The first objective of this paper is to describe the Android operating system. The chapter presents history and architecture regarding to all versions of the operating system. The significant part of chapter is focused on security. The second main topic of this paper is analysing the NFC (Near Field Communication) technology. This technology is based on an older contactless system RFID (Radio Frequency Communication), so RFID is described either. The NFC technology chapter contains the description of usability, history and the definitions of physical layer, link layer and NDEF (NFC Data Exchange) data format, used for data transmitting. The next chapter is focusing on the analysis of the NFC vulnerability. It contains a possible attacks methods and solutions how to prevent them. The output of this paper is the projection and creation of an application, which allow sending an arbitrary data between two devices using the NFC technology. Additional Bluetooth technology can be used for larger files. In this case, NFC helps to create Bluetooth communication channel which is utilized for data transfer.

A compiler allows us to describe an algorithm in a high-level programming language with a higher level of abstraction and readability than a low-level machine code. This work describes design of the compiler back-end of subset of language C for 8-bit soft-core microcontroller Xilinx PicoBlaze-3. Design is described from the initial selection of a suitable framework to the implementation itself. One of the main reasons of this work is that there is not any suitable compiler for this processor.

Data centers hosting internet-scale services consume megawatts of power. Mainly for cost reasons but also to appease environmental concerns, data center operators are interested to reduce their use of energy. This thesis investigates if and how hardware virtualization helps to improve the energy efficiency of modern cloud data centers. Our main motivation is to power off unused servers to save energy. The work encompasses three major parts: First, a simulation-driven analysis to quantify the benefits of known reservation times in infrastructure clouds. Virtual machines with similar expiration times are co-located to increase the probability to power down unused physical hosts. Second, we propose and prototyped a system to deliver truly on-demand cloud services. Idle virtual machines are suspended to free resources and as a first step to power off the physical server. Third, a novel block-level data synchronization tool enables fast and efficient state replication. Frequent state synchronization is necessary to prevent data unavailability: powering down a server disables access to the locally attached disks and any data stored on them. The techniques effectively reduce the overall number of required servers either through optimized scheduling or by suspending idle virtual machines. Fewer live servers translate into proportional energy savings, as the unused servers must no longer be powered.

This master's thesis deals with creation of generators of the code for existing virtual platforms QEMU and OVP. This work consist of study of techniques, which are used by virtual machines for their work. Main part of this work is the design of process, which transforms input instruction sets to the code used by these virtual platforms. As the result of this work functional programs, which generate the code for these virtual platforms, was created.

In this thesis, we evaluate how well isolation can be achieved between two virtual machines within a mixed criticality system on a multi-core processor. We achieve this isolation with Jailhouse, an open-source, minimalist hypervisor. We then enhance Jailhouse with core throttling, a technique we use to minimize inter-core interference between VMs. Then, we run workloads with and without core throttling to determine the effect throttling has on interference between a non-real time VM and a real-time VM. We find that Jailhouse provides excellent isolation between VMs even without throttling, and that core throttling suppresses the remaining inter-core interference to a large extent.

In a world where much of society is dependent on digital infrastructure, various cyber threats can pose a great risk to businesses, critical infrastructure and potentially entire nations. For this reason, research and education as well as the preparation of strategies,  training of personnel etc., is imperative. Cyber ranges can provide ''safe environments'' in which for example cyber security exercises and experiments can be conducted. While easier to deploy and configure than ''real'' infrastructures, monitoring of such environments during ongoing exercises/experiments poses a number of challenges. During this thesis work, the question of what types of data and information could be relevant to provide in a monitoring system for this context was investigated, with regard to aspects such as providing technical support or gaining situational awareness during exercises. Results gained from a survey with participants from relevant organizations, contributed greatly to this question. The survey and literature study also provided insights into challenges and potential problems of developing and running such monitoring. CRATE is a cyber range developed and maintained by the Swedish Defence Research Agency (FOI). In this thesis work, some of the challenges and potential problems found are tackled with a suggested design and an implemented monitoring system prototype for CRATE. Apart from providing functionality to retrieve information about accounts and privileges as well as status of services, the design of the prototype also lays the foundation for a flexible and extensible monitoring system -- fully adapted for use within a cyber range. With cyber exercises becoming both more prevalent and extensive, the need for capable monitoring of exercise environments will naturally arise. While the developed prototype may facilitate future cyber exercises/experiments in CRATE, the results of this thesis work are also ready to be used as a source of inspiration for other cyber range operators.

Virtualisation is a technology that is more and more applied due to its advantages regarding cost and operation. It is often believed that it provides a better security for an IT environment since it enables centralisation of hardware. However, virtualisation changes an IT environment fundamentally and contains new vulnerabilities that must be considered. It is of interest to evaluate whether the belief that virtual environments provide a better security for an IT environment is true or not. In this project, the resiliency against attacks for physical environments and virtual environments is analysed to determine which one provides a higher resiliency and why. Therefore, the physical and digital attack surfaces of all entities are analysed to reveal the relevant vulnerabilities that could be exploited. Beside a theoretical research, a physical and a virtual environment have been established to test chosen attacks practically. The results show that virtual environments are less resilient than physical environments, especially to common attacks. This shows that virtualisation is still a technology that is new to many companies and the vulnerabilities it has must be taken seriously.

L'objectif de cette thèse est de présenter de nouveaux algorithmes de placement de machines virtuelles (VMs) à fin d’optimiser le coût et les émissions de carbone dans les Clouds distribués. La thèse se concentre d’abord sur la rentabilité des Clouds distribués, et développe ensuite les raisons d’optimiser les coûts ainsi que les émissions de carbone. La thèse comprend deux principales parties: la première propose, développe et évalue les algorithmes de placement statiques de VMs (où un premier placement d'une VM détient pendant toute la durée de vie de la VM). La deuxième partie propose des algorithmes de placement dynamiques de VMs où le placement initial de VM peut changer dynamiquement (par exemple, grâce à la migration de VMs et à leur consolidation). Cette thèse comprend cinq contributions. La première contribution est une étude de l'état de l'art sur la répartition des coûts et des émissions de carbone dans les environnements de clouds distribués. La deuxième contribution propose une méthode d'allocation des ressources, appelée NACER, pour les clouds distribués. L'objectif est de minimiser le coût de communication du réseau pour exécuter une tâche dans un cloud distribué. La troisième contribution propose une méthode de placement VM (appelée NACEV) pour les clouds distribués. NACEV est une version étendue de NACER. Tandis que NACER considère seulement le coût de communication parmi les DCs, NACEV optimise en même temps les coûts de communication et de calcul. Il propose également un algorithme de cartographie pour placer des machines virtuelles sur des machines physiques (PM). La quatrième contribution présente une méthode de placement VM efficace en termes de coûts et de carbone (appelée CACEV) pour les clouds distribués verts. CACEV est une version étendue de NACEV. En plus de la rentabilité, CACEV considère l'efficacité des émissions de carbone pour les clouds distribués. Pour obtenir une meilleure performance, la cinquième contribution propose une méthode dynamique de placement VM (D-CACEV) pour les clouds distribués. D-CACEV est une version étendue de notre travail précédent, CACEV, avec des chiffres supplémentaires, une description et également des mécanismes de migration de VM en direct. Nous montrons que notre mécanisme conjoint de réallocation-placement de VM peut constamment optimiser à la fois le coût et l'émission de carbone dans un cloud distribué / Virtual machine (VM) placement (i.e., resource allocation) method has a direct effect on both cost and carbon emission. Considering the geographic distribution of data centers (DCs), there are a variety of resources, energy prices and carbon emission rates to consider in a distributed cloud, which makes the placement of VMs for cost and carbon efficiency even more critical and complex than in centralized clouds. The goal of this thesis is to present new VM placement algorithms to optimize cost and carbon emission in a distributed cloud. It first focuses on cost efficiency in distributed clouds and, then, extends the goal to optimization of both cost and carbon emission at the same time. Thesis includes two main parts. The first part of thesis proposes, develops and evaluates static VM placement algorithms to reach the mentioned goal where an initial placement of a VM holds throughout the lifetime of the VM. The second part proposes dynamic VM placement algorithms where the initial placement of VMs is allowed to change (e.g., through VM migration and consolidation). The first contribution is a survey of the state of the art on cost and carbon emission resource allocation in distributed cloud environments. The second contribution targets the challenge of optimizing inter-DC communication cost for large-scale tasks and proposes a Network-Aware Cost-Efficient Resource allocation method, called NACER, for distributed clouds. The goal is to minimize the network communication cost of running a task in a distributed cloud by selecting the DCs to provision the VMs in such a way that the total network distance (hop count or any reasonable measure) among the selected DCs is minimized. The third contribution proposes a Network-Aware Cost Efficient VM Placement method (called NACEV) for Distributed Clouds. NACEV is an extended version of NACER. While NACER only considers inter-DC communication cost, NACEV optimizes both communication and computing cost at the same time and also proposes a mapping algorithm to place VMs on Physical Machines (PMs) inside of the selected DCs. NACEV also considers some aspects such as heterogeneity of VMs, PMs and switches, variety of energy prices, multiple paths between PMs, effects of workload on cost (energy consumption) of cloud devices (i.e., switches and PMs) and also heterogeneity of energy model of cloud elements. The forth contribution presents a Cost and Carbon Emission-Efficient VM Placement Method (called CACEV) for green distributed clouds. CACEV is an extended version of NACEV. In addition to cost efficiency, CACEV considers carbon emission efficiency and green distributed clouds. It is a VM placement algorithm for joint optimization of computing and network resources, which also considers price, location and carbon emission rate of resources. It also, unlike previous contributions of thesis, considers IaaS Service Level Agreement (SLA) violation in the system model. To get a better performance, the fifth contribution proposes a dynamic Cost and Carbon Emission-Efficient VM Placement method (D-CACEV) for green distributed clouds. D-CACEV is an extended version of our previous work, CACEV, with additional figures, description and also live VM migration mechanisms. We show that our joint VM placement-reallocation mechanism can constantly optimize both cost and carbon emission at the same time in a distributed cloud

Modern general purpose programming languages like Java or C# provide a rich feature set and a higher degree of abstraction than conventional real-time programming languages like C/C++ or Ada. Applications developed with these modern languages are typically deployed via platform independent intermediate code. The intermediate code is typically executed by a virtualizing runtime environment. This allows for a high portability. Prominent examples are the Dalvik Virtual Machine of the Android operating system, the Java Virtual Machine as well as Microsoft .NET’s Common Language Runtime. The virtualizing runtime environment executes the instructions of the intermediate code. This introduces additional challenges to real-time software development. One issue is the transformation of the intermediate code instructions to native code instructions. If this transformation interferes with the execution of the real-time application, this might introduce jitter to its execution times. This can degrade the quality of soft real-time systems like augmented reality applications on mobile devices, but can lead to severe problems in hard real-time applications that have strict timing requirements. This thesis examines the possibility to overcome timing issues with intermediate code execution in virtualizing runtime environments. It addresses real-time suitable generation of native code from intermediate code in particular. In order to preserve the advantages of modern programming languages over conventional ones, the solution has to adhere to the following main requirements: - Intermediate code transformation does not interfere with application execution - Portability is not reduced and code transformation is still transparent to a programmer - Comparable performance Existing approaches are evaluated. A concept for real-time suitable code generation is developed. The concept bases on a pre-allocation of the native code and the elimination of indirect references, while considering and optimizing startup time of an application. This concept is implemented by the extension of an existing virtualizing runtime environment, which does not target real-time systems per se. It is evaluated qualitatively and quantitatively. A comparison of the new concept to existing approaches reveals high execution time determinism and good performance and while preserving the portability deployment of applications via intermediate code.

Several cloud providers offer reltional databases as part of their portfolio. It is however not obvious how resource virtualization and sharing, which is inherent to cloud computing, influence performance and predictability of these cloud databases. Cloud providers give little to no guarantees for consistent execution or isolation from other users. To evaluate the performance isolation capabilities of two commercial cloud databases, we ran a series of experiments over the course of a week (a query, a minute) and report variations in query response times. As a baseline, we ran the same experiments on a dedicated server in our data center. The results show that in the cloud single outliers are up to 31 times slower than the average. Additionally, one can see a point in time after which the average performance of all executed queries improves by 38 %.