An improved distributed dynamic channel assignment scheme for dense WLANs

The popularity of wireless local area networks (WLANs) has resulted in their dense deployment in many cities around the world. The increased interference among different WLANs severely degrades the throughput achievable. This problem has been further exacerbated by the limited number of frequency channels available. An improved distributed and dynamic channel assignment scheme that is simple to implement and does not depend on the knowledge of the throughput function is proposed in this work. It also allows each access point (AP) to asynchronously switch to the new best channel. Simulation results show that our proposed scheme converges much faster than similar previously reported work, with a reduction in convergence time and channel switches as much as 77.3% and 52.3% respectively. When it is employed in dynamic environments, the throughput improves by up to 12.7%.

Jpowder: a Java-based program for the display and examination of powder diffraction data

The ability to display and inspect powder diffraction data quickly and efficiently is a central part of the data analysis process. Whilst many computer programs are capable of displaying powder data, their focus is typically on advanced operations such as structure solution or Rietveld refinement. This article describes a lightweight software package, Jpowder, whose focus is fast and convenient visualization and comparison of powder data sets in a variety of formats from computers with network access. Jpowder is written in Java and uses its associated Web Start technology to allow ‘single-click deployment’ from a web page, http://www.jpowder.org. Jpowder is open source, free and available for use by anyone.

Ocean data dissemination: new challenges for data integration

In the decade since OceanObs `99, great advances have been made in the field of ocean data dissemination. The use of Internet technologies has transformed the landscape: users can now find, evaluate and access data rapidly and securely using only a web browser. This paper describes the current state of the art in dissemination methods for ocean data, focussing particularly on ocean observations from in situ and remote sensing platforms. We discuss current efforts being made to improve the consistency of delivered data and to increase the potential for automated integration of diverse datasets. An important recent development is the adoption of open standards from the Geographic Information Systems community; we discuss the current impact of these new technologies and their future potential. We conclude that new approaches will indeed be necessary to exchange data more effectively and forge links between communities, but these approaches must be evaluated critically through practical tests, and existing ocean data exchange technologies must be used to their best advantage. Investment in key technology components, cross-community pilot projects and the enhancement of end-user software tools will be required in order to assess and demonstrate the value of any new technology.

Minimum neighbour and extended Kalman filter estimator: a practical distributed channel assignment scheme for dense wireless local area networks

Dense deployments of wireless local area networks (WLANs) are becoming a norm in many cities around the world. However, increased interference and traffic demands can severely limit the aggregate throughput achievable unless an effective channel assignment scheme is used. In this work, a simple and effective distributed channel assignment (DCA) scheme is proposed. It is shown that in order to maximise throughput, each access point (AP) simply chooses the channel with the minimum number of active neighbour nodes (i.e. nodes associated with neighbouring APs that have packets to send). However, application of such a scheme to practice depends critically on its ability to estimate the number of neighbour nodes in each channel, for which no practical estimator has been proposed before. In view of this, an extended Kalman filter (EKF) estimator and an estimate of the number of nodes by AP are proposed. These not only provide fast and accurate estimates but can also exploit channel switching information of neighbouring APs. Extensive packet level simulation results show that the proposed minimum neighbour and EKF estimator (MINEK) scheme is highly scalable and can provide significant throughput improvement over other channel assignment schemes.

Delay analysis of enhanced relay-enabled distributed coordination function

This paper analyzes the delay performance of Enhanced relay-enabled Distributed Coordination Function (ErDCF) for wireless ad hoc networks under ideal condition and in the presence of transmission errors. Relays are nodes capable of supporting high data rates for other low data rate nodes. In ideal channel ErDCF achieves higher throughput and reduced energy consumption compared to IEEE 802.11 Distributed Coordination Function (DCF). This gain is still maintained in the presence of errors. It is also expected of relays to reduce the delay. However, the impact on the delay behavior of ErDCF under transmission errors is not known. In this work, we have presented the impact of transmission errors on delay. It turns out that under transmission errors of sufficient magnitude to increase dropped packets, packet delay is reduced. This is due to increase in the probability of failure. As a result the packet drop time increases, thus reflecting the throughput degradation.

Distributed water ingress and water potential measurements using fibre optics

We report on a distributed moisture detection scheme which uses a cable design based on waterswellable hydrogel polymers. The cable modulates the loss characteristic of light guided within a multi-mode optical fibre in response to relative water potentials in the surrounding environment. Interrogation of the cable using conventional optical time-domain reflectometry (OTDR) instruments allows water ingress points to be identified and located with a spatial resolution of 50 cm. The system has been tested in a simulated tendon duct grouting experiment as a means of mapping the extent of fill along the duct during the grouting process. Voided regions were detected and identified to within 50 cm. A series of salt solutions has been used to determine the sensor behaviour over a range of water potentials. These experiments predict that measurements of soil moisture content can be made over the range 0 to – 1500 kPa. Preliminary data on soil measurements have shown that the sensor can detect water pressure changes with a resolution of 45 kPa. Applications for the sensor include quality assurance of grouting procedures, verification of waterproofing barriers and soil moisture content determination (for load-bearing calculations).

Generating virtual environments to allow increased access to the built environment

The problems encountered by individuals with disabilities when accessing large public buildings is described and a solution based on the generation of virtual models of the built environment is proposed. These models are superimposed on a control network infrastructure, currently utilised in intelligent building applications such as lighting, heating and access control. The use of control network architectures facilitates the creation of distributed models that closely mirror both the physical and control properties of the environment. The model of the environment is kept local to the installation which allows the virtual representation of a large building to be decomposed into an interconnecting series of smaller models. This paper describes two methods of interacting with the virtual model, firstly a two dimensional aural representation that can be used as the basis of a portable navigational device. Secondly an augmented reality called DAMOCLES that overlays additional information on a user’s normal field of view. The provision of virtual environments offers new possibilities in the man-machine interface so that intuitive access to network based services and control functions can be given to a user.

Negotiating access into firms: obstacles and strategies

Researchers often experience difficulties with the negotiation of access into firms for the purpose of data collection. The question we explore is: What are the main obstacles associated with access negotiation into firms; and what strategies do researchers employ to increase their chances of success? Our research work on the tendering process of contractors took place between 2006 and 2008. We successfully negotiated access into four firms (two each in Ghana and the UK) to observe live examples of tender preparation The techniques we employed in negotiating access were personal contacts, contacting firms through online details and professional institutions, etc. With all of this effort, our average success rate was less than 5 per cent. The main obstacles encountered were firms’ reluctance because of commercial sensitiveness and fear that the data could eventually be divulged to their competitors or end up in the public domain. However, some firms agreed mainly because of the written assurances of confidentiality and anonymity in reporting the study; reputation of the researchers’ academic institution; gatekeepers who spoke to their colleagues on our behalf; academic purpose of the study; and a feedback report which was promised in return for access to the case studies. Although the access through personal contacts is by far the easiest, it is not always possible. Researchers can approach firms as complete strangers, especially in a foreign country, and that could make the firms more likely to assist the research.

Model-based groupware solution for distributed real-time collaborative 4D planning via teamwork

Construction planning plays a fundamental role in construction project management that requires team working among planners from a diverse range of disciplines and in geographically dispersed working situations. Model-based four-dimensional (4D) computer-aided design (CAD) groupware, though considered a possible approach to supporting collaborative planning, is still short of effective collaborative mechanisms for teamwork due to methodological, technological and social challenges. Targeting this problem, this paper proposes a model-based groupware solution to enable a group of multidisciplinary planners to perform real-time collaborative 4D planning across the Internet. In the light of the interactive definition method, and its computer-supported collaborative work (CSCW) design analysis, the paper discusses the realization of interactive collaborative mechanisms from software architecture, application mode, and data exchange protocol. These mechanisms have been integrated into a groupware solution, which was validated by a planning team in a truly geographically dispersed condition. Analysis of the validation results revealed that the proposed solution is feasible for real-time collaborative 4D planning to gain a robust construction plan through collaborative teamwork. The realization of this solution triggers further considerations about its enhancement for wider groupware applications.

Conditioning and preconditioning of the variational data assimilation problem

Numerical weather prediction (NWP) centres use numerical models of the atmospheric flow to forecast future weather states from an estimate of the current state. Variational data assimilation (VAR) is used commonly to determine an optimal state estimate that miminizes the errors between observations of the dynamical system and model predictions of the flow. The rate of convergence of the VAR scheme and the sensitivity of the solution to errors in the data are dependent on the condition number of the Hessian of the variational least-squares objective function. The traditional formulation of VAR is ill-conditioned and hence leads to slow convergence and an inaccurate solution. In practice, operational NWP centres precondition the system via a control variable transform to reduce the condition number of the Hessian. In this paper we investigate the conditioning of VAR for a single, periodic, spatially-distributed state variable. We present theoretical bounds on the condition number of the original and preconditioned Hessians and hence demonstrate the improvement produced by the preconditioning. We also investigate theoretically the effect of observation position and error variance on the preconditioned system and show that the problem becomes more ill-conditioned with increasingly dense and accurate observations. Finally, we confirm the theoretical results in an operational setting by giving experimental results from the Met Office variational system.

Communication mechanisms and middleware for distributed video surveillance

A new generation of advanced surveillance systems is being conceived as a collection of multi-sensor components such as video, audio and mobile robots interacting in a cooperating manner to enhance situation awareness capabilities to assist surveillance personnel. The prominent issues that these systems face are: the improvement of existing intelligent video surveillance systems, the inclusion of wireless networks, the use of low power sensors, the design architecture, the communication between different components, the fusion of data emerging from different type of sensors, the location of personnel (providers and consumers) and the scalability of the system. This paper focuses on the aspects pertaining to real-time distributed architecture and scalability. For example, to meet real-time requirements, these systems need to process data streams in concurrent environments, designed by taking into account scheduling and synchronisation. The paper proposes a framework for the design of visual surveillance systems based on components derived from the principles of Real Time Networks/Data Oriented Requirements Implementation Scheme (RTN/DORIS). It also proposes the implementation of these components using the well-known middleware technology Common Object Request Broker Architecture (CORBA). Results using this architecture for video surveillance are presented through an implemented prototype.

Distributed multimedia quality: the user perspective

Distributed multimedia supports a symbiotic infotainment duality, i.e. the ability to transfer information to the user, yet also provide the user with a level of satisfaction. As multimedia is ultimately produced for the education and / or enjoyment of viewers, the user’s-perspective concerning the presentation quality is surely of equal importance as objective Quality of Service (QoS) technical parameters, to defining distributed multimedia quality. In order to extensively measure the user-perspective of multimedia video quality, we introduce an extended model of distributed multimedia quality that segregates quality into three discrete levels: the network-level, the media-level and content-level, using two distinct quality perspectives: the user-perspective and the technical-perspective. Since experimental questionnaires do not provide continuous monitoring of user attention, eye tracking was used in our study in order to provide a better understanding of the role that the human element plays in the reception, analysis and synthesis of multimedia data. Results showed that video content adaptation, results in disparity in user video eye-paths when: i) no single / obvious point of focus exists; or ii) when the point of attention changes dramatically. Accordingly, appropriate technical- and user-perspective parameter adaptation is implemented, for all quality abstractions of our model, i.e. network-level (via simulated delay and jitter), media-level (via a technical- and user-perspective manipulated region-of-interest attentive display) and content-level (via display-type and video clip-type). Our work has shown that user perception of distributed multimedia quality cannot be achieved by means of purely technical-perspective QoS parameter adaptation.

PDM 2006: Proceedings of the International Workshop on Data Mining

Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.

Random-walk-based characterisation of multiple access interference in a DS/SSMA system

The problem of calculating the probability of error in a DS/SSMA system has been extensively studied for more than two decades. When random sequences are employed some conditioning must be done before the application of the central limit theorem is attempted, leading to a Gaussian distribution. The authors seek to characterise the multiple access interference as a random-walk with a random number of steps, for random and deterministic sequences. Using results from random-walk theory, they model the interference as a K-distributed random variable and use it to calculate the probability of error in the form of a series, for a DS/SSMA system with a coherent correlation receiver and BPSK modulation under Gaussian noise. The asymptotic properties of the proposed distribution agree with other analyses. This is, to the best of the authors' knowledge, the first attempt to propose a non-Gaussian distribution for the interference. The modelling can be extended to consider multipath fading and general modulation