MCS-IOV : Real-time I/o virtualization for mixed-criticality systems

In mixed-criticality systems, timely handling of I/O is a key for the system being successfully implemented and functioning appropriately. The criticality levels of functions and sometimes the whole system are often dependent on the state of the I/O. An I/O system for a MCS must provide simultaneously isolation/separation, performance/efficiency and timing-predictability, as well as being able to manage I/O resource in an adaptive manner to facilitate efficient yet safe resource sharing among components of different criticality levels. Existing approaches cannot achieve all of these requirements simultaneously. This paper presents a MCS I/O management framework, termed MCS-IOV. MCS-IOV is based on hardware assisted virtualisation, which provides temporal and spatial isolation and prohibits fault propagation with small extra overhead in performance. MCS-IOV extends a real-time I/O virtualisation system, by supporting the concept of mixed criticalities and customised interfaces for schedulers, which offers good timing-preditability. MCS-IOV supports I/O driven criticality mode switch (the mode switch can be triggered by detection of unexpected I/O behaviors, e.g., a higher I/O utilization than expected) and timely I/O resource reconfiguration up on that. Finally, We evaluated and demonstrate MCS-IOV in different aspects

OSS architecture for mixed-criticality systems – a dual view from a software and system engineering perspective

Computer-based automation in industrial appliances led to a growing number of logically dependent, but physically separated embedded control units per appliance. Many of those components are safety-critical systems, and require adherence to safety standards, which is inconsonant with the relentless demand for features in those appliances. Features lead to a growing amount of control units per appliance, and to a increasing complexity of the overall software stack, being unfavourable for safety certifications. Modern CPUs provide means to revise traditional separation of concerns design primitives: the consolidation of systems, which yields new engineering challenges that concern the entire software and system stack. Multi-core CPUs favour economic consolidation of formerly separated systems with one efficient single hardware unit. Nonetheless, the system architecture must provide means to guarantee the freedom from interference between domains of different criticality. System consolidation demands for architectural and engineering strategies to fulfil requirements (e.g., real-time or certifiability criteria) in safety-critical environments. In parallel, there is an ongoing trend to substitute ordinary proprietary base platform software components by mature OSS variants for economic and engineering reasons. There are fundamental differences of processual properties in development processes of OSS and proprietary software. OSS in safety-critical systems requires development process assessment techniques to build an evidence-based fundament for certification efforts that is based upon empirical software engineering methods. In this thesis, I will approach from both sides: the software and system engineering perspective. In the first part of this thesis, I focus on the assessment of OSS components: I develop software engineering techniques that allow to quantify characteristics of distributed OSS development processes. I show that ex-post analyses of software development processes can be used to serve as a foundation for certification efforts, as it is required for safety-critical systems. In the second part of this thesis, I present a system architecture based on OSS components that allows for consolidation of mixed-criticality systems on a single platform. Therefore, I exploit virtualisation extensions of modern CPUs to strictly isolate domains of different criticality. The proposed architecture shall eradicate any remaining hypervisor activity in order to preserve real-time capabilities of the hardware by design, while guaranteeing strict isolation across domains.Computergestützte Automatisierung industrieller Systeme führt zu einer wachsenden Anzahl an logisch abhängigen, aber physisch voneinander getrennten Steuergeräten pro System. Viele der Einzelgeräte sind sicherheitskritische Systeme, welche die Einhaltung von Sicherheitsstandards erfordern, was durch die unermüdliche Nachfrage an Funktionalitäten erschwert wird. Diese führt zu einer wachsenden Gesamtzahl an Steuergeräten, einhergehend mit wachsender Komplexität des gesamten Softwarekorpus, wodurch Zertifizierungsvorhaben erschwert werden. Moderne Prozessoren stellen Mittel zur Verfügung, welche es ermöglichen, das traditionelle >Trennung von Belangen< Designprinzip zu erneuern: die Systemkonsolidierung. Sie stellt neue ingenieurstechnische Herausforderungen, die den gesamten Software und Systemstapel betreffen. Mehrkernprozessoren begünstigen die ökonomische und effiziente Konsolidierung vormals getrennter Systemen zu einer effizienten Hardwareeinheit. Geeignete Systemarchitekturen müssen jedoch die Rückwirkungsfreiheit zwischen Domänen unterschiedlicher Kritikalität sicherstellen. Die Konsolidierung erfordert architektonische, als auch ingenieurstechnische Strategien um die Anforderungen (etwa Echtzeit- oder Zertifizierbarkeitskriterien) in sicherheitskritischen Umgebungen erfüllen zu können. Zunehmend werden herkömmliche proprietär entwickelte Basisplattformkomponenten aus ökonomischen und technischen Gründen vermehrt durch ausgereifte OSS Alternativen ersetzt. Jedoch hindern fundamentale Unterschiede bei prozessualen Eigenschaften des Entwicklungsprozesses bei OSS den Einsatz in sicherheitskritischen Systemen. Dieser erfordert Techniken, welche es erlauben die Entwicklungsprozesse zu bewerten um ein evidenzbasiertes Fundament für Zertifizierungsvorhaben basierend auf empirischen Methoden des Software Engineerings zur Verfügung zu stellen. In dieser Arbeit nähere ich mich von beiden Seiten: der Softwaretechnik, und der Systemarchitektur. Im ersten Teil befasse ich mich mit der Beurteilung von OSS Komponenten: Ich entwickle Softwareanalysetechniken, welche es ermöglichen, prozessuale Charakteristika von verteilten OSS Entwicklungsvorhaben zu quantifizieren. Ich zeige, dass rückschauende Analysen des Entwicklungsprozess als Grundlage für Softwarezertifizierungsvorhaben genutzt werden können. Im zweiten Teil dieser Arbeit widme ich mich der Systemarchitektur. Ich stelle eine OSS-basierte Systemarchitektur vor, welche die Konsolidierung von Systemen gemischter Kritikalität auf einer alleinstehenden Plattform ermöglicht. Dazu nutze ich Virtualisierungserweiterungen moderner Prozessoren aus, um die Hardware in strikt voneinander isolierten Rechendomänen unterschiedlicher Kritikalität unterteilen zu können. Die vorgeschlagene Architektur soll jegliche Betriebsstörungen des Hypervisors beseitigen, um die Echtzeitfähigkeiten der Hardware bauartbedingt aufrecht zu erhalten, während strikte Isolierung zwischen Domänen stets sicher gestellt ist

Container network functions: bringing NFV to the network edge

In order to cope with the increasing network utilization driven by new mobile clients, and to satisfy demand for new network services and performance guarantees, telecommunication service providers are exploiting virtualization over their network by implementing network services in virtual machines, decoupled from legacy hardware accelerated appliances. This effort, known as NFV, reduces OPEX and provides new business opportunities. At the same time, next generation mobile, enterprise, and IoT networks are introducing the concept of computing capabilities being pushed at the network edge, in close proximity of the users. However, the heavy footprint of today's NFV platforms prevents them from operating at the network edge. In this article, we identify the opportunities of virtualization at the network edge and present Glasgow Network Functions (GNF), a container-based NFV platform that runs and orchestrates lightweight container VNFs, saving core network utilization and providing lower latency. Finally, we demonstrate three useful examples of the platform: IoT DDoS remediation, on-demand troubleshooting for telco networks, and supporting roaming of network functions

Multi-tier GPU virtualization for deep learning in cloud-edge systems

Accelerator virtualization offers several advantages in the context of cloud-edge computing. Relatively weak user devices can enhance performance when running workloads by accessing virtualized accelerators available on other resources in the cloud-edge continuum. However, cloud-edge systems are heterogeneous, often leading to compatibility issues arising from various hardware and software stacks present in the system. One mechanism to alleviate this issue is using containers for deploying workloads. Containers isolate applications and their dependencies and store them as images that can run on any device. In addition, user devices may move during the course of application execution, and thus mechanisms such as container migration are required to move running workloads from one resource to another in the network. Furthermore, an optimal destination will need to be determined when migrating between virtual accelerators. Scheduling and placement strategies are incorporated to choose the best possible location depending on the workload requirements. This paper presents AVEC , a framework for accelerator virtualization in cloud-edge computing. The AVEC framework enables the offloading of deep learning workloads for inference from weak user devices to computationally more powerful devices in a cloud-edge network. AVEC incorporates a mechanism that efficiently manages and schedules the virtualization of accelerators. It also supports migration between accelerators to enable stateless container migration. The experimental analysis highlights that AVEC can achieve up to 7x speedup by offloading applications to remote resources. Furthermore, AVEC features a low migration downtime that is less than 5 seconds.PostprintPeer reviewe