A modified AHP algorithm for network selection

This paper addresses the concept of ranking networks to the multiple criteria of customers to find the best and alternative networks. The use of modified AHP algorithm has been shown to provide better network ranking for reasonable customer objectives than the traditional AHP method. Both the traditional method and the proposed method produced results subjective to the customer requirements. However, the proposed method is more intuitive to the customers through direct capture of their exact requirements rather than an interpretation of their requirements through pair-wise comparison alone. Also, the proposed method is less time-consuming and results are of higher quality

The SIMRAND methodology: Theory and application for the simulation of research and development projects

A research and development (R&D) project often involves a number of decisions that must be made concerning which subset of systems or tasks are to be undertaken to achieve the goal of the R&D project. To help in this decision making, SIMRAND (SIMulation of Research ANd Development Projects) is a methodology for the selection of the optimal subset of systems or tasks to be undertaken on an R&D project. Using alternative networks, the SIMRAND methodology models the alternative subsets of systems or tasks under consideration. Each path through an alternative network represents one way of satisfying the project goals. Equations are developed that relate the system or task variables to the measure of reference. Uncertainty is incorporated by treating the variables of the equations probabilistically as random variables, with cumulative distribution functions assessed by technical experts. Analytical techniques of probability theory are used to reduce the complexity of the alternative networks. Cardinal utility functions over the measure of preference are assessed for the decision makers. A run of the SIMRAND Computer I Program combines, in a Monte Carlo simulation model, the network structure, the equations, the cumulative distribution functions, and the utility functions

Alternative networks: toward global access to the Internet for all

It is often said that the Internet is ubiquitous in our daily lives, but this holds true only for those who can easily access it. In fact, billions of people are still digitally disconnected, as bringing connectivity to certain zones does not make a good business case. The only solution for these unsatisfied potential users is to directly undertake the building of the infrastructure required to obtaining access to the Internet, typically forming groups in order to share the corresponding cost. This article presents a global classification and a summary of the main characteristics of different Alternative Network deployments that have arisen in recent years with an aim to provide Internet services in places where mainstream network deployments do not exist or are not adequate solutions. The Global Access to the Internet for All Research Group of the Internet Research Task Force, where all authors actively participate, is interested in documenting these emerging deployments. As an outcome of this work, a classification has converged by consensus, where five criteria have been identified and, based on them, four different types of Alternative Networks have been identified and described with real-world examples. Such a classification is useful for a deeper understanding of the common characteristics behind existing and emerging Alternative Networks

Scalable bloom-filter based content dissemination in community networks using information centric principles

Information-Centric Networking (ICN) is a new communication paradigm that shifts the focus from content location to content objects themselves. Users request the content by its name or some other form of identifier. Then, the network is responsible for locating the requested content and sending it to the users. Despite a large number of works on ICN in recent years, the problem of scalability of ICN systems has not been studied and addressed adequately. This is especially true when considering real-world deployments and the so-called alternative networks such as community networks. In this work, we explore the applicability of ICN principles in the challenging and unpredictable environments of community networks. In particular, we focus on stateless content dissemination based on Bloom filters (BFs). We highlight the scalability limitations of the classical single-stage BF based approach and argue that by enabling multiple BF stages would lead to performance enhancements. That is, a multi-stage BF based content dissemination mechanism could support large network topologies with heterogeneous traffic and diverse channel conditions. In addition to scalability improvements, this approach also is more secure with regard to Denial of Service attacks

On the effects of alternative optima in context-specific metabolic model predictions

Recent methodological developments have facilitated the integration of high-throughput data into genome-scale models to obtain context-specific metabolic reconstructions. A unique solution to this data integration problem often may not be guaranteed, leading to a multitude of context-specific predictions equally concordant with the integrated data. Yet, little attention has been paid to the alternative optima resulting from the integration of context-specific data. Here we present computational approaches to analyze alternative optima for different context-specific data integration instances. By using these approaches on metabolic reconstructions for the leaf of Arabidopsis thaliana and the human liver, we show that the analysis of alternative optima is key to adequately evaluating the specificity of the predictions in particular cellular contexts. While we provide several ways to reduce the ambiguity in the context-specific predictions, our findings indicate that the existence of alternative optimal solutions warrant caution in detailed context-specific analyses of metabolism

From Caenorhabditis elegans to the Human Connectome: A Specific Modular Organisation Increases Metabolic, Functional, and Developmental Efficiency

The connectome, or the entire connectivity of a neural system represented by network, ranges various scales from synaptic connections between individual neurons to fibre tract connections between brain regions. Although the modularity they commonly show has been extensively studied, it is unclear whether connection specificity of such networks can already be fully explained by the modularity alone. To answer this question, we study two networks, the neuronal network of C. elegans and the fibre tract network of human brains yielded through diffusion spectrum imaging (DSI). We compare them to their respective benchmark networks with varying modularities, which are generated by link swapping to have desired modularity values but otherwise maximally random. We find several network properties that are specific to the neural networks and cannot be fully explained by the modularity alone. First, the clustering coefficient and the characteristic path length of C. elegans and human connectomes are both higher than those of the benchmark networks with similar modularity. High clustering coefficient indicates efficient local information distribution and high characteristic path length suggests reduced global integration. Second, the total wiring length is smaller than for the alternative configurations with similar modularity. This is due to lower dispersion of connections, which means each neuron in C. elegans connectome or each region of interest (ROI) in human connectome reaches fewer ganglia or cortical areas, respectively. Third, both neural networks show lower algorithmic entropy compared to the alternative arrangements. This implies that fewer rules are needed to encode for the organisation of neural systems

From community networks to off-the-cloud toolkits art and DIY networking

The last fifteen years, and especially parallel to the increasing datafication of everyday life, an emerging scene of network practitioners from different fields has been actively involved in building alternative networks of communication and file-sharing. Among the practitioners of this DIY networking scene, a growing number of artists have been playing a crucial role offering alternatives and critical perspectives. The aim of this paper is to present and discuss these particular initiatives, while locating them within a context and relating them to the needs of the particular time-period