Energy efficient architectures and techniques for green radio access networks

Energy consumption in wireless networks, and in particular in cellular mobile networks, is now of major concern in respect of their potential adverse impact upon the environment and their escalating operating energy costs. The recent phenomenal growth of data services in cellular mobile networks has exacerbated the energy consumption issue and is forcing researchers to address how to design future wireless networks that take into account energy consumption constraints. One fundamental approach to reduce energy consumption of wireless networks is to adopt new radio access architectures and radio techniques. The Mobile VCE (MVCE) Green Radio project, established in 2009, is considering such new architectural and technical approaches. This paper reports highlights the key research issues pursued in the MVCE Green Radio project.

Product cipher negotiation with on-line evaluation for private communication over computer networks

A method is proposed to offer privacy in computer communications, using symmetric product block ciphers. The security protocol involved a cipher negotiation stage, in which two communicating parties select privately a cipher from a public cipher space. The cipher negotiation process includes an on-line cipher evaluation stage, in which the cryptographic strength of the proposed cipher is estimated. The cryptographic strength of the ciphers is measured by confusion and diffusion. A method is proposed to describe quantitatively these two properties. For the calculation of confusion and diffusion a number of parameters are defined, such as the confusion and diffusion matrices and the marginal diffusion. These parameters involve computationally intensive calculations that are performed off-line, before any communication takes place. Once they are calculated, they are used to obtain estimation equations, which are used for on-line, fast evaluation of the confusion and diffusion of the negotiated cipher. A technique proposed in this thesis describes how to calculate the parameters and how to use the results for fast estimation of confusion and diffusion for any cipher instance within the defined cipher space.

Feed-forward neural networks and topographic mappings for exploratory data analysis

A recent novel approach to the visualisation and analysis of datasets, and one which is particularly applicable to those of a high dimension, is discussed in the context of real applications. A feed-forward neural network is utilised to effect a topographic, structure-preserving, dimension-reducing transformation of the data, with an additional facility to incorporate different degrees of associated subjective information. The properties of this transformation are illustrated on synthetic and real datasets, including the 1992 UK Research Assessment Exercise for funding in higher education. The method is compared and contrasted to established techniques for feature extraction, and related to topographic mappings, the Sammon projection and the statistical field of multidimensional scaling.

CDMA multiuser detection, neural networks, and statistical mechanics

A novel approach, based on statistical mechanics, to analyze typical performance of optimum code-division multiple-access (CDMA) multiuser detectors is reviewed. A `black-box' view ot the basic CDMA channel is introduced, based on which the CDMA multiuser detection problem is regarded as a `learning-from-examples' problem of the `binary linear perceptron' in the neural network literature. Adopting Bayes framework, analysis of the performance of the optimum CDMA multiuser detectors is reduced to evaluation of the average of the cumulant generating function of a relevant posterior distribution. The evaluation of the average cumulant generating function is done, based on formal analogy with a similar calculation appearing in the spin glass theory in statistical mechanics, by making use of the replica method, a method developed in the spin glass theory.

Selection and application of risk management tools and techniques for build-operate-transfer projects

Construction projects are risky. However, the characteristics of the risk highly depend on the type of procurement being adopted for managing the project. A build-operate-transfer (BOT) project is recognized as one of the most risky project schemes. There are instances of project failure where a BOT scheme was employed. Ineffective rts are increasingly being managed using various risk management tools and techniques. However, application of those tools depends on the nature of the project, organization's policy, project management strategy, risk attitude of the project team members, and availability of the resources. Understanding of the contents and contexts of BOT projects, together with a thorough understanding of risk management tools and techniques, helps select processes of risk management for effective project implementation in a BOT scheme. This paper studies application of risk management tools and techniques in BOT projects through reviews of relevant literatures and develops a model for selecting risk management process for BOT projects. The application to BOT projects is considered from the viewpoints of the major project participants. Discussion is also made with regard to political risks. This study would contribute to the establishment of a framework for systematic risk management in BOT projects.

Human-computer interaction and innovation in handheld, mobile and wearable technologies

Handheld and mobile technologies have witnessed significant advances in functionality, leading to their widespread use as both business and social networking tools. Human-Computer Interaction and Innovation in Handheld, Mobile and Wearable Technologies reviews concepts relating to the design, development, evaluation, and application of mobile technologies. Studies on mobile user interfaces, mobile learning, and mobile commerce contribute to the growing body of knowledge on this expanding discipline.

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses

We show theoretically and experimentally a mechanismbehind the emergence of wide or bimodal protein distributions in biochemical networks with nonlinear input-output characteristics (the dose-response curve) and variability in protein abundance. Large cell-to-cell variation in the nonlinear dose-response characteristics can be beneficial to facilitate two distinct groups of response levels as opposed to a graded response. Under the circumstances that we quantify mathematically, the two distinct responses can coexist within a cellular population, leading to the emergence of a bimodal protein distribution. Using flow cytometry, we demonstrate the appearance of wide distributions in the hypoxia-inducible factor-mediated response network in HCT116 cells. With help of our theoretical framework, we perform a novel calculation of the magnitude of cell-to-cell heterogeneity in the dose-response obtained experimentally. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Special issue on intelligent wireless sensor networks and applications

Editorial

Understanding inter-firm networks and types of innovation in SMEs:a social network perspective

Innovation is one of the key drivers for gaining competitive advantages in any firms. Understanding knowledge transfer through inter-firm networks and its effects on types of innovation in SMEs is very important in improving SMEs innovation. This study examines relationships between characteristics of inter-firm knowledge transfer networks and types of innovation in SMEs. To achieve this, social network perspective is adopted to understand inter-firm knowledge transfer networks and its impact on innovation by investigating how and to what extend ego network characteristics are affecting types of innovation. Therefore, managers can develop the firms'network according to their strategies and requirements. First, a conceptual model and research hypotheses are proposed to establish the possible relationship between network properties and types of innovation. Three aspects of ego network are identified and adopted for hypotheses development: 1) structural properties which address the potential for resources and the context for the flow of resources, 2) relational properties which reflect the quality of resource flows, and 3) nodal properties which are about quality and variety of resources and capabilities of the ego partners. A questionnaire has been designed based on the hypotheses. Second, semistructured interviews with managers of five SMEs have been carried out, and a thematic qualitative analysis of these interviews has been performed. The interviews helped to revise the questionnaire and provided preliminary evidence to support the hypotheses. Insights from the preliminary investigation also helped to develop research plan for the next stage of this research.

All optical networking beyond 10 Gbits/s OTDM networks based on electro-optic modulators and fibre ring lasers

This thesis examines options for high capacity all optical networks. Specifically optical time division multiplexed (OTDM) networks based on electro-optic modulators are investigated experimentally, whilst comparisons with alternative approaches are carried out. It is intended that the thesis will form the basis of comparison between optical time division multiplexed networks and the more mature approach of wavelength division multiplexed networks. Following an introduction to optical networking concepts, the required component technologies are discussed. In particular various optical pulse sources are described with the demanding restrictions of optical multiplexing in mind. This is followed by a discussion of the construction of multiplexers and demultiplexers, including favoured techniques for high speed clock recovery. Theoretical treatments of the performance of Mach Zehnder and electroabsorption modulators support the design criteria that are established for the construction of simple optical time division multiplexed systems. Having established appropriate end terminals for an optical network, the thesis examines transmission issues associated with high speed RZ data signals. Propagation of RZ signals over both installed (standard fibre) and newly commissioned fibre routes are considered in turn. In the case of standard fibre systems, the use of dispersion compensation is summarised, and the application of mid span spectral inversion experimentally investigated. For green field sites, soliton like propagation of high speed data signals is demonstrated. In this case the particular restrictions of high speed soliton systems are discussed and experimentally investigated, namely the increasing impact of timing jitter and the downward pressure on repeater spacings due to the constraint of the average soliton model. These issues are each addressed through investigations of active soliton control for OTDM systems and through investigations of novel fibre types respectively. Finally the particularly remarkable networking potential of optical time division multiplexed systems is established, and infinite node cascadability using soliton control is demonstrated. A final comparison of the various technologies for optical multiplexing is presented in the conclusions, where the relative merits of the technologies for optical networking emerges as the key differentiator between technologies.

The interplay between microscopic and mesoscopic structures in complex networks

Understanding a complex network's structure holds the key to understanding its function. The physics community has contributed a multitude of methods and analyses to this cross-disciplinary endeavor. Structural features exist on both the microscopic level, resulting from differences between single node properties, and the mesoscopic level resulting from properties shared by groups of nodes. Disentangling the determinants of network structure on these different scales has remained a major, and so far unsolved, challenge. Here we show how multiscale generative probabilistic exponential random graph models combined with efficient, distributive message-passing inference techniques can be used to achieve this separation of scales, leading to improved detection accuracy of latent classes as demonstrated on benchmark problems. It sheds new light on the statistical significance of motif-distributions in neural networks and improves the link-prediction accuracy as exemplified for gene-disease associations in the highly consequential Online Mendelian Inheritance in Man database. © 2011 Reichardt et al.