In the current era of computing, the emergence of middle-ware software has resulted into a high level of software abstraction which has contributed to the diffusion of distributed computing. Distributed frameworks are systems comprised of many computing resources that are coupled together to perform one or more tasks. In a scientific grid-like environment, there are many different applications which require vast computing resources for simulation, execution, or analysis. Some of the applications require faster results, while other rely on more resources for execution. A configurable job submission system helps in distributing the tasks among the resources depending on their preference, priority and usage in a distributed environment. We implemented a job submission system using JavaSpace which can be used for simulating jobs according to their priority. Two different types of brokers are used to monitor the JavaSpace. These brokers can either be used to compute results for tasks that require faster results using binaries installed on a stand-alone system or they can be used to submit the task to a BOINC system for computation. The flexibility to submit tasks as per their priority would help users to get faster results. Upon completion of the tasks, the brokers updates the jobs and transfers the results for further processing thus completing a cycle of retrieving a job, computing the data and transferring the results back to the user. The generic nature of the framework makes it very simple to add new services which can perform a variety of tasks, making the system highly modular and easily extensible. Multiple brokers doing the same or different tasks can run on the same or different systems allowing the users to make efficient use of their resources. The brokers can be configured to detect the existing system and start monitoring jobs of different types. The framework can be used to transfer the results or detect any failures while execution and report it back to the user. The simple modular design and strong high-level JavaSpace API make it very easy to develop new systems for the framework. / Master of Science

Context. When dealing with large data sets and heavy calculations the common solution is clusters, supercomputers or Grids of these two. However, there are ways of gaining large computational power by utilizing the unused cycles of regular home or office computers, this are referred to as Desktop Grids. Objectives. In this study we review the current field of solutions for open source Desktop Grid computing capable of dealing with a heterogeneous set of clients and dynamic size of the Desktop Grid. We investigate current use, interest of use and priority of key attributes of Desktop Grids. Finally we want to show how time effective Desktop Grids are compared to execution on a single machine and in the process show effort needed to setup a Desktop Grid and start computing. The overall purpose of this study is to provide a path for industry organizations to take when taking the first step into Desktop Grid computing. Methods. We use a systematic review to collect information of existing open source Desktop Grid solutions. Studies are selected based on inclusion criterions and a quality assessment. A survey questioner is used to assess industry usage, interest and prioritization of attributes of Desktop Grids. We will conduct an experiment to show execution speedup as well as setup effort. Results. We found ten open source Desktop Grids fulfilling our requirements. The survey shows that Desktop Grids is used to a very little extent within industry while a majority of the participants state that there is an interest for Desktop Grids. As result of the experiment, we can say that we achieved very high speedup and that effort needed to setup a Desktop Grid is about 40 hours for one person with no prior experience to the selected Desktop Grid system. Conclusions. We conclude that industry organizations have a possible need for Desktop Grids but in order to be more successful, Desktop Grid developers must put more effort into areas as automated testing and code compilation.

Os avanços nas tecnologias de rede e nos componentes computacionais possibilitaram a criação dos sistemas de Computação Voluntária (CV) que permitem que voluntários doem seus ciclos de CPU ociosos da máquina para um determinado projeto. O BOINC é a infra-estrutura mais popular atualmente, composta de mais 5.900.000 máquinas que processam mais de 4.003 TeraFLOP por dia. Os projetos do BOINC normalmente possuem centenas de milhares de tarefas independentes e estão interessados no throughput. Cada projeto tem seu próprio servidor que é responsável por distribuir unidades de trabalho para os clientes, recuperando os resultados e validando-os. Os algoritmos de escalonamento do BOINC são complexos e têm sido usados por muitos anos. Sua eficiência e justiça foram comprovadas no contexto dos projetos orientados ao throughput. Ainda, recentemente, surgiram projetos em rajadas, com menos tarefas e interessados no tempo de resposta. Diversos trabalhos propuseram novos algoritmos de escalonamento para otimizar seu tempo de resposta individual. Entretanto, seu uso pode ser problemático na presença de outros projetos. Neste texto, são estudadas as consequências do comportamento não cooperativo nos ambientes de Computação Voluntária. Para realizar o estudo, foi necessário modificar o simulador SimGrid para melhorar seu desempenho na simulação dos sistemas de CV. A primeira contribuição do trabalho é um conjunto de melhorias no núcleo de simulação do SimGrid para remover os gargalos de desempenho. O resultado é um simulador consideravelmente mais rápido que as versões anteriores e capaz de rodar experimentos nessa área. Ainda, como segunda grande contribuição, apresentou-se como os algoritmos de escalonamento atuais do BOINC são incapazes de garantir a justiça e isolação entre os projetos. Os projetos em rajadas podem impactar drasticamente o desempenho de todos os outros projetos (rajadas ou não). Para estudar tais interações, realizou-se um detalhado, multi jogador e multi objetivo, estudo baseado em teoria dos jogos. Os experimentos e análise realizados proporcionaram um bom entendimento do impacto dos diferentes parâmetros de escalonamento e mostraram que a otimização não cooperativa pode resultar em ineficiências e num compartilhamento injusto dos recursos. / Advances in inter-networking technology and computing components have enabled Volunteer Computing (VC) systems that allows volunteers to donate their computers’ idle CPU cycles to a given project. BOINC is the most popular VC infrastructure today with over 5.900.000 hosts that deliver over 4.003 TeraFLOP per day. BOINC projects usually have hundreds of thousands of independent tasks and are interested in overall throughput. Each project has its own server which is responsible for distributing work units to clients, recovering results and validating them. The BOINC scheduling algorithms are complex and have been used for many years now. Their efficiency and fairness have been assessed in the context of throughput oriented projects. Yet, recently, burst projects, with fewer tasks and interested in response time, have emerged. Many works have proposed new scheduling algorithms to optimize individual response time but their use may be problematic in presence of other projects. In this text, we study the consequences of non-cooperative behavior in volunteer computing environment. In order to perform our study, we needed to modify the SimGrid simulator to improve its performance simulating VC systems. So, the first contribution is a set of improvements in SimGrid’s core simulation to remove its performance bottlenecks. The result is a simulator considerably faster than the previous versions and able to run VC experiments. Also, in the second contribution, we show that the commonly used BOINC scheduling algorithms are unable to enforce fairness and project isolation. Burst projects may dramatically impact the performance of all other projects (burst or non-burst). To study such interactions, we perform a detailed, multi-player and multi-objective game theoretic study. Our analysis and experiments provide a good understanding on the impact of the different scheduling parameters and show that the non-cooperative optimization may result in inefficient and unfair share of the resources.

Os avanços nas tecnologias de rede e nos componentes computacionais possibilitaram a criação dos sistemas de Computação Voluntária (CV) que permitem que voluntários doem seus ciclos de CPU ociosos da máquina para um determinado projeto. O BOINC é a infra-estrutura mais popular atualmente, composta de mais 5.900.000 máquinas que processam mais de 4.003 TeraFLOP por dia. Os projetos do BOINC normalmente possuem centenas de milhares de tarefas independentes e estão interessados no throughput. Cada projeto tem seu próprio servidor que é responsável por distribuir unidades de trabalho para os clientes, recuperando os resultados e validando-os. Os algoritmos de escalonamento do BOINC são complexos e têm sido usados por muitos anos. Sua eficiência e justiça foram comprovadas no contexto dos projetos orientados ao throughput. Ainda, recentemente, surgiram projetos em rajadas, com menos tarefas e interessados no tempo de resposta. Diversos trabalhos propuseram novos algoritmos de escalonamento para otimizar seu tempo de resposta individual. Entretanto, seu uso pode ser problemático na presença de outros projetos. Neste texto, são estudadas as consequências do comportamento não cooperativo nos ambientes de Computação Voluntária. Para realizar o estudo, foi necessário modificar o simulador SimGrid para melhorar seu desempenho na simulação dos sistemas de CV. A primeira contribuição do trabalho é um conjunto de melhorias no núcleo de simulação do SimGrid para remover os gargalos de desempenho. O resultado é um simulador consideravelmente mais rápido que as versões anteriores e capaz de rodar experimentos nessa área. Ainda, como segunda grande contribuição, apresentou-se como os algoritmos de escalonamento atuais do BOINC são incapazes de garantir a justiça e isolação entre os projetos. Os projetos em rajadas podem impactar drasticamente o desempenho de todos os outros projetos (rajadas ou não). Para estudar tais interações, realizou-se um detalhado, multi jogador e multi objetivo, estudo baseado em teoria dos jogos. Os experimentos e análise realizados proporcionaram um bom entendimento do impacto dos diferentes parâmetros de escalonamento e mostraram que a otimização não cooperativa pode resultar em ineficiências e num compartilhamento injusto dos recursos. / Advances in inter-networking technology and computing components have enabled Volunteer Computing (VC) systems that allows volunteers to donate their computers’ idle CPU cycles to a given project. BOINC is the most popular VC infrastructure today with over 5.900.000 hosts that deliver over 4.003 TeraFLOP per day. BOINC projects usually have hundreds of thousands of independent tasks and are interested in overall throughput. Each project has its own server which is responsible for distributing work units to clients, recovering results and validating them. The BOINC scheduling algorithms are complex and have been used for many years now. Their efficiency and fairness have been assessed in the context of throughput oriented projects. Yet, recently, burst projects, with fewer tasks and interested in response time, have emerged. Many works have proposed new scheduling algorithms to optimize individual response time but their use may be problematic in presence of other projects. In this text, we study the consequences of non-cooperative behavior in volunteer computing environment. In order to perform our study, we needed to modify the SimGrid simulator to improve its performance simulating VC systems. So, the first contribution is a set of improvements in SimGrid’s core simulation to remove its performance bottlenecks. The result is a simulator considerably faster than the previous versions and able to run VC experiments. Also, in the second contribution, we show that the commonly used BOINC scheduling algorithms are unable to enforce fairness and project isolation. Burst projects may dramatically impact the performance of all other projects (burst or non-burst). To study such interactions, we perform a detailed, multi-player and multi-objective game theoretic study. Our analysis and experiments provide a good understanding on the impact of the different scheduling parameters and show that the non-cooperative optimization may result in inefficient and unfair share of the resources.

Os avanços nas tecnologias de rede e nos componentes computacionais possibilitaram a criação dos sistemas de Computação Voluntária (CV) que permitem que voluntários doem seus ciclos de CPU ociosos da máquina para um determinado projeto. O BOINC é a infra-estrutura mais popular atualmente, composta de mais 5.900.000 máquinas que processam mais de 4.003 TeraFLOP por dia. Os projetos do BOINC normalmente possuem centenas de milhares de tarefas independentes e estão interessados no throughput. Cada projeto tem seu próprio servidor que é responsável por distribuir unidades de trabalho para os clientes, recuperando os resultados e validando-os. Os algoritmos de escalonamento do BOINC são complexos e têm sido usados por muitos anos. Sua eficiência e justiça foram comprovadas no contexto dos projetos orientados ao throughput. Ainda, recentemente, surgiram projetos em rajadas, com menos tarefas e interessados no tempo de resposta. Diversos trabalhos propuseram novos algoritmos de escalonamento para otimizar seu tempo de resposta individual. Entretanto, seu uso pode ser problemático na presença de outros projetos. Neste texto, são estudadas as consequências do comportamento não cooperativo nos ambientes de Computação Voluntária. Para realizar o estudo, foi necessário modificar o simulador SimGrid para melhorar seu desempenho na simulação dos sistemas de CV. A primeira contribuição do trabalho é um conjunto de melhorias no núcleo de simulação do SimGrid para remover os gargalos de desempenho. O resultado é um simulador consideravelmente mais rápido que as versões anteriores e capaz de rodar experimentos nessa área. Ainda, como segunda grande contribuição, apresentou-se como os algoritmos de escalonamento atuais do BOINC são incapazes de garantir a justiça e isolação entre os projetos. Os projetos em rajadas podem impactar drasticamente o desempenho de todos os outros projetos (rajadas ou não). Para estudar tais interações, realizou-se um detalhado, multi jogador e multi objetivo, estudo baseado em teoria dos jogos. Os experimentos e análise realizados proporcionaram um bom entendimento do impacto dos diferentes parâmetros de escalonamento e mostraram que a otimização não cooperativa pode resultar em ineficiências e num compartilhamento injusto dos recursos. / Advances in inter-networking technology and computing components have enabled Volunteer Computing (VC) systems that allows volunteers to donate their computers’ idle CPU cycles to a given project. BOINC is the most popular VC infrastructure today with over 5.900.000 hosts that deliver over 4.003 TeraFLOP per day. BOINC projects usually have hundreds of thousands of independent tasks and are interested in overall throughput. Each project has its own server which is responsible for distributing work units to clients, recovering results and validating them. The BOINC scheduling algorithms are complex and have been used for many years now. Their efficiency and fairness have been assessed in the context of throughput oriented projects. Yet, recently, burst projects, with fewer tasks and interested in response time, have emerged. Many works have proposed new scheduling algorithms to optimize individual response time but their use may be problematic in presence of other projects. In this text, we study the consequences of non-cooperative behavior in volunteer computing environment. In order to perform our study, we needed to modify the SimGrid simulator to improve its performance simulating VC systems. So, the first contribution is a set of improvements in SimGrid’s core simulation to remove its performance bottlenecks. The result is a simulator considerably faster than the previous versions and able to run VC experiments. Also, in the second contribution, we show that the commonly used BOINC scheduling algorithms are unable to enforce fairness and project isolation. Burst projects may dramatically impact the performance of all other projects (burst or non-burst). To study such interactions, we perform a detailed, multi-player and multi-objective game theoretic study. Our analysis and experiments provide a good understanding on the impact of the different scheduling parameters and show that the non-cooperative optimization may result in inefficient and unfair share of the resources.

This thesis introduces viable password recovery tools and their categories as well as the technologies and hardware commonly used in this field of informatics. It follows by an overview of the available benchmarking tools for the given hardware. Thesis later contains a description of the custom benchmarking process targeting the aspects of interest. Later, the thesis moves to a distributed system FITcrack as it proposes and experimentally implements new features. The thesis finishes by comparison of the additions against the original state and highlights the areas of improvement.

The goal of this thesis is to analyze the technologies for distributed computing in password cracking. Distribution is a key factor regarding the total time of cracking the password which can sometimes take up to tens of years. In the introductory section we take a look at the general password cracking, types of attacks and the most popular tools. Next we address the GPU parallelization as well as the need of distributed computing on multiple computers. We look at all kinds of technologies, such as VirtualCL, BOINC, MPI and analyze their usability in password cracking. We examine each technology's performance, efficiency, scalability and adaptability when given pre-defined conditions. Part of this thesis is a design and implementation of distributed password cracking using MPI technology along with Hashcat, a self-proclaimed World's fastest password cracker.

The aim of this thesis is a distributed solution for password recovery, using hashcat tool. The basis of this solution is password recovery tool Fitcrack, developed during my previous work on TARZAN project. The jobs distribution is done using BOINC platform, which is widely used for volunteer computing in a variety of scientific projects. The outcome of this work is a tool, which uses robust and reliable way of job distribution across a local or the Internet network. On the client side, fast and efficient password recovery process takes place, using OpenCL standard for acceleration of the whole process with the use of GPGPU principle.

This thesis is focused on distributed systems modeling using Petri nets. Distributed systems are increasingly being implemented in applications and computing systems, where their task is to ensure sufficient performance and stability for a large number of its users. When modeling a distributed systems, stochastic behavior of Petri nets is important, which will provide more realistic simulations. Therefore, this thesis focuses mainly on timed Petri nets. The theoretical part of this thesis summarizes distributed systems, their properties, types and available architectures, as well as Petri nets, their representation, types and the principle of an operation. In the practical part, two models were implemented, namely a horizontally scaled web application divided into several services with a distributed database and a large grid computing system, more precisely the BOINC platform with the Folding@home project. Both models were implemented using the PetNetSim library of Python. The goal of this thesis is to perform simulations on the created models for different scenarios of their behavior.