Scheduling of Overload-Tolerant Computation and Multi-Mode Communication in Real-Time Systems

Real-time tasks require sufficient resources to meet deadline constraints. A component should provision sufficient resources for its workloads consisting of tasks to meet their deadlines. Supply and demand bound functions can be used to analyze the schedulability of workloads. The demand-bound function determines the maximum required computational units for a given workload and the supply-bound function determines the minimum possible resources supplied to the workload. A component will experience an overload if it receives fewer resources than required. An overload will be transient if it occurs for a bounded amount of time. Most work concentrates on designing components that avoid overloads by over-provisioning resources even though some computational units such as control system components can tolerate transient overloads. Overload-tolerant components can utilize resources more efficiently if over-provisioning of resources can be avoided. First, this dissertation presents the design of an efficient periodic resource model for scheduling computation of components that can tolerate transient overloads under the Earliest Deadline First (EDF) scheduling policy. We propose a periodic resource model for overload-tolerant components to address three problems: (1) characterize overloads and determine metrics of interest (i.e., delay), (2) derive a model to compute a periodic resource supply for a given workload and a worst-case tolerable delay, and (3) find a periodic resource supply for given control system specifications with a worst-case delay. The derived periodic resource supply can be used to derive an overload-tolerant component interface. Overload-tolerant real-time components can connect with each other in a distributed manner and thus require communication scheduling for reliable and guaranteed transmissions. Moreover, applications may require multi-mode communication for efficient data transmission. Second, this dissertation discusses communication schedules for multi-mode distributed components. Since distributed multi-mode applications are prone to suffer from delays incurred during mode changes, good communication schedules have low average mode-change delays. A key problem in designing multi-mode communication in real-time systems is the generation of schedules to move away the complexity of schedule design from the developer. We propose a mechanism to generate multi-mode communication schedules using optimization constraints associated with timing requirements. We illustrate a workflow from specifications to the generation of communication schedules through a real-time video monitoring case-study. Experimental analysis for the case-study demonstrates that schedules generated using the proposed method reduce the average mode-change delay compared to a randomized algorithm and the well-known EDF scheduling policy. Finally, this thesis discusses the synthesis of schedules for computation and communication to achieve not only performance but also separation of concerns for reducing complexity and increasing safety. To integrate overload-tolerant components using real-time communication, we derive specifications of component interfaces using the characterization of overloads and the proposed periodic resource model. The generation of communication schedules uses the specifications of interfaces which include timing requirements of possible transient overloads. A walk-through case-study explains the steps necessary to generate communication schedules using component interfaces. The interfaces provide safety through isolation of transient overload-tolerant components and the generated communication schedules provide high performance as a result of their low average mode-change delay

Semantics-Preserving Implementation of Synchronous Specifications Over Dynamic TDMA Distributed Architectures

International audienceWe propose a technique to automatically synthesize programs and schedules for hard real-time distributed (embedded) systems from synchronous data-flow models. Our technique connects the SynDEx scheduling tool and the Network Code toolchain in a seamless flow of automatic model transformations that go all the way from specification to implementation. Our contribution is the non-trivial connection between the models manipulated by SynDEx and by the Network Code toolchain, at both formal and tool level. We provide an algorithm for converting the data-dependent schedule tables output by SynDEx into Network Code programs which can be seen as an ``assembly code'' level for time-driven distributed real-time systems. The main difficulty is to ensure the preservation of both functionality and the real-time guarantees computed by SynDEx in the presence of clock drifts (which are abstracted away in the scheduling model of SynDEx). Existing tools can convert the resulting Network Code programs into software and hardware-accelerated execution units.Nous proposons une technique pour la synthèse automatique de programmes et ordonnancements pour des systèmes temps-réel (embarqués) distribués, à partir de spécifications synchrones flot de données

A Systematic Review of Fault Injection Attacks on IoT Systems

The field of the Internet of Things (IoT) is growing at a breakneck pace and its applications are becoming increasingly sophisticated with time. Fault injection attacks on IoT systems are aimed at altering software behavior by introducing faults into the hardware devices of the system. Attackers introduce glitches into hardware components, such as the clock generator, microcontroller, and voltage source, which can affect software functioning, causing it to misbehave. The methods proposed in the literature to handle fault injection attacks on IoT systems vary from hardware-based attack detection using system-level properties to analyzing the IoT software for vulnerabilities against fault injection attacks. This paper provides a systematic review of the various techniques proposed in the literature to counter fault injection attacks at both the system level and the software level to identify their limitations and propose solutions to address them. Hybrid attack detection methods at the software level are proposed to enhance the security of IoT systems against fault injection attacks. Solutions to the identified limitations are suggested using machine learning, dynamic code instrumentation tools, hardware emulation platforms, and concepts from the software testing domain. Future research possibilities, such as the use of software fault injection tools and supervised machine learning for attack detection at the software level, are investigated

Design and Development of a Machine Learning-Based Task Orchestrator for Intelligent Systems on Edge Networks

This paper proposes an edge-centric workload orchestration approach that uses machine learning in a three-tier vehicular architecture (edge, cloud via roadside unit, or cloud via cellular base station). The orchestrator uses a wireless network at the edge to receive and send over-the-air requests from vehicles, considering a metropolitan network connects the entire edge structure to support the high mobility of devices, allowing vehicles to share information and resources. Additionally, suppose the edge is congested, or its resources are unavailable. In that case, cloud resources will be used via roadside or cellular networks using a wide-area network to meet the tasks’ time constraints. Moreover, the proposed machine learning model uses variance-based sensitivity analysis to determine which inputs influence the model’s final decision. The experiments performed on the EdgeCloudSim simulator are based on modelling computational and network resources besides the representation of vehicles. The results indicate that our approach best fits task offloading over-the-air, outperforming the comparative experiments between the one-stage(our approach) model against two-stage and random models. Furthermore, by using our one-stage model that outputs the average of the prediction interval and the variance of this interval, we can measure how confident our model is in its prediction

Semantics-preserving implementation of synchronous specifications over dynamic TDMA distributed architectures

ABSTRACT We propose a technique to automatically synthesize programs and schedules for hard real-time distributed (embedded) systems from synchronous data-flow models. Our technique connects the SynDEx scheduling tool and the Network Code toolchain in a seamless flow of automatic model transformations that go all the way from specification to implementation. Our contribution is the non-trivial connection between the models manipulated by SynDEx and by the Network Code toolchain, at both formal and tool level. We provide an algorithm for converting the data-dependent schedule tables output by SynDEx into Network Code programs which can be seen as an "assembly code" level for time-driven distributed real-time systems. The main difficulty is to ensure the preservation of both functionality and the real-time guarantees computed by SynDEx in the presence of clock drifts (which are abstracted away in the scheduling model of SynDEx). Existing tools can convert the resulting Network Code programs into software and hardware-accelerated execution units

A State-of-the-Art Review of Task Scheduling for Edge Computing: A Delay-Sensitive Application Perspective

The edge computing paradigm enables mobile devices with limited memory and processing power to execute delay-sensitive, compute-intensive, and bandwidth-intensive applications on the network by bringing the computational power and storage capacity closer to end users. Edge computing comprises heterogeneous computing platforms with resource constraints that are geographically distributed all over the network. As users are mobile and applications change over time, identifying an optimal task scheduling method is a complex multi-objective optimization problem that is NP-hard, meaning the exhaustive search with a time complexity that grows exponentially can solve the problem. Therefore, various approaches are utilized to discover a good solution for scheduling the tasks within a reasonable time complexity, while achieving the most optimal solution takes exponential time. This study reviews task scheduling algorithms based on centralized and distributed methods in a three-layer computing architecture to identify their strengths and limitations in scheduling tasks to edge service nodes