REMIND: A Framework for the Resilient Design of Automotive Systems

In the past years, great effort has been spent on enhancing the security and safety of vehicular systems. Current advances in information and communication technology have increased the complexity of these systems and lead to extended functionalities towards self-driving and more connectivity. Unfortunately, these advances open the door for diverse and newly emerging attacks that hamper the security and, thus, the safety of vehicular systems. In this paper, we contribute to supporting the design of resilient automotive systems. We review and analyze scientific literature on resilience techniques, fault tolerance, and dependability. As a result, we present the REMIND resilience framework providing techniques for attack detection, mitigation, recovery, and resilience endurance. Moreover, we provide guidelines on how the REMIND framework can be used against common security threats and attacks and further discuss the trade-offs when applying these guidelines

Managing Event-Driven Applications in Heterogeneous Fog Infrastructures

The steady increase in digitalization propelled by the Internet of Things (IoT) has led to a deluge of generated data at unprecedented pace. Thereby, the promise to realize data-driven decision-making is a major innovation driver in a myriad of industries. Based on the widely used event processing paradigm, event-driven applications allow to analyze data in the form of event streams in order to extract relevant information in a timely manner. Most recently, graphical flow-based approaches in no-code event processing systems have been introduced to significantly lower technological entry barriers. This empowers non-technical citizen technologists to create event-driven applications comprised of multiple interconnected event-driven processing services. Still, today’s event-driven applications are focused on centralized cloud deployments that come with inevitable drawbacks, especially in the context of IoT scenarios that require fast results, are limited by the available bandwidth, or are bound by the regulations in terms of privacy and security. Despite recent advances in the area of fog computing which mitigate these shortcomings by extending the cloud and moving certain processing closer to the event source, these approaches are hardly established in existing systems. Inherent fog computing characteristics, especially the heterogeneity of resources alongside novel application management demands, particularly the aspects of geo-distribution and dynamic adaptation, pose challenges that are currently insufficiently addressed and hinder the transition to a next generation of no-code event processing systems. The contributions of this thesis enable citizen technologists to manage event-driven applications in heterogeneous fog infrastructures along the application life cycle. Therefore, an approach for a holistic application management is proposed which abstracts citizen technologists from underlying technicalities. This allows to evolve present event processing systems and advances the democratization of event-driven application management in fog computing. Individual contributions of this thesis are summarized as follows: 1. A model, manifested in a geo-distributed system architecture, to semantically describe characteristics specific to node resources, event-driven applications and their management to blend application-centric and infrastructure-centric realms. 2. Concepts for geo-distributed deployment and operation of event-driven applications alongside strategies for flexible event stream management. 3. A methodology to support the evolution of event-driven applications including methods to dynamically reconfigure, migrate and offload individual event-driven processing services at run-time. The contributions are introduced, applied and evaluated along two scenarios from the manufacturing and logistics domain

Embedded Virtual Machines for Robust Wireless Control Systems

Embedded wireless networks have largely focused on open loop sensing and monitoring. To address actuation in closed loop wireless control systems there is a strong need to re-think the communication architectures and protocols for reliability, coordination and control. As the links, nodes and topology of wireless systems are inherently unreliable, such time-critical and safety-critical applications require programming abstractions where the tasks are assigned to the sensors, actuators and controllers as a single component rather than statically mapping a set of tasks to a specific physical node at design time. To this end, we introduce the Embedded Virtual Machine (EVM), a powerful and flexible programming abstraction where virtual components and their properties are maintained across node boundaries. In the context of process and discrete control, an EVM is the distributed runtime system that dynamically selects primary-backup sets of controllers to guarantee QoS given spatial and temporal constraints of the underlying wireless network. The EVM architecture defines explicit mechanisms for control, data and fault communication within the virtual component. EVM-based algorithms introduce new capabilities such as predictable outcomes and provably minimal graceful degradation during sensor/actuator failure, adaptation to mode changes and runtime optimization of resource consumption. Through the design of a natural gas process plant hardware-in-loop simulation we aim to demonstrate the preliminary capabilities of EVM-based wireless networks

Managing power amongst a group of networked embedded fpgas using dynamic reconfiguration and task migration

Small unpiloted aircraft (UAVs) each have limited power budgets. If a group (swarm) of small UAVs is organized to perform a common task such as geo-location then it is possible to share the total power across the group by introducing task mobility inside the group supported by an ad hoc wireless network (where the communication encoding/decodeing is also done on fpgas). In this presentation I will describe research into the construction of a distributed operating system where partial dynamic reconfiguration and network mobility are combined so that fpga tasks can be moved to make the best use of the total power available in a swarm of UAVs

MystifY : A Proactive Moving-Target Defense for a Resilient SDN Controller in Software Defined CPS

The recent devastating mission Cyber–Physical System (CPS) attacks, failures, and the desperate need to scale and to dynamically adapt to changes, revolutionized traditional CPS to what we name as Software Defined CPS (SD-CPS). SD-CPS embraces the concept of Software Defined (SD) everything where CPS infrastructure is more elastic, dynamically adaptable and online-programmable. However, in SD-CPS, the threat became more immanent, as the long-been physically-protected assets are now programmatically accessible to cyber attackers. In SD-CPSs, a network failure hinders the entire functionality of the system. In this paper, we present MystifY, a spatiotemporal runtime diversification for Moving-Target Defense (MTD) to secure the SD-CPS infrastructure. In this paper, we relied on Smart Grid networks as crucial SD-CPS application to evaluate our presented solution. MystifY’s MTD relies on a set of pillars to ensure the SDN controller resiliency against failures and attacks. The 1st pillar is a grid-aware algorithm that optimally allocates the most suitable controller–deployment location in large-scale grids. The 2nd pillar is a special diversifier that dynamically relocates the controller between heterogeneously configured hosts to avoid host-based attacks. The 3rd pillar is a temporal diversifier that dynamically detours controller–workload between multiple controllers to enhance their reliability and to detect and avoid controller intrusions. Our experimental results showed the efficiency and effectiveness of the presented approach

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position

Cluster-Wide Context Switch of Virtualized Jobs

International audienceClusters are mostly used through Resources Management Systems (RMS) with a static allocation of resources for a bounded amount of time. Those approaches are known to be insufficient for an efficient use of clusters. To provide a finer RMS, job preemption, migration and dynamic allocation of resources are required. However due to the complexity of developing and using such mechanisms, advanced scheduling strategies have rarely been deployed. This trend is currently evolving thanks to the use of migration and preemption capabilities of Virtual Machines (VMs). However, although the manipulation of jobs composed of VM enables to change the state of the jobs according to the scheduling objective, changing the state and the location of numerous VMs at each decision is tedious and degrades the overall performance. In addition to the scheduling policy implementation, developers have to focus on the feasibility of the actions while executing them in the most efficient way. In this paper, we argue such an operation is independent from the policy itself and can be addressed through a generic mechanism, the cluster-wide context switch. Thanks to it, developers can implement sophisticated algorithms to schedule jobs without handling the issues related to their manipulations. They only focus on the implementation of their algorithm to select the jobs to run while the cluster-wide context switch system performs the necessary actions to switch from the current to the new situation. As a proof of concept, we evaluate the interest of the cluster-wide context switch through a sample scheduler that executes jobs as early as possible, even partially, regarding to their current resources requirements and their priority

An Adaptive Modular Redundancy Technique to Self-regulate Availability, Area, and Energy Consumption in Mission-critical Applications

As reconfigurable devices\u27 capacities and the complexity of applications that use them increase, the need for self-reliance of deployed systems becomes increasingly prominent. A Sustainable Modular Adaptive Redundancy Technique (SMART) composed of a dual-layered organic system is proposed, analyzed, implemented, and experimentally evaluated. SMART relies upon a variety of self-regulating properties to control availability, energy consumption, and area used, in dynamically-changing environments that require high degree of adaptation. The hardware layer is implemented on a Xilinx Virtex-4 Field Programmable Gate Array (FPGA) to provide self-repair using a novel approach called a Reconfigurable Adaptive Redundancy System (RARS). The software layer supervises the organic activities within the FPGA and extends the self-healing capabilities through application-independent, intrinsic, evolutionary repair techniques to leverage the benefits of dynamic Partial Reconfiguration (PR). A SMART prototype is evaluated using a Sobel edge detection application. This prototype is shown to provide sustainability for stressful occurrences of transient and permanent fault injection procedures while still reducing energy consumption and area requirements. An Organic Genetic Algorithm (OGA) technique is shown capable of consistently repairing hard faults while maintaining correct edge detector outputs, by exploiting spatial redundancy in the reconfigurable hardware. A Monte Carlo driven Continuous Markov Time Chains (CTMC) simulation is conducted to compare SMART\u27s availability to industry-standard Triple Modular Technique (TMR) techniques. Based on nine use cases, parameterized with realistic fault and repair rates acquired from publically available sources, the results indicate that availability is significantly enhanced by the adoption of fast repair techniques targeting aging-related hard-faults. Under harsh environments, SMART is shown to improve system availability from 36.02% with lengthy repair techniques to 98.84% with fast ones. This value increases to five nines (99.9998%) under relatively more favorable conditions. Lastly, SMART is compared to twenty eight standard TMR benchmarks that are generated by the widely-accepted BL-TMR tools. Results show that in seven out of nine use cases, SMART is the recommended technique, with power savings ranging from 22% to 29%, and area savings ranging from 17% to 24%, while still maintaining the same level of availability

A Survey on Virtualization of Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are gaining tremendous importance thanks to their broad range of commercial applications such as in smart home automation, health-care and industrial automation. In these applications multi-vendor and heterogeneous sensor nodes are deployed. Due to strict administrative control over the specific WSN domains, communication barriers, conflicting goals and the economic interests of different WSN sensor node vendors, it is difficult to introduce a large scale federated WSN. By allowing heterogeneous sensor nodes in WSNs to coexist on a shared physical sensor substrate, virtualization in sensor network may provide flexibility, cost effective solutions, promote diversity, ensure security and increase manageability. This paper surveys the novel approach of using the large scale federated WSN resources in a sensor virtualization environment. Our focus in this paper is to introduce a few design goals, the challenges and opportunities of research in the field of sensor network virtualization as well as to illustrate a current status of research in this field. This paper also presents a wide array of state-of-the art projects related to sensor network virtualization

On the use of Wireless Sensor Networks in Preventative Maintenance for Industry 4.0

The goal of this paper is to present a literature study on the use of Wireless Sensor Networks (WSNs) in Preventative Maintenance applications for Industry 4.0. Requirements for industrial applications are discussed along with a comparative of the characteristics of the existing and emerging WSN technology enablers. The design considerations inherent to WSNs becoming a tool to drive maintenance efficiencies are discussed in the context of implementations in the research literature and commercial solutions available on the market