Cost Models for Routing and Wavelength Assignment in Wavelength-Division Multiplexing Optical Net

WDM (Wavelength-Division Multiplexing) optiset verkot on tällä hetkellä suosituin tapa isojen määrän tietojen siirtämiseen. Jokaiselle liittymälle määrätään reitin ja aallonpituus joka linkin varten. Tarvittavan reitin ja aallon pituuden löytäminen kutsutaan RWA-ongelmaksi. Tämän työn kuvaa mahdollisia kustannuksen mallein ratkaisuja RWA-ongelmaan. Olemassa on paljon erilaisia optimoinnin tavoitteita. Edellä mainittuja kustannuksen malleja perustuu näillä tavoitteilla. Kustannuksen malleja antavat tehokkaita ratkaisuja ja algoritmeja. The multicommodity malli on käsitelty tässä työssä perusteena RV/A-kustannuksen mallille. Myöskin OB käsitelty heuristisia menetelmiä RWA-ongelman ratkaisuun. Työn loppuosassa käsitellään toteutuksia muutamalle mallille ja erilaisia mahdollisuuksia kustannuksen mallein parantamiseen.

Corporate identity and its efficient and effective communication

Yritysidentiteetistä on monta eri näkemystä ja yleisesti hyväksyttyä määritelmää ei ole olemassa. Monia eri näkemyksiä käsitellään tässä tutkielmassa. Vaikka yritysidentiteettiä ei olekaan helppo mitata, on tätä varten kuitenkin kehitetty useampia metodeja. Identiteetin viestintä vaati strategisia päätöksiä ennen kuin viestintää voidaan tehdä. Viestinnän integrointi on avainasemassa identiteetin viestinnässä. Hyvin hoidettu ja kommunikoitu yritysidentiteetti voi johtaa useisiin hyötyihin organisaatiolle. Kuitenkaan nämä hyödyt eivät näy kovin nopeasti, koska yritysidentiteetin viestintä on pitkän tähtäimen prosessi.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Security and Privacy in a Ubiquitous Information Screen

We expose the ubiquitous interaction between an information screen and its’ viewers mobile devices, highlights the communication vulnerabilities, suggest mitigation strategies and finally implement these strategies to secure the communication. The screen infers information preferences’ of viewers within its vicinity transparently from their mobile devices over Bluetooth. Backend processing then retrieves up-to-date versions of preferred information from content providers. Retrieved content such as sporting news, weather forecasts, advertisements, stock markets and aviation schedules, are systematically displayed on the screen. To maximise users’ benefit, experience and acceptance, the service is provided with no user interaction at the screen and securely upholding preferences privacy and viewers anonymity. Compelled by the personal nature of mobile devices, their contents privacy, preferences confidentiality, and vulnerabilities imposed by screen, the service’s security is fortified. Fortification is predominantly through efficient cryptographic algorithms inspired by elliptic curves cryptosystems, access control and anonymity mechanisms. These mechanisms are demonstrated to attain set objectives within reasonable performance.

A Co-Processor Approach for Efficient Java Execution in Embedded Systems

This thesis deals with a hardware accelerated Java virtual machine, named REALJava. The REALJava virtual machine is targeted for resource constrained embedded systems. The goal is to attain increased computational performance with reduced power consumption. While these objectives are often seen as trade-offs, in this context both of them can be attained simultaneously by using dedicated hardware. The target level of the computational performance of the REALJava virtual machine is initially set to be as fast as the currently available full custom ASIC Java processors. As a secondary goal all of the components of the virtual machine are designed so that the resulting system can be scaled to support multiple co-processor cores. The virtual machine is designed using the hardware/software co-design paradigm. The partitioning between the two domains is flexible, allowing customizations to the resulting system, for instance the floating point support can be omitted from the hardware in order to decrease the size of the co-processor core. The communication between the hardware and the software domains is encapsulated into modules. This allows the REALJava virtual machine to be easily integrated into any system, simply by redesigning the communication modules. Besides the virtual machine and the related co-processor architecture, several performance enhancing techniques are presented. These include techniques related to instruction folding, stack handling, method invocation, constant loading and control in time domain. The REALJava virtual machine is prototyped using three different FPGA platforms. The original pipeline structure is modified to suit the FPGA environment. The performance of the resulting Java virtual machine is evaluated against existing Java solutions in the embedded systems field. The results show that the goals are attained, both in terms of computational performance and power consumption. Especially the computational performance is evaluated thoroughly, and the results show that the REALJava is more than twice as fast as the fastest full custom ASIC Java processor. In addition to standard Java virtual machine benchmarks, several new Java applications are designed to both verify the results and broaden the spectrum of the tests.

The Pursuit of Efficient Copyright Licensing : How Some Rights Reserved Attempts to Solve the Problems of All Rights Reserved

This dissertation analyses the growing pool of copyrighted works, which are offered to the public using Creative Commons licensing. The study consist of analysis of the novel licensing system, the licensors, and the changes of the "all rights reserved" —paradigm of copyright law. Copyright law reserves all rights to the creator until seventy years have passed since her demise. Many claim that this endangers communal interests. Quite often the creators are willing to release some rights. This, however, is very difficult to do and needs help of specialized lawyers. The study finds that the innovative Creative Commons licensing scheme is well suited for low value - high volume licensing. It helps to reduce transaction costs on several le¬vels. However, CC licensing is not a "silver bullet". Privacy, moral rights, the problems of license interpretation and license compatibility with other open licenses and collecting societies remain unsolved. The study consists of seven chapters. The first chapter introduces the research topic and research questions. The second and third chapters inspect the Creative Commons licensing scheme's technical, economic and legal aspects. The fourth and fifth chapters examine the incentives of the licensors who use open licenses and describe certain open business models. The sixth chapter studies the role of collecting societies and whether two institutions, Creative Commons and collecting societies can coexist. The final chapter summarizes the findings. The dissertation contributes to the existing literature in several ways. There is a wide range of prior research on open source licensing. However, there is an urgent need for an extensive study of the Creative Commons licensing and its actual and potential impact on the creative ecosystem.

Bayesian Estimation of Noise

In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.

Development a distributed simulation environment on a cluster of workstations

Simulation has traditionally been used for analyzing the behavior of complex real world problems. Even though only some features of the problems are considered, simulation time tends to become quite high even for common simulation problems. Parallel and distributed simulation is a viable technique for accelerating the simulations. The success of parallel simulation depends heavily on the combination of the simulation application, algorithm and message population in the simulation is sufficient, no additional delay is caused by this environment. In this thesis a conservative, parallel simulation algorithm is applied to the simulation of a cellular network application in a distributed workstation environment. This thesis presents a distributed simulation environment, Diworse, which is based on the use of networked workstations. The distributed environment is considered especially hard for conservative simulation algorithms due to the high cost of communication. In this thesis, however, the distributed environment is shown to be a viable alternative if the amount of communication is kept reasonable. Novel ideas of multiple message simulation and channel reduction enable efficient use of this environment for the simulation of a cellular network application. The distribution of the simulation is based on a modification of the well known Chandy-Misra deadlock avoidance algorithm with null messages. The basic Chandy Misra algorithm is modified by using the null message cancellation and multiple message simulation techniques. The modifications reduce the amount of null messages and the time required for their execution, thus reducing the simulation time required. The null message cancellation technique reduces the processing time of null messages as the arriving null message cancels other non processed null messages. The multiple message simulation forms groups of messages as it simulates several messages before it releases the new created messages. If the message population in the simulation is suffiecient, no additional delay is caused by this operation A new technique for considering the simulation application is also presented. The performance is improved by establishing a neighborhood for the simulation elements. The neighborhood concept is based on a channel reduction technique, where the properties of the application exclusively determine which connections are necessary when a certain accuracy for simulation results is required. Distributed simulation is also analyzed in order to find out the effect of the different elements in the implemented simulation environment. This analysis is performed by using critical path analysis. Critical path analysis allows determination of a lower bound for the simulation time. In this thesis critical times are computed for sequential and parallel traces. The analysis based on sequential traces reveals the parallel properties of the application whereas the analysis based on parallel traces reveals the properties of the environment and the distribution.

A Practical Micro Mechanical Model Based Local Approach Methodology for the Analysis of Ductile Fracture of Welded T-Joints

This thesis concentrates on developing a practical local approach methodology based on micro mechanical models for the analysis of ductile fracture of welded joints. Two major problems involved in the local approach, namely the dilational constitutive relation reflecting the softening behaviour of material, and the failure criterion associated with the constitutive equation, have been studied in detail. Firstly, considerable efforts were made on the numerical integration and computer implementation for the non trivial dilational Gurson Tvergaard model. Considering the weaknesses of the widely used Euler forward integration algorithms, a family of generalized mid point algorithms is proposed for the Gurson Tvergaard model. Correspondingly, based on the decomposition of stresses into hydrostatic and deviatoric parts, an explicit seven parameter expression for the consistent tangent moduli of the algorithms is presented. This explicit formula avoids any matrix inversion during numerical iteration and thus greatly facilitates the computer implementation of the algorithms and increase the efficiency of the code. The accuracy of the proposed algorithms and other conventional algorithms has been assessed in a systematic manner in order to highlight the best algorithm for this study. The accurate and efficient performance of present finite element implementation of the proposed algorithms has been demonstrated by various numerical examples. It has been found that the true mid point algorithm (a = 0.5) is the most accurate one when the deviatoric strain increment is radial to the yield surface and it is very important to use the consistent tangent moduli in the Newton iteration procedure. Secondly, an assessment of the consistency of current local failure criteria for ductile fracture, the critical void growth criterion, the constant critical void volume fraction criterion and Thomason's plastic limit load failure criterion, has been made. Significant differences in the predictions of ductility by the three criteria were found. By assuming the void grows spherically and using the void volume fraction from the Gurson Tvergaard model to calculate the current void matrix geometry, Thomason's failure criterion has been modified and a new failure criterion for the Gurson Tvergaard model is presented. Comparison with Koplik and Needleman's finite element results shows that the new failure criterion is fairly accurate indeed. A novel feature of the new failure criterion is that a mechanism for void coalescence is incorporated into the constitutive model. Hence the material failure is a natural result of the development of macroscopic plastic flow and the microscopic internal necking mechanism. By the new failure criterion, the critical void volume fraction is not a material constant and the initial void volume fraction and/or void nucleation parameters essentially control the material failure. This feature is very desirable and makes the numerical calibration of void nucleation parameters(s) possible and physically sound. Thirdly, a local approach methodology based on the above two major contributions has been built up in ABAQUS via the user material subroutine UMAT and applied to welded T joints. By using the void nucleation parameters calibrated from simple smooth and notched specimens, it was found that the fracture behaviour of the welded T joints can be well predicted using present methodology. This application has shown how the damage parameters of both base material and heat affected zone (HAZ) material can be obtained in a step by step manner and how useful and capable the local approach methodology is in the analysis of fracture behaviour and crack development as well as structural integrity assessment of practical problems where non homogeneous materials are involved. Finally, a procedure for the possible engineering application of the present methodology is suggested and discussed.

On Fault Tolerance Methods for Networks-on-Chip

Technology scaling has proceeded into dimensions in which the reliability of manufactured devices is becoming endangered. The reliability decrease is a consequence of physical limitations, relative increase of variations, and decreasing noise margins, among others. A promising solution for bringing the reliability of circuits back to a desired level is the use of design methods which introduce tolerance against possible faults in an integrated circuit. This thesis studies and presents fault tolerance methods for network-onchip (NoC) which is a design paradigm targeted for very large systems-onchip. In a NoC resources, such as processors and memories, are connected to a communication network; comparable to the Internet. Fault tolerance in such a system can be achieved at many abstraction levels. The thesis studies the origin of faults in modern technologies and explains the classification to transient, intermittent and permanent faults. A survey of fault tolerance methods is presented to demonstrate the diversity of available methods. Networks-on-chip are approached by exploring their main design choices: the selection of a topology, routing protocol, and flow control method. Fault tolerance methods for NoCs are studied at different layers of the OSI reference model. The data link layer provides a reliable communication link over a physical channel. Error control coding is an efficient fault tolerance method especially against transient faults at this abstraction level. Error control coding methods suitable for on-chip communication are studied and their implementations presented. Error control coding loses its effectiveness in the presence of intermittent and permanent faults. Therefore, other solutions against them are presented. The introduction of spare wires and split transmissions are shown to provide good tolerance against intermittent and permanent errors and their combination to error control coding is illustrated. At the network layer positioned above the data link layer, fault tolerance can be achieved with the design of fault tolerant network topologies and routing algorithms. Both of these approaches are presented in the thesis together with realizations in the both categories. The thesis concludes that an optimal fault tolerance solution contains carefully co-designed elements from different abstraction levels

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

MCMC Analysis Of Classical Time Series Algorithms

Identification of order of an Autoregressive Moving Average Model (ARMA) by the usual graphical method is subjective. Hence, there is a need of developing a technique to identify the order without employing the graphical investigation of series autocorrelations. To avoid subjectivity, this thesis focuses on determining the order of the Autoregressive Moving Average Model using Reversible Jump Markov Chain Monte Carlo (RJMCMC). The RJMCMC selects the model from a set of the models suggested by better fitting, standard deviation errors and the frequency of accepted data. Together with deep analysis of the classical Box-Jenkins modeling methodology the integration with MCMC algorithms has been focused through parameter estimation and model fitting of ARMA models. This helps to verify how well the MCMC algorithms can treat the ARMA models, by comparing the results with graphical method. It has been seen that the MCMC produced better results than the classical time series approach.

Numerics of Spacecraft Dynamics

Whenever a spacecraft is launched it is essential that the algorithms in the on-board software systems and at ground control are efficient and reliable over extended periods of time. Geometric numerical integrators, and in particular variational integrators, have both these characteristics. In "Numerics of Spacecraft Dynamics" new numerical integrators are presented and analysed in depth. These algorithms have been designed specifically for the dynamics of spacecraft and artificial satellites in Earth orbits. Full analytical solutions to a class of integrable deformations of the two-body problem in classical mechanics are derived, and a systematic method to compute variational integrators to arbitrary order with a computer algebra system is introduced.