An improved method for discovering link criticality in transport networks

Quantitatively assessing the importance or criticality of each link in a network is of practical value to operators, as that can help them to increase the network's resilience, provide more efficient services, or improve some other aspect of the service. Betweenness is a graph-theoretical measure of centrality that can be applied to communication networks to evaluate link importance. However, as we illustrate in this paper, the basic definition of betweenness centrality produces inaccurate estimations as it does not take into account some aspects relevant to networking, such as the heterogeneity in link capacity or the difference between node-pairs in their contribution to the total traffic. A new algorithm for discovering link centrality in transport networks is proposed in this paper. It requires only static or semi-static network and topology attributes, and yet produces estimations of good accuracy, as verified through extensive simulations. Its potential value is demonstrated by an example application. In the example, the simple shortest-path routing algorithm is improved in such a way that it outperforms other more advanced algorithms in terms of blocking ratio

Allocation rules on networks

When allocating a resource, geographical and infrastructural constraints have to be taken into account. We study the problem of distributing a resource through a network from sources endowed with the resource to citizens with claims. A link between a source and an agent depicts the possibility of a transfer from the source to the agent. Given the supplies at each source, the claims of citizens, and the network, the question is how to allocate the available resources among the citizens. We consider a simple allocation problem that is free of network constraints, where the total amount can be freely distributed. The simple allocation problem is a claims problem where the total amount of claims is greater than what is available. We focus on consistent and resource monotonic rules in claims problems that satisfy equal treatment of equals. We call these rules fairness principles and we extend fairness principles to allocation rules on networks. We require that for each pair of citizens in the network, the extension is robust with respect to the fairness principle. We call this condition pairwise robustness with respect to the fairness principle. We provide an algorithm and show that each fairness principle has a unique extension which is pairwise robust with respect to the fairness principle. We give applications of the algorithm for three fairness principles: egalitarianism, proportionality and equal sacrifice.

Enhanced fault recovery methods for protected traffic services in GMPLS networks

Les noves tecnologies a la xarxa ens permeten transportar, cada cop més, grans volums d' informació i trànsit de xarxa amb diferents nivells de prioritat. En aquest escenari, on s'ofereix una millor qualitat de servei, les conseqüències d'una fallada en un enllaç o en un node esdevenen més importants. Multiprotocol Lavel Switching (MPLS), juntament amb l'extensió a MPLS generalitzat (GMPLS), proporcionen mecanismes ràpids de recuperació de fallada establint camins, Label Switch Path (LSPs), redundants per ser utilitzats com a camins alternatius. En cas de fallada podrem utilitzar aquests camins per redireccionar el trànsit. El principal objectiu d'aquesta tesi ha estat millorar alguns dels actuals mecanismes de recuperació de fallades MPLS/GMPLS, amb l'objectiu de suportar els requeriments de protecció dels serveis proporcionats per la nova Internet. Per tal de fer aquesta avaluació s'han tingut en compte alguns paràmetres de qualitat de protecció com els temps de recuperació de fallada, les pèrdues de paquets o el consum de recursos. En aquesta tesi presentem una completa revisió i comparació dels principals mètodes de recuperació de fallada basats en MPLS. Aquest anàlisi inclou els mètodes de protecció del camí (backups globals, backups inversos i protecció 1+1), els mètodes de protecció locals i els mètodes de protecció de segments. També s'ha tingut en compte l'extensió d'aquests mecanismes a les xarxes òptiques mitjançant el pla de control proporcionat per GMPLS. En una primera fase d'aquest treball, cada mètode de recuperació de fallades és analitzat sense tenir en compte restriccions de recursos o de topologia. Aquest anàlisi ens dóna una primera classificació dels millors mecanismes de protecció en termes de pèrdues de paquets i temps de recuperació. Aquest primer anàlisi no és aplicable a xarxes reals. Per tal de tenir en compte aquest nou escenari, en una segona fase, s'analitzen els algorismes d'encaminament on sí tindrem en compte aquestes limitacions i restriccions de la xarxa. Es presenten alguns dels principals algorismes d'encaminament amb qualitat de servei i alguna de les principals propostes d'encaminament per xarxes MPLS. La majoria dels actual algorismes d'encaminament no tenen en compte l'establiment de rutes alternatives o utilitzen els mateixos objectius per seleccionar els camins de treball i els de protecció. Per millorar el nivell de protecció introduïm i formalitzem dos nous conceptes: la Probabilitat de fallada de la xarxa i l'Impacte de fallada. Un anàlisi de la xarxa a nivell físic proporciona un primer element per avaluar el nivell de protecció en termes de fiabilitat i disponibilitat de la xarxa. Formalitzem l'impacte d'una fallada, quant a la degradació de la qualitat de servei (en termes de retard i pèrdues de paquets). Expliquem la nostra proposta per reduir la probabilitat de fallada i l'impacte de fallada. Per últim fem una nova definició i classificació dels serveis de xarxa segons els valors requerits de probabilitat de fallada i impacte. Un dels aspectes que destaquem dels resultats d'aquesta tesi és que els mecanismes de protecció global del camí maximitzen la fiabilitat de la xarxa, mentre que les tècniques de protecció local o de segments de xarxa minimitzen l'impacte de fallada. Per tant podem assolir mínim impacte i màxima fiabilitat aplicant protecció local a tota la xarxa, però no és una proposta escalable en termes de consum de recursos. Nosaltres proposem un mecanisme intermig, aplicant protecció de segments combinat amb el nostre model d'avaluació de la probabilitat de fallada. Resumint, aquesta tesi presenta diversos mecanismes per l'anàlisi del nivell de protecció de la xarxa. Els resultats dels models i mecanismes proposats milloren la fiabilitat i minimitzen l'impacte d'una fallada en la xarxa.

Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research

The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research.

Theory and practice in value management: a reply to Ellis et al (2005)

The constructivist model of 'soft' value management (VM) is contrasted with the VM discourse appropriated by cost consultants who operate from within UK quantity surveying (QS) practices. The enactment of VM by cost consultants is shaped by the institutional context within which they operate and is not necessarily representative of VM practice per se. Opportunities to perform VM during the formative stages of design are further constrained by the positivistic rhetoric that such practitioners use to conceptualize and promote their services. The complex interplay between VM theory and practice is highlighted and analysed from a non-deterministic perspective. Codified models of 'best practice' are seen to be socially constructed and legitimized through human interaction in the context of interorganizational networks. Published methodologies are seen to inform practice in only a loose and indirect manner, with extensive scope for localized improvization. New insights into the relationship between VM theory and practice are derived from the dramaturgical metaphor. The social reality of VM is seen to be constituted through scripts and performances, both of which are continuously contested across organizational arenas. It is concluded that VM defies universal definition and is conceptualized and enacted differently across different localized contexts.

Teachers' networks in and out of school

A 'mapping task' was used to explore the networks available to head teachers, school coordinators and local authority staff. Beginning from an ego-centred perspective on networks, we illustrate a number of key analytic categories, including brokerage, formality, and strength and weakness of links with reference to a single UK primary school. We describe how teachers differentiate between the strength of network links and their value, which is characteristically related to their potential impact on classroom practice.

A new RBF neural network with boundary value constraints

We present a novel topology of the radial basis function (RBF) neural network, referred to as the boundary value constraints (BVC)-RBF, which is able to automatically satisfy a set of BVC. Unlike most existing neural networks whereby the model is identified via learning from observational data only, the proposed BVC-RBF offers a generic framework by taking into account both the deterministic prior knowledge and the stochastic data in an intelligent manner. Like a conventional RBF, the proposed BVC-RBF has a linear-in-the-parameter structure, such that it is advantageous that many of the existing algorithms for linear-in-the-parameters models are directly applicable. The BVC satisfaction properties of the proposed BVC-RBF are discussed. Finally, numerical examples based on the combined D-optimality-based orthogonal least squares algorithm are utilized to illustrate the performance of the proposed BVC-RBF for completeness.

The state estimation of flow demands in gas networks from sparse pressure telemetry

This paper presents novel observer-based techniques for the estimation of flow demands in gas networks, from sparse pressure telemetry. A completely observable model is explored, constructed by incorporating difference equations that assume the flow demands are steady. Since the flow demands usually vary slowly with time, this is a reasonable approximation. Two techniques for constructing robust observers are employed: robust eigenstructure assignment and singular value assignment. These techniques help to reduce the effects of the system approximation. Modelling error may be further reduced by making use of known profiles for the flow demands. The theory is extended to deal successfully with the problem of measurement bias. The pressure measurements available are subject to constant biases which degrade the flow demand estimates, and such biases need to be estimated. This is achieved by constructing a further model variation that incorporates the biases into an augmented state vector, but now includes information about the flow demand profiles in a new form.

Memory and burstiness in dynamic networks

A discrete-time random process is described, which can generate bursty sequences of events. A Bernoulli process, where the probability of an event occurring at time t is given by a fixed probability x, is modified to include a memory effect where the event probability is increased proportionally to the number of events that occurred within a given amount of time preceding t. For small values of x the interevent time distribution follows a power law with exponent −2−x. We consider a dynamic network where each node forms, and breaks connections according to this process. The value of x for each node depends on the fitness distribution, \rho(x), from which it is drawn; we find exact solutions for the expectation of the degree distribution for a variety of possible fitness distributions, and for both cases where the memory effect either is, or is not present. This work can potentially lead to methods to uncover hidden fitness distributions from fast changing, temporal network data, such as online social communications and fMRI scans.

Mapping power law distributions in digital health social networks: methods, interpretations, and practical implications

BACKGROUND: Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. OBJECTIVES: The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. METHODS: Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. RESULTS: All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R(2) values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). CONCLUSIONS: This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns can be replicated in networks that are managed by other organizations, and we conjecture that patterns observed in this study could be found in other DHSNs. Future research should analyze network growth over time and examine the characteristics and survival rates of superusers.

Investigating relationships within and between category networks in Wikipedia

This work maps and analyses cross-citations in the areas of Biology, Mathematics, Physics and Medicine in the English version of Wikipedia, which are represented as an undirected complex network where the entries correspond to nodes and the citations among the entries are mapped as edges. We found a high value of clustering coefficient for the areas of Biology and Medicine, and a small value for Mathematics and Physics. The topological organization is also different for each network, including a modular structure for Biology and Medicine, a sparse structure for Mathematics and a dense core for Physics. The networks have degree distributions that can be approximated by a power-law with a cut-off. The assortativity of the isolated networks has also been investigated and the results indicate distinct patterns for each subject. We estimated the betweenness centrality of each node considering the full Wikipedia network, which contains the nodes of the four subjects and the edges between them. In addition, the average shortest path length between the subjects revealed a close relationship between the subjects of Biology and Physics, and also between Medicine and Physics. Our results indicate that the analysis of the full Wikipedia network cannot predict the behavior of the isolated categories since their properties can be very different from those observed in the full network. (C) 2011 Elsevier Ltd. All rights reserved.

More than just a transaction: conceptualising industry-based networks for virtual trading communities

This paper addresses the questions of why failure in industry-based networks has been so persistent and whether it is possible to avoid failure and achieve success in internet based markets [iMarketplaces]. A better explanation of implementation failures is important for both improved empirical outcomes and theory building. We construct a theoretical framework based on Bijker’s technology frame (1995) and a contextualization typology developed by Nowotny, Scott and Gibbons (2001). The framework helps us understand how industry-based networks function, why they fail and how we can apply the framework to assist better empirical outcomes. In this paper we apply our framework to Food Connect Australia, a vertically integrated marketplace, representative of the first wave of B2B markets. Sponsors of these iMarketplaces were quick to see and exploit the opportunities online access offered to bring together large numbers of buyers and sellers in new ways. However a lack of understanding of firstly, what represented true value in these networks and secondly, how to achieve buy-in at sustainable levels, meant that many of these first wave sites failed. Application of our framework reveals why there has been a radical shift from the trading role originally envisioned for these sites to the information hub model of the iMarketplace that industry is now being urged to adopt (Berryman and Heck, 2001).

Virtual communities of practice for regional small businesses: bringing informal networks online

Virtual communities of practice (VCoPs) are online business networks which are increasingly used by large organisations as a key strategy for creating value in the knowledge-based economy of the 21st Century.This paper examines the applicability of VCoPs to cross-industry regionally clustered small business networks. Interviews conducted with government and industry informants in two regional areas of Australia indicate that these strategies used for establishing VCoPs are applicable to such small business networks. Both regions had regional networks with active member involvement displaying CoP characteristics. Significant social capital existed on which VCoPs could be built, and there were viable alternatives to satisfy the roles of sponsors and leaders. There were, however, significant impediments that will have to be addressed before VCoPs can be  implemented such as the apparent reluctance of many SME owners to use the Internet and ICT generally, and the preference for informal networking. Funding to ensure that VCoPs are sustainable was also an issue. VCoPs appear to be extremely useful in linking small businesses in regional areas and in the development of viable regional clusters.

Virtual communities of enterprise value creation potential for regional clusters

The research examines regionally networked small business practices. A new concept Virtual Communities of Enterprise is proferred to explain the nature of knowledge sharing both interpersonally and online, and its potential for creating value for small businesses and their regions. Social capital emerges as an essential pre-requisite for accessing value.

T-OSN : a trust evaluation model in online social networks

Now days, the online social networks (OSN) have gained considerable popularity. More and more people use OSN to share their interests and make friends, also the OSN helps users overcome the geographical barriers. With the development of OSN, there is an important problem users have to face that is trust evaluation. Before user makes friends with a stranger, the user need to consider the following issues: Can a stranger be trusted? How much the stranger can be trusted? How to measure the trust of a stranger? In this paper, we take two factors, Degree and Contact Interval into consideration, which produce a new trust evaluation model (T-OSN). T-OSN is aimed to solve how to evaluate the trust value of an OSN user, also which is more efficient, more reliable and easy to implement. Base on our research, this model can be used in wide range, such as online social network (OSN) trust evaluation, mobile network message forwarding, ad hoc wireless networking, routing message on Internet and peer-to-peer file sharing network. The T-OSN model has following obvious advantages compare to other trust evaluate methods. First of all, it is not base on features of traditional social network, such as, distance and shortest path. We choose the special features of OSN to build up the model, that is including numbers of friends(Degree) and contact frequency(Contact Interval). These species features makes our model more suitable to evaluate OSN users trust value. Second, the formulations of our model are quite simple but effective. That means, to calculate the result by using our formulations will not cost too much resources. Last but not least, our model is easy to implement for an OSN website, because of the features that we used in our model, such as numbers of friends and contact frequency are easy to obtain. To sum up, our model is using a few resources to obtain a valuable trust value that can help OSN users to solve an important security problem, we believe that will be big step - or development of OSN.