Temporal correlations of local network losses

We introduce a continuum model describing data losses in a single node of a packet-switched network (like the Internet) which preserves the discrete nature of the data loss process. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that such a model exhibits strong fluctuations in the loss rate at the critical point and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process. The continuum model allows for rather general incoming data packet distributions and can be naturally generalized to consider the buffer server idleness statistics.

Finding structures in information networks using the affinity network

This thesis proposes a novel graphical model for inference called the Affinity Network,which displays the closeness between pairs of variables and is an alternative to Bayesian Networks and Dependency Networks. The Affinity Network shares some similarities with Bayesian Networks and Dependency Networks but avoids their heuristic and stochastic graph construction algorithms by using a message passing scheme. A comparison with the above two instances of graphical models is given for sparse discrete and continuous medical data and data taken from the UCI machine learning repository. The experimental study reveals that the Affinity Network graphs tend to be more accurate on the basis of an exhaustive search with the small datasets. Moreover, the graph construction algorithm is faster than the other two methods with huge datasets. The Affinity Network is also applied to data produced by a synchronised system. A detailed analysis and numerical investigation into this dynamical system is provided and it is shown that the Affinity Network can be used to characterise its emergent behaviour even in the presence of noise.

Network lifetime maximization with cross-layer design in wireless sensor networks

This paper investigates a cross-layer design approach for minimizing energy consumption and maximizing network lifetime (NL) of a multiple-source and single-sink (MSSS) WSN with energy constraints. The optimization problem for MSSS WSN can be formulated as a mixed integer convex optimization problem with the adoption of time division multiple access (TDMA) in medium access control (MAC) layer, and it becomes a convex problem by relaxing the integer constraint on time slots. Impacts of data rate, link access and routing are jointly taken into account in the optimization problem formulation. Both linear and planar network topologies are considered for NL maximization (NLM). With linear MSSS and planar single-source and single-sink (SSSS) topologies, we successfully use Karush-Kuhn-Tucker (KKT) optimality conditions to derive analytical expressions of the optimal NL when all nodes are exhausted simultaneously. The problem for planar MSSS topology is more complicated, and a decomposition and combination (D&C) approach is proposed to compute suboptimal solutions. An analytical expression of the suboptimal NL is derived for a small scale planar network. To deal with larger scale planar network, an iterative algorithm is proposed for the D&C approach. Numerical results show that the upper-bounds of the network lifetime obtained by our proposed optimization models are tight. Important insights into the NL and benefits of cross-layer design for WSN NLM are obtained.

Energy efficient radio access architectures for green radio:large versus small cell size deployment

In this paper new architectural approaches that improve the energy efficiency of a cellular radio access network (RAN) are investigated. The aim of the paper is to characterize both the energy consumption ratio (ECR) and the energy consumption gain (ECG) of a cellular RAN when the cell size is reduced for a given user density and service area. The paper affirms that reducing the cell size reduces the cell ECR as desired while increasing the capacity density but the overall RAN energy consumption remains unchanged. In order to trade the increase in capacity density with RAN energy consumption, without degrading the cell capacity provision, a sleep mode is introduced. In sleep mode, cells without active users are powered-off, thereby saving energy. By combining a sleep mode with a small-cell deployment architecture, the paper shows that the ECG can be increased by the factor n = (R/R) while the cell ECR continues to decrease with decreasing cell size.

Loss fluctuations and temporal correlations in network queues

We consider data losses in a single node of a packet- switched Internet-like network. We employ two distinct models, one with discrete and the other with continuous one-dimensional random walks, representing the state of a queue in a router. Both models have a built-in critical behavior with a sharp transition from exponentially small to finite losses. It turns out that the finite capacity of a buffer and the packet-dropping procedure give rise to specific boundary conditions which lead to strong loss rate fluctuations at the critical point even in the absence of such fluctuations in the data arrival process.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

SMEs in a globalised world:survival and growth strategies on Europe's geographical periphery

This insightful book shows how small and medium enterprises (SMEs) from some of the traditionally less dynamic peripheral economies of the 'old' EU - namely Ireland, Italy, Portugal and Spain - have responded to the twin challenges of globalisation and industrial restructuring. Through a series of unique case studies the contributing authors discuss how these economies, and in particular the SME sector, can be transformed. The book begins by examining the key drivers of the globally competitive SME sector in the EU, before moving on to explore the relationship between multinational enterprises (MNEs), SMEs and industrial development. The authors investigate important policy implications and provide lessons for SME development and growth. With empirical and theoretical contributions on SMEs in both the manufacturing and the services sectors, this essential book will be invaluable for researchers and policymakers in small business economics and management. Postgraduate students of entrepreneurship, business economics, industrial economics and European studies will appreciate this unique set of insights.

Communities and emerging semantics in semantic link network:discovery and learning

The World Wide Web provides plentiful contents for Web-based learning, but its hyperlink-based architecture connects Web resources for browsing freely rather than for effective learning. To support effective learning, an e-learning system should be able to discover and make use of the semantic communities and the emerging semantic relations in a dynamic complex network of learning resources. Previous graph-based community discovery approaches are limited in ability to discover semantic communities. This paper first suggests the Semantic Link Network (SLN), a loosely coupled semantic data model that can semantically link resources and derive out implicit semantic links according to a set of relational reasoning rules. By studying the intrinsic relationship between semantic communities and the semantic space of SLN, approaches to discovering reasoning-constraint, rule-constraint, and classification-constraint semantic communities are proposed. Further, the approaches, principles, and strategies for discovering emerging semantics in dynamic SLNs are studied. The basic laws of the semantic link network motion are revealed for the first time. An e-learning environment incorporating the proposed approaches, principles, and strategies to support effective discovery and learning is suggested.

Internationalization of small and medium sized UK manufacturing enterprises:technology and knowledge transfer perspective

This dissertation examines internationalisation of small and medium sized enterprises. There has been a journey to achieve this. The research has started as an action research as Teaching Company Scheme Associate. This has been done in two research cycles, which investigated factors for successful internationalisation of a small and medium sized UK manufacturing enterprise. This has revealed that successful internationalisation requires good technology and knowledge transfer to the new operations. The action research is followed by a survey that has been conducted within UK manufacturing companies. The data collected was analysed under three models: entry mode selection, role of factory and level of internationalisation. The first two models explain two major aspects of internationalisation decision. The last is showing what makes successful internationalising small and medium sized companies. These models provided several important results. The small and medium sized enterprise internationalisation is harder to achieve because most of these organisations do not have experience in technology and knowledge transfer. The success of internationalisation depends on the success of the transfer. This is achieved through employee ownership of the new knowledge. There are many factors affecting this result such as the network relationships such as trust, control and commitment and cognitive distance between two organisations. The last is a product of the difference between prior knowledge and the required level of knowledge. The entry mode and role of factory are decided through these factors while the level of internationalisation can only be explained by absorptive capacity of the recipient organisation and the technology transfer ability of the host organisation.

Do social capital building strategies influence the financing behavior of Chinese private small and medium-sized enterprises?

Using data from 65,485 Chinese private small and medium-sized enterprises over the period 2000-2006, we examine the extent to which firms can improve access to debt by adopting strategies aimed at building social capital, namely entertaining and gift giving to others in their social network, and obtaining political affiliation. We find that although entertainment and gift-giving expenditure leads to higher levels of total and short-term debt, it does not enable firms to obtain greater long-term debt. In contrast, we demonstrate that obtaining political affiliation allows firms greater access to long-term debt.

When cost-efficient technologies meet politics:a case study of radical wireless network implementation

Cost efficiency has been a dominant perspective in the traditional IT literature. However, in complex technology and business environment, the widely recognized cost efficient assumption of information technology has been increasingly challenged. Drawing from a case study of wireless network implementation situated in a politically sensitive workplace, this paper provided practice insights for IT managers in today’s networked economy. More specifically, stories experienced in the case study illustrated that despite well-calculated cost efficiency of wireless network infrastructure, the radical implementation process in the case organization encountered enormous challenges and opposition due to the fact that administrators failed to consider various stakeholders’ positions and interests. Eventually, the implementation objectives and outcome were considerably undermined. Implications from this empirical case research reemphasized the significance of understanding political forces situated in any business environment where different stakeholders hold conflicting interests. Lessons learned from the case story further encouraged IT managers and policy makers to better strategize emerging information technology in general and wireless networks in particular as the whole global society and business environment are increasingly facing an emerging wireless world.

Small business owners’ success criteria, a values approach to personal differences

This study of 150 Dutch small business owners, identified through business/ network directories, investigated relationships between owners’ understanding of success and their personal values. Business owners ranked 10 success criteria. Per- sonal satisfaction, profitability, and satisfied stakeholders ranked highest. Multidi- mensional scaling techniques revealed two dimensions underlying the rank order of success criteria: person-oriented (personal satisfaction versus business growth) and business-oriented (profitability versus contributing back to society). Furthermore, business growth, profitability, and innovativeness were guided by self-enhancing value orientations (power and achievement). Softer success criteria, such as having satisfied stakeholders and a good work–life balance, were guided by self-transcendent value orientations (benevolence and universalism).

Random walks in local dynamics of network losses

We suggest a model for data losses in a single node (memory buffer) of a packet-switched network (like the Internet) which reduces to one-dimensional discrete random walks with unusual boundary conditions. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that for a finite-capacity buffer at the critical point the loss rate exhibits strong fluctuations and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process.

Exploring chain, network and cluster collaborative practices:implications for SMEs

Collaboration among enterprises has been rendered as one of the most important issues in the business agenda, either as a result of the globalisation and deregulation of markets or as a result of the Information and Communication Technology (ICT) revolution. Both factors have created a business reality where success in the collaboration practices followed, may result in improvements in the competitive position of enterprises. This paper starts from the basic business activity of the individual enterprise, looks into the chain, network and cluster collaborative practices and analyses their characteristics and the implications for Small-Medium Enterprises (SMEs). In addition, it provides insights regarding the opportunities, benefits, requirements and risks related to each collaborative practice. This paper finally argues that different collaboration practices are required, as enterprises and the industrial sectors where they operate, present distinctive characteristics.