Complex network theoretical analysis on information dissemination over vehicular networks

How to enhance the communication efficiency and quality on vehicular networks is one critical important issue. While with the larger and larger scale of vehicular networks in dense cities, the real-world datasets show that the vehicular networks essentially belong to the complex network model. Meanwhile, the extensive research on complex networks has shown that the complex network theory can both provide an accurate network illustration model and further make great contributions to the network design, optimization and management. In this paper, we start with analyzing characteristics of a taxi GPS dataset and then establishing the vehicular-to-infrastructure, vehicle-to-vehicle and the hybrid communication model, respectively. Moreover, we propose a clustering algorithm for station selection, a traffic allocation optimization model and an information source selection model based on the communication performances and complex network theory.

Identifying influential nodes in complex networks for network immunization

Identifying influential nodes is of theoretical significance in network immunization which is one of important methods to prevent virus propagation through protecting the influential nodes in a network. Lots of methods have been proposed to find these influential nodes based on the topological characteristics of a network (e.g., degree, betweenness or K-shell). Whereas due to the diversity of network topologies, these methods are not always effective in identifying influential nodes in any benchmark networks. We combine the advantages of existing methods based on attribute ranking and propose a universal ranking method, namely MAF (Multiple Attribute Fusion), to identify influential nodes from a complex network. We compare the efficiency of our proposed method with existing immunization strategies in different types of networks. Simulation results in the interactive email model show that the immunized nodes selected by MAF can restrain virus propagation effectively.

Quantitation of ascorbic acid in Arabidopsis thaliana reveals distinct differences between organs and growth phases

Optimal plant growth is the result of the interaction of a complex network of plant hormones and environmental signals. Ascorbic acid (AsA) is a crucial antioxidant in plants and is involved in the regulation of cell division, cell expansion, photosynthesis and hormone biosynthesis. Quantitative analysis of AsA in Arabidopsis thaliana organs was conducted using HPLC with d -isoascorbic acid (Iso-AsA) as an internal standard. Analysis revealed Àuctuations in the levels of AsA in different organs and growth phases when plants were grown under standard conditions. AsA concentrations increased in leaves in direct proportion to leaf size and age. Young siliques (seed set stage) and Àowering buds (open and unopened) showed the highest levels of AsA. A relationship was found between the level of AsA and indole acetic acid (IAA) in leaves, stems, Àowers, and siliques and the highest level of IAA and AsAwere found in the Àowers. In contrast, the lowest level of the plant hormone, salicylic acid, was found in the Àowers and the highest quantity measured in the leaves. Consequently, AsA has been found to be a multifunctional molecule that is involved as a key regulator of plant growth and development.

Enabling successful web-based information technology support for enterprise customers: a service provider perspective of stakeholder-based issues

An understanding by support organisations of the key factors enabling successful enterprise after-sales customer support provision when using Web-based Selfservice Systems (WSSs) is essential to making  improvements in such systems. This paper reports key stakeholder-oriented findings from an interpretive study of critical success factors (CSFs) for the transfer of after-sales support-oriented knowledge from an information technology (IT) service provider to enterprise customers when a WSS is used. The findings suggest that researchers and practitioners should consider WSSs within a complex network of service providers, business partners and customer firms. The paper also clearly points to a need for support organisations to engage in greater collaboration and integration of WSSs with enterprise customers and business partners.

Web-based self-service systems for managed IT support: service provider perspectives of stakeholder-based issues

This chapter explores the provision of after-sales information technology (IT) support services using Web-based self-service systems (WSSs) in a business-to-business (B2B) context. A recent study conducted at six large multi-national IT support organisations revealed a number of critical success factors (CSFs) and stakeholder-based issues. To better identify and understand these important enablers and barriers, we explain how WSSs should be considered within a complex network of service providers, business partners and customer firms. The CSFs and stakeholder-based issues are discussed. The chapter highlights that for more successful service provision using WSSs, IT service providers should collaborate more effectively with enterprise customers and business partners and should better integrate their WSSs.

Mapping Co2 emission from commuting in regional Australia : greater Geelong case study

Commuting to work is one of the most important and regular routines of urban transportation. From a geographic perspective, the length of people's commute is influenced, to some degree, by the spatial separation of their home and workplace and the transport infrastructure. The rise of car ownership in Australia has been accompanied by a considerable decrease of public transport use. Increased personal mobility has fuelled the trend of decentralised housing development, mostly without a clear planning for local employment, or alternative means of transportation. As a result, the urban patterns of regional Australia is formed by a complex network of a multitude of small towns, scattered in relatively large areas, which are totally dependent and polarized by few medium and large cities. Such hierarchical and dispersed geographical structure implies significant carbon dioxide emissions from transportation. Transport sector accounts for 14% of Australia's net greenhouse gas emissions, and without further policy action, they are projected to continue to increase. The aim of this paper is to demonstrate the importance of incorporating urban climate understanding and knowledge into urban planning processes in order to develop cities that are more sustainable. A GIS-based gravity model is employed to examine the travel patterns related to hierarchical and geographical urban region networks, and the derived total carbon emissions, using the Greater Geelong region as a case study. The new challenges presented by climate change bring with them opportunities. In order to fully reach the very challenging targets of carbon reduction in Australia an integrated and strategic vision for urban and regional planning is necessary.

Mining mechanism of top-k influential nodes based on voting algorithm in mobile social networks

In recent years, evaluating the influence of nodes and finding top-k influential nodes in social networks, has drawn a wide attention and has become a hot-pot research issue. Considering the characteristics of social networks, we present a novel mechanism to mine the top-k influential nodes in mobile social networks. The proposed mechanism is based on the behaviors analysis of SMS/MMS (simple messaging service / multimedia messaging service) communication between mobile users. We introduce the complex network theory to build a social relation graph, which is used to reveal the relationship among people's social contacts and messages sending. Moreover, intimacy degree is also introduced to characterize social frequency among nodes. Election mechanism is hired to find the most influential node, and then a heap sorting algorithm is used to sort the voting results to find the k most influential nodes. The experimental results show that the mechanism can finds out the most influential top-k nodes efficiently and effectively. © 2013 IEEE.

JLMC: A clustering method based on Jordan-Form of Laplacian-Matrix

Among the current clustering algorithms of complex networks, Laplacian-based spectral clustering algorithms have the advantage of rigorous mathematical basis and high accuracy. However, their applications are limited due to their dependence on prior knowledge, such as the number of clusters. For most of application scenarios, it is hard to obtain the number of clusters beforehand. To address this problem, we propose a novel clustering algorithm - Jordan-Form of Laplacian-Matrix based Clustering algorithm (JLMC). In JLMC, we propose a model to calculate the number (n) of clusters in a complex network based on the Jordan-Form of its corresponding Laplacian matrix. JLMC clusters the network into n clusters by using our proposed modularity density function (P function). We conduct extensive experiments over real and synthetic data, and the experimental results reveal that JLMC can accurately obtain the number of clusters in a complex network, and outperforms Fast-Newman algorithm and Girvan-Newman algorithm in terms of clustering accuracy and time complexity.

Agent-based smart grid protection and security

The vision of a smart grid is to provide a modern, resilient, and secure electric power grid as it boasts up with a highly reliable and efficient environment through effective use of its information and communication technology (ICT). Generally, the control and operation of a smart grid which integrate the distributed energy resources (DERs) such as, wind power, solar power, energy storage, etc., largely depends on a complex network of computers, softwares, and communication infrastructure superimposed on its physical grid architecture facilitated with the deployment of intelligent decision support system applications. In recent years, multi-agent system (MAS) has been well investigated for wide area power system applications and specially gained a significant attention in smart grid protection and security due to its distributed characteristics. In this chapter, a MAS framework for smart grid protection relay coordination is proposed, which consists of a number of intelligent autonomous agents each of which are embedded with the protection relays. Each agent has its own thread of control that provides it with a capability to operate the circuit breakers (CBs) using the critical clearing time (CCT) information as well as communicate with each other through high speed communication network. Besides physical failure, since smart grid highly depends on communication infrastructure, it is vulnerable to several cyber threats on its information and communication channel. An attacker who has knowledge about a certain smart grid communication framework can easily compromise its appliances and components by corrupting the information which may destabilize a system results a widespread blackout. To mitigate such risk of cyber attacks, a few innovative counter measuring techniques are discussed in this chapter.

Investigating the efficacy of an intelligent operation planning and support tool for acute healthcare contexts

Nurses are the largest group of healthcare professionals in hospitals providing 24-hour care to patients. Hence, nurses are pivotal in coordinating and communicating patient care information in the complex network of healthcare professionals, services and other care processes. Yet, despite nurses' central role in health care delivery, intelligent systems have historically rarely been designed around nurses' operational needs. This could explain the poor integration of technologies into nursing work processes and consequent rejection by nursing professionals. The complex nature of acute care delivery in hospitals and the frequently interrupted patterns of nursing work suggest that nurses require flexible intelligent systems that can support and adapt to their variable workflow patterns. This study is designed to explore nurses' initial reactions to a new intelligent operational planning and support tool (IOPST) for acute healthcare. The following reports on the first stage of a longitudinal project to use an innovative approach involving nurses in the development of the IOPST; from conceptualization to implementation.

The acceptance of nursing information systems: an analysis using UTAUT

Nurses are the largest group of health-care professionals in hospitals providing 24-h care to patients. Hence, nurses are pivotal in coordinating and communicating patient care information in the complex network of health-care professionals, services, and other care processes. Further, surveillance and timely interventions by nurses impact quality of care, reduce errors, and decrease health-care costs. Information communication technologies (ICTs) provide the capabilities to support many aspects of nursing care. However, within the context of acute nursing care, there is a lack of integrated technology solutions to support the complex interactions associated with nursing activities and thereby the delivery of high-quality and safe care. Generally, to date, the literature reports low levels of acceptance of ICT solutions by nurses. To address this, the following discussion serves to examine nurses’ acceptance of an integrated point-of-care solution for acute nursing contexts. The ICT was specifically designed to be sensitive to nurses’ needs with the expectation that this will lead to high levels of user acceptance. An evaluation of the acceptability of the proposed solution is presented using unified theory of acceptance and use of technology (UTAUT). Through the UTAUT lens, initial reactions of the participating nurses were examined. The findings provided us with feedback to redesign the solution to better fit with the dynamics and complexity of nursing care. The study has implications for theory, including using UTAUT in health-care contexts, and for practice, including recommendations for the design and development of ICT solutions suitable for nursing contexts.

On the effect of path loss rates on the optimal receiver position in sensor networks

In this paper we examine the problem of finding an optimal position for a receiver node in a single-hop sensor network. The basic idea is to minimize the network energy consumption according to a particular network cost function. Our contribution is to simply show the effect of signal path loss rates and sensor weighting on the optimal receiver position.

Upgrading arc median shortest path problem for an urban transportation network

In this paper, we propose an algorithm for an upgrading arc median shortest path problem for a transportation network. The problem is to identify a set of nondominated paths that minimizes both upgrading cost and overall travel time of the entire network. These two objectives are realistic for transportation network problems, but of a conflicting and noncompensatory nature. In addition, unlike upgrading cost which is the sum of the arc costs on the path, overall travel time of the entire network cannot be expressed as a sum of arc travel times on the path. The proposed solution approach to the problem is based on heuristic labeling and exhaustive search techniques, in criteria space and solution space, respectively. The first approach labels each node in terms of upgrading cost, and deletes cyclic and infeasible paths in criteria space. The latter calculates the overall travel time of the entire network for each feasible path, deletes dominated paths on the basis of the objective vector and identifies a set of Pareto optimal paths in the solution space. The computational study, using two small-scale transportation networks, has demonstrated that the algorithm proposed herein is able to efficiently identify a set of nondominated median shortest paths, based on two conflicting and noncompensatory objectives.

An optimal transportation routing approach using GIS-based dynamic traffic flows

This paper examines the value of real-time traffic information gathered through Geographic Information Systems for achieving an optimal vehicle routing within a dynamically stochastic transportation network. We present a systematic approach in determining the dynamically varying parameters and implementation attributes that were used for the development of a Web-based transportation routing application integrated with real-time GIS services. We propose and implement an optimal routing algorithm by modifying Dijkstra’s algorithm in order to incorporate stochastically changing traffic flows. We describe the significant features of our Web application in making use of the real-time dynamic traffic flow information from GIS services towards achieving total costs savings and vehicle usage reduction. These features help users and vehicle drivers in improving their service levels and productivity as the Web application enables them to interactively find the optimal path and in identifying destinations effectively.