This work deals with application of ARM based development board as platform for remote controlling of attached peripherals. It describes practical experiences with A20- OLinuXino-Micro-4GB development board and it’s available options. Used hardware and testing peripherals are described in the next part along with programming of the software for web interface and for communication in between development board and peripherals. The second half of this document describes design process of own embedded system beginning with schematic, continuing with PCB wiring. Each step of PCB wiring process is described with required details in text, including crucial connections between processor and memory chips. The last part contains details about setting a calibration of memory chips and designing optional peripheral modules.

This masters thesis deals with updating the Linux emulation layer (so called Linuxulator). The task was to update the layer to match the functionality of Linux 2.6. As a reference implementation, the Linux 2.6.16 kernel was chosen. The concept is loosely based on the NetBSD implementation. Most of the work was done in the summer of 2006 as a part of the Google Summer of Code students program. The focus was on bringing the NPTL (new posix thread library) support into the emulation layer, including TLS (thread local storage), futexes (fast user space mutexes), PID mangling, and some other minor things. Many small problems were identified and fixed in the process. My work was integrated into the main FreeBSD source repository and will be shipped in the upcoming 7.0R release. We, the emulation development team, are working toward making the Linux 2.6 emulation the default emulation layer in FreeBSD.

This paper presents an implementation of a lottery scheduler, presented from design through debugging to performance testing. Desirable characteristics of a general purpose scheduler include low overhead, good overall system performance for a variety of process types, and fair scheduling behavior. Testing is performed, along with an analysis of the results measuring the lottery scheduler against these characteristics. Lottery scheduling is found to provide better than average control over the relative execution rates of processes. The results show that lottery scheduling functions as a good mechanism for sharing the CPU fairly between users that are competing for the resource. While the lottery scheduler proves to have several interesting properties, overall system performance suffers and does not compare favorably with the balanced performance afforded by the standard Linux kernel’s scheduler.

The recent trend of migrating legacy computer systems to a virtualized, cloud-based environment has expanded to real-time systems. Unfortunately, modern hypervisors have no mechanism in place to guarantee the real-time performance of applications running on virtual machines. Past solutions to this problem rely on either spatial or temporal resource partitioning, both of which under-utilize the processing capacity of the host system. Paravirtualized solutions in which the guest communicates its real-time needs have been proposed, but they cannot support legacy operating systems. This thesis demonstrates the shortcomings of resource partitioning using temporally-isolated servers, presents an alternative solution to the scheduling problem called the KairosVM Flattening Scheduling Algorithm, and provides an implementation of the algorithm based on Linux and KVM. The algorithm is analyzed theoretically and an exact schedulability test for the algorithm is derived. Simulations show that the algorithm can schedule more than 90% of all randomly generated tasksets with a utilization less than 0.95. In comparison to the state-of-the-art server based approach, the KairosVM Flattening Scheduling Algorithm is able to schedule more than 20 times more tasksets with utilization of 0.95. Experimental results demonstrate that the Linux-based implementation is able to match the deadline satisfaction ratio of a state-of-the-art server-based approach when the taskset is schedulable using the state-of-the-art approach. When tasksets are unschedulable, the implementation is able to increase the deadline satisfaction ratio of Vanilla KVM by up to 400%. Furthermore, unlike paravirtualized solutions, the implementation supports legacy systems through the use of introspection. / Master of Science

In industry there has been a large focus on system integration and server consolidation, even for real-time systems, leading to an interest in virtualization. However, many modern hypervisors do not inherently support the strict timing guarantees of real-time applications. There are several challenges that arise when trying to virtualize a real-time application. One key challenge is to maintain the guest's real-time guarantees. In a typical virtualized environment there is a hierarchy of schedulers. Past solutions solve this issue by strict resource reservation models. These reservations are pessimistic as they accommodate the worst case execution time of each real-time task. We model real-time tasks using probabilistic execution times instead of worst case execution times which are difficult to calculate and are not representative of the actual execution times. In this thesis, we present a probabilistic hierarchical framework to schedule real-time virtual machines. Our framework reduces the number CPUs reserved for each guest by up to 45%, while only decreasing the deadline satisfaction by 2.7%. In addition, we introduce an introspection mechanism capable of gathering real-time characteristics from the guest systems and present them to the host scheduler. Evaluations show that our mechanism incurs up to 21x less overhead than that of bleeding edge introspection techniques when tracing real-time events. / Master of Science

Recent trends in the computer market suggest that emerging computing platforms will be increasingly parallel and heterogeneous, in order to satisfy the user demand for improved performance and superior energy savings. Heterogeneity is a promising technology to keep growing the number of cores per chip without breaking the power wall. However, existing system software is able to cope with homogeneous architectures, but it was not designed to run on heterogeneous architectures, therefore, new system software designs are necessary. One innovative design is the multikernel OS deployed by the Barrelfish operating system (OS) which partitions hardware resources to independent kernel instances that communicate exclusively by message passing, without exploiting the shared memory available amongst different CPUs in a multicore platform. Popcorn Linux implements an extension of the multikernel OS design, called replicated-kernel OS, with the goal of providing a Linux-based single system image environment on top of multiple kernels, which can eventually run on different ISA processors. A replicated-kernel OS replicates the state of various OS sub-systems amongst kernels that cooperate using message passing to distribute or access various services uniquely available on each kernel. In this thesis, we present mechanisms to distribute signals, namespaces, inter-thread synchronizations and socket state replication. These features are built on top of the existing messaging layer, process or thread migration and address space consistency protocol to provide the application with an illusion of single system image and developers with the SMP programming environment they are most familiar with. The mechanisms developed were unit tested with micro benchmarks to validate their correctness and to measure the gained speed up or additive overhead. Real-world applications were also used to benchmark the developed mechanisms on homogeneous and on heterogeneous architectures. It is found that the contributed Popcorn synchronization mechanism exhibits overhead compared to vanilla Linux on multicore as Linux's equivalent mechanisms are tightly coupled with underlying hardware cache coherency protocol, therefore, faster than software message passing. On heterogeneous platforms, the developed mechanisms allow to transparently map each portion of the application to the processor in the platform on which the execution is faster. Optimizations are recommended to further improve the performance of the proposed synchronization mechanism. However, optimizations may force the userspace application and libraries to be rewritten in order to decouple their synchronization mechanisms of shared memory, therefore losing transparency, which is one of the primary goals of this work. / Master of Science

This thesis studies the problem of experimentally evaluating the scaling behaviors of existing multicore real-time task scheduling algorithms on large-scale multicore platforms. As chip manufacturers rapidly increase the core count of processors, it becomes imperative that multicore real-time scheduling algorithms keep pace. Thus, it must be determined if existing algorithms can scale to these new high core-count platforms. Significant research exists on the theoretical performance of multicore real-time scheduling algorithms, but the vast majority of this research ignores the effects of scalability. It has been demonstrated that multicore real-time scheduling algorithms are feasible for small core-count systems (e.g. 8-core or less), but thus far the majority of the algorithmic research has never been tested on high core-count systems (e.g. 48-core or more). We present an experimental analysis of the scalability of 16 multicore real-time scheduling algorithms. These algorithms include global, clustered, and partitioned algorithms. We cover a broad range of algorithms, including deadline-based and utility accrual scheduling algorithms. These algorithms are compared under metrics including schedulability, tardiness, deadline satisfaction ratio, and utility accrual ratio. We consider multicore platforms ranging from 8 to 48 cores. The algorithms are implemented in a real-time Linux kernel we create called ChronOS. ChronOS is based on the Linux kernel's PREEMPT RT patch, which provides the underlying operating system kernel with real-time capabilities such as full kernel preemptibility and priority inheritance for kernel locking primitives. ChronOS extends these capabilities with a flexible, scalable real-time scheduling framework. Our study shows that it is possible to implement global fixed and dynamic priority and simple global utility accrual real-time scheduling algorithms which will scale to large-scale multicore platforms. Interestingly, and in contrast to the conclusion of prior research, our results reveal that some global scheduling algorithms (e.g. G-NP-EDF) is actually scalable on large core counts (e.g. 48). In our implementation, scalability is restricted by lock contention over the global schedule and the cost of inter-processor communication, rather than the global task queue implementation. We also demonstrate that certain classes of utility accrual algorithms such as the GUA class are inherently not scalable. We show that algorithms implemented with scalability as a first-order implementation goal are able to provide real-time guarantees on our 48-core platform. / Master of Science

Dynamic voltage and frequency scaling (DVFS) is an extensively studied energy manage ment technique, which aims to reduce the energy consumption of computing platforms by dynamically scaling the CPU frequency. Real-Time DVFS (RT-DVFS) is a branch of DVFS, which reduces CPU energy consumption through DVFS, while at the same time ensures that task time constraints are satisfied by constructing appropriate real-time task schedules. The literature presents numerous RT-DVFS scheduling algorithms, which employ different techniques to utilize the CPU idle time to scale the frequency. Many of these algorithms have been experimentally studied through simulations, but have not been implemented on real hardware platforms. Though simulation-based experimental studies can provide a first-order understanding, implementation-based studies can reveal actual timeliness and energy consumption behaviours. This is particularly important, when it is difficult to devise accurate simulation models of hardware, which is increasingly the case with modern systems. In this thesis, we study the timeliness and energy consumption behaviours of fourteen state- of-the-art RT-DVFS schedulers by implementing and evaluating them on two hardware platforms. The schedulers include CC-EDF, LA-EDF, REUA, DRA andd AGR1 among others, and the hardware platforms include ASUS laptop with the Intel I5 processor and a mother- board with the AMD Zacate processor. We implemented these schedulers in the ChronOS real-time Linux kernel and measured their actual timeliness and energy behaviours under a range of workloads including CPU-intensive, memory-intensive, mutual exclusion lock-intensive, and processor-underloaded and overloaded workloads. Our studies reveal that measuring the CPU power consumption as the cube of CPU frequency can lead to incorrect conclusions. In particular, it ignores the idle state CPU power consumption, which is orders of magnitude smaller than the active power consumption. Consequently, power savings obtained by exclusively optimizing active power consumption (i.e., RT-DVFS) may be offset by completing tasks sooner by running them at the highest frequency and transitioning to the idle state earlier (i.e., no DVFS). Thus, the active power consumption savings of the RT-DVFS techniques' that we report are orders of magnitude smaller than their simulation-based savings reported in the literature. / Master of Science

In the era of Linux being omnipresent, the demand for dynamically extending kernel capabil- ities without requiring changes to kernel source code or loading kernel modules at runtime is increasing. This is driven by numerous use cases such as observability, security, and network- ing, which can be efficiently addressed at the system level, underscoring the importance of such extensions. Any extension requires programmers to possess high levels of skill and thor- ough testing to ensure complete safety. The eBPF subsystem in the Linux kernel addresses this challenge by allowing applications to enhance the kernel's capabilities at runtime, while ensuring stability and security. This guaranteed safety is facilitated by the verifier engine, which statically verifies BPF code. In this thesis, we identify that the verifier implicitly relies on safety assumptions about its runtime execution environment, which are not being upheld in certain scenarios. One such critical aspect of the execution environment is the availability of stack space for use while executing the BPF program. Specifically, we high- light this fundamental issue in certain configuration of the BPF runtime environment within the Linux kernel and how this unsafe composition allowed for kernel stack overflow, thus violating safety guarantees. To tackle this problem, we propose a stack switching approach to ensure stack safety and evaluate its effectiveness. / Master of Science / Many platforms worldwide, including Meta, Netflix, Google, Cloudflare, and others, rely on the Linux kernel to manage their servers. To ensure system security, improve monitoring, and enhance networking efficiency, various kernel capabilities are dynamically added or re- moved at runtime without the need for reboots, thus minimizing downtime for users. The Linux Extended Berkeley Packet Filter (eBPF) subsystem facilitates dynamic and safe ex- tension by securely verifying the code injected into the kernel. This eases server maintenance tasks, eliminating concerns about system crashes when making runtime changes as eBPF is guaranteeing safety at all times. In our research, we demonstrate that if we attach verified eBPF in a certain manner, we can potentially stack overflow the kernel stack and crash the whole kernel due to unsafe composition with the Kernel. We also propose two solutions to this problem, which can ensure that eBPF remains safe while adhering to the guarantees it provides.

L’objectif de cette thèse est d’étudier l’efficacité énergétique des stratégies basse consommation pour des plateformes représentatives. Principalement, nous nous intéresserons aux stratégies énergétiques pour des systèmes embarqués multicœur en étudiant le comportement de politiques logicielles qui permettent la réduction effective de l’énergie tout en répondant aux exigences applicatives. Le travail présenté dans ce mémoire vise à étudier des stratégies de gestion de la consommation pour des plateformes monoprocesseur puis multiprocesseur concrètes. L’approche utilisée pour cette étude fut basée sur des plateformes représentatives afin d’identifier les paramètres significatifs, aussi bien au niveau matériel qu’au niveau applicatif, à l’inverse de nombreux travaux dans lesquels ces paramètres sont assez peu pris en compte voir ignorés. Ce travail analyse et compare diverses expérimentations menées sur des politiques énergétiques basées sur des techniques DVFS (Dynamic Voltage and Frequency Scaling) et DPS (Dynamic Power Switching) et définit les conditions sous lesquelles ces stratégies sont efficaces. Ces expérimentations ont permis d’établir des conclusions remarquables qui peuvent servir de pré-requis lors de la définition de stratégies efficaces de gestion de la consommation. Ces résultats montrent également que pour obtenir des stratégies efficientes il est nécessaire de tenir compte du domaine applicatif. Enfin, il faut noter que les modèles de haut de niveau de consommation ont été définis sur la base des mesures effectuées et afin d’estimer les gains énergétiques dès les premières étapes d’un flot de conception. / The purpose of this study is to investigate how power management strategies can be efficiently exploited in actual platforms. Primarily, the challenges in multicore based embedded systems lies in managing the energy expenditure, determining the scheduling behavior and establishing methods to monitor power and energy, so as to meet the demands of the battery life and load requirements. The work presented in this dissertation is a study of low power-aware strategies in the practical world for single and multiprocessor platforms. The approach used for this study is based on representative multiprocessor platforms (real or virtual) to identify the most influential parameters, at hardware as well as application level, unlike many existing works in which these parameters are often underestimated or sometimes even ignored. The work analyzes and compares in detail various experimentations with different power policies based on Dynamic Voltage and Frequency Scaling (DVFS) and Dynamic Power Switching (DPS) techniques, and investigates the conditions at which these policies are effective in terms of energy savings. The results of these investigations reveal many interesting and notable conclusions that can serve as prerequisites for the efficient use of power management strategies. This work also shows the potential of advanced domain specific power strategies compared to real world available strategies that are general purpose based in their majority. Finally, some high level consumption models are derived from the different energy measurement results to let the estimation of power management benefits at early stages of a system development.