well beyond previous work, as we annotate these topologies with representative capacity and latency information. Taking only demand for network services over a given region as input, we propose a natural cost model for building and interconnecting PoPs and formulate the resulting optimization problem faced by an ISP. We devise hill-climbing heuristics for this problem and demonstrate that the solutions we obtain are quantitatively similar to those in measured router-level ISP topologies, with respect to both topological properties and fault-tolerance.

Evolution of networks and sequences in eukaryotic cell cycle control.

The molecular networks regulating the G1-S transition in budding yeast and mammals are strikingly similar in network structure. However, many of the individual proteins performing similar network roles appear to have unrelated amino acid sequences, suggesting either extremely rapid sequence evolution, or true polyphyly of proteins carrying out identical network roles. A yeast/mammal comparison suggests that network topology, and its associated dynamic properties, rather than regulatory proteins themselves may be the most important elements conserved through evolution. However, recent deep phylogenetic studies show that fungal and animal lineages are relatively closely related in the opisthokont branch of eukaryotes. The presence in plants of cell cycle regulators such as Rb, E2F and cyclins A and D, that appear lost in yeast, suggests cell cycle control in the last common ancestor of the eukaryotes was implemented with this set of regulatory proteins. Forward genetics in non-opisthokonts, such as plants or their green algal relatives, will provide direct information on cell cycle control in these organisms, and may elucidate the potentially more complex cell cycle control network of the last common eukaryotic ancestor.

Intrinsic measure of diversity gains in generalised distributed antenna systems with cooperative users

The diversity gains achievable in the generalised distributed antenna system with cooperative users (GDAS-CU) are considered. A GDAS-CU is comprised of M largely separated access points (APs) at one side of the link, and N geographically closed user terminals (UTs) at the other side. The UTs are collaborating together to enhance the system performance, where an idealised message sharing among the UTs is assumed. First, geometry-based network models are proposed to describe the topology of a GDAS-CU. The mean cross-correlation coefficients of signals received from non-collocated APs and UTs are calculated based on the network topology and the correlation models derived from the empirical data. The analysis is also extendable to more general scenarios where the APs are placed in a clustered form due to the constraints of street layout or building structure. Subsequently, a generalised signal attenuation model derived from several stochastic ray-tracing-based pathloss models is applied to describe the power-decaying pattern in urban built-up areas, where the GDAS-CU may be deployed. Armed with the cross-correlation and pathloss model preliminaries, an intrinsic measure of cooperative diversity obtainable from a GDAS-CU is then derived, which is the number of independent fading channels that can be averaged over to detect symbols. The proposed analytical framework would provide critical insight into the degree of possible performance improvement when combining multiple copies of the received signal in such systems.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Picking up the Pieces: Self-Healing in reconfigurable networks

We consider the problem of self-healing in networks that are reconfigurable in the sense that they can change their topology during an attack. Our goal is to maintain connectivity in these networks, even in the presence of repeated adversarial node deletion, by carefully adding edges after each attack. We present a new algorithm, DASH, that provably ensures that: 1) the network stays connected even if an adversary deletes up to all nodes in the network; and 2) no node ever increases its degree by more than 2 log n, where n is the number of nodes initially in the network. DASH is fully distributed; adds new edges only among neighbors of deleted nodes; and has average latency and bandwidth costs that are at most logarithmic in n. DASH has these properties irrespective of the topology of the initial network, and is thus orthogonal and complementary to traditional topology- based approaches to defending against attack. We also prove lower-bounds showing that DASH is asymptotically optimal in terms of minimizing maximum degree increase over multiple attacks. Finally, we present empirical results on power-law graphs that show that DASH performs well in practice, and that it significantly outperforms naive algorithms in reducing maximum degree increase.

Droop setting design for multi-terminal HVDC grids considering voltage deviation impacts

In multi-terminal high voltage direct current (HVDC) grids, the widely deployed droop control strategies will cause a non-uniform voltage deviation on the power flow, which is determined by the network topology and droop settings. This voltage deviation results in an inconsistent power flow pattern when the dispatch references are changed, which could be detrimental to the operation and seamless integration of HVDC grids. In this paper, a novel droop setting design method is proposed to address this problem for a more precise power dispatch. The effects of voltage deviations on the power sharing accuracy and transmission loss are analysed. This paper shows that there is a trade-off between minimizing the voltage deviation, ensuring a proper power delivery and reducing the total transmission loss in the droop setting design. The efficacy of the proposed method is confirmed by simulation studies.

Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

Flexible management of bandwidth and redundancy in fieldbuses

Os sistemas distribuídos embarcados (Distributed Embedded Systems – DES) têm sido usados ao longo dos últimos anos em muitos domínios de aplicação, da robótica, ao controlo de processos industriais passando pela aviónica e pelas aplicações veiculares, esperando-se que esta tendência continue nos próximos anos. A confiança no funcionamento é uma propriedade importante nestes domínios de aplicação, visto que os serviços têm de ser executados em tempo útil e de forma previsível, caso contrário, podem ocorrer danos económicos ou a vida de seres humanos poderá ser posta em causa. Na fase de projecto destes sistemas é impossível prever todos os cenários de falhas devido ao não determinismo do ambiente envolvente, sendo necessária a inclusão de mecanismos de tolerância a falhas. Adicionalmente, algumas destas aplicações requerem muita largura de banda, que também poderá ser usada para a evolução dos sistemas, adicionandolhes novas funcionalidades. A flexibilidade de um sistema é uma propriedade importante, pois permite a sua adaptação às condições e requisitos envolventes, contribuindo também para a simplicidade de manutenção e reparação. Adicionalmente, nos sistemas embarcados, a flexibilidade também é importante por potenciar uma melhor utilização dos, muitas vezes escassos, recursos existentes. Uma forma evidente de aumentar a largura de banda e a tolerância a falhas dos sistemas embarcados distribuídos é a replicação dos barramentos do sistema. Algumas soluções existentes, quer comerciais quer académicas, propõem a replicação dos barramentos para aumento da largura de banda ou para aumento da tolerância a falhas. No entanto e quase invariavelmente, o propósito é apenas um, sendo raras as soluções que disponibilizam uma maior largura de banda e um aumento da tolerância a falhas. Um destes raros exemplos é o FlexRay, com a limitação de apenas ser permitido o uso de dois barramentos. Esta tese apresentada e discute uma proposta para usar a replicação de barramentos de uma forma flexível com o objectivo duplo de aumentar a largura de banda e a tolerância a falhas. A flexibilidade dos protocolos propostos também permite a gestão dinâmica da topologia da rede, sendo o número de barramentos apenas limitado pelo hardware/software. As propostas desta tese foram validadas recorrendo ao barramento de campo CAN – Controller Area Network, escolhido devido à sua grande implantação no mercado. Mais especificamente, as soluções propostas foram implementadas e validadas usando um paradigma que combina flexibilidade com comunicações event-triggered e time-triggered: o FTT – Flexible Time- Triggered. No entanto, uma generalização para CAN nativo é também apresentada e discutida. A inclusão de mecanismos de replicação do barramento impõe a alteração dos antigos protocolos de replicação e substituição do nó mestre, bem como a definição de novos protocolos para esta finalidade. Este trabalho tira partido da arquitectura centralizada e da replicação do nó mestre para suportar de forma eficiente e flexível a replicação de barramentos. Em caso de ocorrência de uma falta num barramento (ou barramentos) que poderia provocar uma falha no sistema, os protocolos e componentes propostos nesta tese fazem com que o sistema reaja, mudando para um modo de funcionamento degradado. As mensagens que estavam a ser transmitidas nos barramentos onde ocorreu a falta são reencaminhadas para os outros barramentos. A replicação do nó mestre baseia-se numa estratégia líder-seguidores (leaderfollowers), onde o líder (leader) controla todo o sistema enquanto os seguidores (followers) servem como nós de reserva. Se um erro ocorrer no nó líder, um dos nós seguidores passará a controlar o sistema de uma forma transparente e mantendo as mesmas funcionalidades. As propostas desta tese foram também generalizadas para CAN nativo, tendo sido para tal propostos dois componentes adicionais. É, desta forma possível ter as mesmas capacidades de tolerância a falhas ao nível dos barramentos juntamente com a gestão dinâmica da topologia de rede. Todas as propostas desta tese foram implementadas e avaliadas. Uma implementação inicial, apenas com um barramento foi avaliada recorrendo a uma aplicação real, uma equipa de futebol robótico onde o protocolo FTT-CAN foi usado no controlo de movimento e da odometria. A avaliação do sistema com múltiplos barramentos foi feita numa plataforma de teste em laboratório. Para tal foi desenvolvido um sistema de injecção de faltas que permite impor faltas nos barramentos e nos nós mestre, e um sistema de medida de atrasos destinado a medir o tempo de resposta após a ocorrência de uma falta.