Molecular dynamics simulations of the adsorption and diffusion behavior of pure and mixed alkanes in silicalite

The adsorption and diffusion of mixed hydrocarbon components in silicalite have been studied using molecular dynamic simulation methods. We have investigated the effect of molecular loadings and temperature on the diffusional behavior of both pure and mixed alkane components. For binary mixtures with components of similar sizes, molecular diffusional behavior in the channels was noticed to be reversed as loading is increased. This behavior was noticeably absent for components of different sizes in the mixture. Methane molecules in the methane/propane mixture have the highest diffusion coefficients across the entire loading range. Binary mixtures containing ethane molecules prove more difficult to separate compared to other binary components. In the ternary mixture, however, ethane molecules diffuse much faster at 400 K in the channel with a tendency to separate out quickly from other components. © 2005 Elsevier Inc. All rights reserved.

Agent-based Anomalies Monitoring in Distributed Systems

In this paper an agent-based approach for anomalies monitoring in distributed systems such as computer networks, or Grid systems is proposed. This approach envisages on-line and off-line monitoring in order to analyze users’ activity. On-line monitoring is carried in real time, and is used to predict user actions. Off-line monitoring is done after the user has ended his work, and is based on the analysis of statistical information obtained during user’s work. In both cases neural networks are used in order to predict user actions and to distinguish normal and anomalous user behavior.

The Living Economy

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

An epistemic event -based correlation scheme for pervasive network management

Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

Analysis and comparison of network performance with different network parameters

The purpose of this study was to analyze the network performance by observing the effect of varying network size and data link rate on one of the most commonly found network configurations. Computer networks have been growing explosively. Networking is used in every aspect of business, including advertising, production, shipping, planning, billing, and accounting. Communication takes place through networks that form the basis of transfer of information. The number and type of components may vary from network to network depending on several factors such as requirement and actual physical placement of the networks. There is no fixed size of the networks and they can be very small consisting of say five to six nodes or very large consisting of over two thousand nodes. The varying network sizes make it very important to study the network performance so as to be able to predict the functioning and the suitability of the network. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected. The findings demonstrated that the network performance parameters such as global delay, load, router processor utilization, router processor delay, etc. are affected significantly due to the increase in the size of the network and that there exists a correlation between the various parameters and the size of the network. These variations are not only dependent on the magnitude of the change in the actual physical area of the network but also on the data link rate used to connect the various components of the network.

Infoestrutura: um sistema em nuvem para prover contexto como serviço no cenário de internet das coisas integrado a ambientes veiculares

Through numerous technological advances in recent years along with the popularization of computer devices, the company is moving towards a paradigm “always connected”. Computer networks are everywhere and the advent of IPv6 paves the way for the explosion of the Internet of Things. This concept enables the sharing of data between computing machines and objects of day-to-day. One of the areas placed under Internet of Things are the Vehicular Networks. However, the information generated individually for a vehicle has no large amount and does not contribute to an improvement in transit, once information has been isolated. This proposal presents the Infostructure, a system that has to facilitate the efforts and reduce costs for development of applications context-aware to high-level semantic for the scenario of Internet of Things, which allows you to manage, store and combine the data in order to generate broader context. To this end we present a reference architecture, which aims to show the major components of the Infostructure. Soon after a prototype is presented which is used to validate our work reaches the level of contextualization desired high level semantic as well as a performance evaluation, which aims to evaluate the behavior of the subsystem responsible for managing contextual information on a large amount of data. After statistical analysis is performed with the results obtained in the evaluation. Finally, the conclusions of the work and some problems such as no assurance as to the integrity of the sensory data coming Infostructure, and future work that takes into account the implementation of other modules so that we can conduct tests in real environments are presented.

Extensões na arquitetura SDN para o provisionamento de QoS através do monitoramento e uso de múltiplos caminhos

The substantial increase in the number of applications offered through the computer networks, as well as in the volume of traffic forwarded through the network, have hampered to assure adequate service level to users. The Quality of Service (QoS) offer, honoring specified parameters in Service Level Agreements (SLA), established between the service providers and their clients, composes a traditional and extensive computer networks’ research area. Several schemes proposals for the provision of QoS were presented in the last three decades, but the acting scope of these proposals is always limited due to some factors, including the limited development of the network hardware and software, generally belonging to a single manufacturer. The advent of Software Defined Networking (SDN), along with the maturation of its main materialization, the OpenFlow protocol, allowed the decoupling between network hardware and software, through an architecture which provides a control plane and a data plane. This eases the computer networks scenario, allowing that new abstractions are applied in the hardware composing the data plane, through the development of new software pieces which are executed in the control plane. This dissertation investigates the QoS offer through the use and extension of the SDN architecture. Based on the proposal of two new modules, one to perform the data plane monitoring, SDNMon, and the second, MP-ROUTING, developed to determine the use of multiple paths in the forwarding of data referring to a flow, we demonstrated in this work that some QoS metrics specified in the SLAs, such as bandwidth, can be honored. Both modules were implemented and evaluated through a prototype. The evaluation results referring to several aspects of both proposed modules are presented in this dissertation, showing the obtained accuracy of the monitoring module SDNMon and the QoS gains due to the utilization of multiple paths defined by the MP-Routing, when forwarding data flow through the SDN.

A theory-informed approach to developing visually mediated interventions to change behaviour using an asthma and physical activity intervention exemplar

Funding for this study was received from the Chief Scientist Office for Scotland. We would like to thank Asthma UK and Asthma UK Scotland for facilitating the advertisement of the study pilot and consultative user group. Thanks to Dr Mark Grindle for his helpful discussions concerning narrative. Thanks also to Mr Mark Haldane who designed the characters, backgrounds, and user interface used within the 3D computer animation. Particular thanks to the participants of the consultative user group for their enthusiasm, comments, and suggestions at all stages of the intervention design.

[N]pT ensemble and finite-size-scaling study of the critical isostructural transition in the generalized exponential model of index 4.

First-order transitions of system where both lattice site occupancy and lattice spacing fluctuate, such as cluster crystals, cannot be efficiently studied by traditional simulation methods, which necessarily fix one of these two degrees of freedom. The difficulty, however, can be surmounted by the generalized [N]pT ensemble [J. Chem. Phys. 136, 214106 (2012)]. Here we show that histogram reweighting and the [N]pT ensemble can be used to study an isostructural transition between cluster crystals of different occupancy in the generalized exponential model of index 4 (GEM-4). Extending this scheme to finite-size scaling studies also allows us to accurately determine the critical point parameters and to verify that it belongs to the Ising universality class.

An Epistemic Event-based Correlation Scheme for Pervasive Network Management

Computer networks produce tremendous amounts of event-based data that can be collected and managed to support an increasing number of new classes of pervasive applications. Examples of such applications are network monitoring and crisis management. Although the problem of distributed event-based management has been addressed in the non-pervasive settings such as the Internet, the domain of pervasive networks has its own characteristics that make these results non-applicable. Many of these applications are based on time-series data that possess the form of time-ordered series of events. Such applications also embody the need to handle large volumes of unexpected events, often modified on-the-fly, containing conflicting information, and dealing with rapidly changing contexts while producing results with low-latency. Correlating events across contextual dimensions holds the key to expanding the capabilities and improving the performance of these applications. This dissertation addresses this critical challenge. It establishes an effective scheme for complex-event semantic correlation. The scheme examines epistemic uncertainty in computer networks by fusing event synchronization concepts with belief theory. Because of the distributed nature of the event detection, time-delays are considered. Events are no longer instantaneous, but duration is associated with them. Existing algorithms for synchronizing time are split into two classes, one of which is asserted to provide a faster means for converging time and hence better suited for pervasive network management. Besides the temporal dimension, the scheme considers imprecision and uncertainty when an event is detected. A belief value is therefore associated with the semantics and the detection of composite events. This belief value is generated by a consensus among participating entities in a computer network. The scheme taps into in-network processing capabilities of pervasive computer networks and can withstand missing or conflicting information gathered from multiple participating entities. Thus, this dissertation advances knowledge in the field of network management by facilitating the full utilization of characteristics offered by pervasive, distributed and wireless technologies in contemporary and future computer networks.

Distributed parallelization of greedy Mobile Network Optimization algorithms

The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

A green perspective on Structured parallel programming

Structured parallel programming, and in particular programming models using the algorithmic skeleton or parallel design pattern concepts, are increasingly considered to be the only viable means of supporting effective development of scalable and efficient parallel programs. Structured parallel programming models have been assessed in a number of works in the context of performance. In this paper we consider how the use of structured parallel programming models allows knowledge of the parallel patterns present to be harnessed to address both performance and energy consumption. We consider different features of structured parallel programming that may be leveraged to impact the performance/energy trade-off and we discuss a preliminary set of experiments validating our claims.

The Loop-of-Stencil-Reduce Paradigm

In this paper we advocate the Loop-of-stencil-reduce pattern as a way to simplify the parallel programming of heterogeneous platforms (multicore+GPUs). Loop-of-Stencil-reduce is general enough to subsume map, reduce, map-reduce, stencil, stencil-reduce, and, crucially, their usage in a loop. It transparently targets (by using OpenCL) combinations of CPU cores and GPUs, and it makes it possible to simplify the deployment of a single stencil computation kernel on different GPUs. The paper discusses the implementation of Loop-of-stencil-reduce within the FastFlow parallel framework, considering a simple iterative data-parallel application as running example (Game of Life) and a highly effective parallel filter for visual data restoration to assess performance. Thanks to the high-level design of the Loop-of-stencil-reduce, it was possible to run the filter seamlessly on a multicore machine, on multi-GPUs, and on both.

Verfahren zur Durchsatz-maximierenden Lagerordnung auf Grundlage unsicherer Zugriffshäufigkeitsprognosen

Im Zusammenhang mit der Entwicklung einer neuen Betriebsstrategie zur Erzeugung einer Durchsatz-maximierenden Lagerordnung werden neue Herausforderungen des Strategiedesigns in Form von Echtzeitanfoderungen, Korrelationen-abbildende Prognosenwertemodelle und ungewissen Auftragsfolgen thematisiert. Die Effektivität der neuen Betriebsstrategie wird im Rahmen eines Simulationsexperiments getestet.

On Multi- Server Queues With Consultation With Main Server

Queueing Theory is the mathematical study of queues or waiting lines. Queues abound in every day life - in computer networks, in tra c islands, in communication of electro-magnetic signals, in telephone exchange, in bank counters, in super market checkouts, in doctor's clinics, in petrol pumps, in o ces where paper works to be processed and many other places. Originated with the published work of A. K. Erlang in 1909 [16] on congestion in telephone tra c, Queueing Theory has grown tremendously in a century. Its wide range applications includes Operations Research, Computer Science, Telecommunications, Tra c Engineering, Reliability Theory, etc.