Multi-core systems are increasingly interesting candidates for executing parallel real-time applications, in avionic, space or automotive industries, as they provide both computing capabilities and power efficiency. However, ensuring that timing constraints are met on such platforms is challenging, because some hardware resources are shared between cores.Assuming worst-case contentions when analyzing the schedulability of applications may result in systems mistakenly declared unschedulable, although the worst-case level of contentions can never occur in practice. In this paper, we present two contention-aware scheduling strategies that produce a time-triggered schedule of the application's tasks. Based on knowledge of the application's structure, our scheduling strategies precisely estimate the effective contentions, in order to minimize the overall makespan of the schedule. An Integer Linear Programming (ILP) solution of the scheduling problem is presented, as well as a heuristic solution that generates schedules very close to ones of the ILP (5 % longer on average), with a much lower time complexity. Our heuristic improves by 19% the overall makespan of the resulting schedules compared to a worst-case contention baseline.

The emergence of battery-powered devices has led to an increase of interest in the energy consumption of computing devices. For embedded systems, dispatching the workload on different computing units enables the optimisation of the overall energy consumption on high-performance heterogeneous platforms. However, to use the full power of heterogeneity, architecture specific binary blocks are required, each with different energy/time trade-offs. Finding a scheduling strategy that minimises the energy consumption, while guaranteeing timing constraints creates new challenges. These challenges can only be met by using the full heterogeneous capacity of the platform (e.g. heterogeneous CPU, GPU, DVFS, dynamic frequency changes from within an application).We propose an off-line scheduling algorithm for dependent multiversion tasks based on Forward List Scheduling to minimise the overall energy consumption. Our heuristic accounts for Dynamic Voltage and Frequency Scaling (DVFS) and enables applications to dynamically adapt voltage and frequency during run time. We demonstrate the benefits of multi-version task models coupled with an energy-aware scheduler. We observe that selecting the most energy efficient version for each task does not lead to the lowest energy consumption for the whole application. Then we show that our approach produces schedules that are on average 45.6% more energy efficient than schedules produced by a state-of-the-art scheduling algorithm. Next we compare our heuristic against an optimal solution derived by an Integer Linear Programming (ILP) formulation (deviation of 1.6% on average). Lastly, we empirically show that the energy consumption predicted by our scheduler is close to the actual measured energy consumption on a Odroid-XU4 board (at most -15.8%).

Computational energy-efficiency is a critical aspect of many modern embedded devices as it impacts the level of autonomy for numerous scenarios. We present a component-based energy modeling approach to abstract per-component energy in a dataflow computational network executed according to a given scheduling policy. The approach is based on a modeling tool and ultimately relies on battery state to support a wider range of energy-optimization strategies for power-critical devices. CCS Concepts• Hardware → Power estimation and optimization; • Computing methodologies → Modeling and simulation; • Computer systems organization → Embedded systems; Multicore architectures.

Coordination is a well established computing paradigm with a plethora of languages, abstractions and approaches. Yet, we are not aware of any adoption of the principle of coordination in the broad domain of cyber-physical systems, where non-functional properties, such as execution/response time, energy consumption and security are as crucial as functional correctness.We propose a coordination approach, including a functional coordination language and its associated tool flow, that considers time, energy and security as first-class citizens in application design and development. We primarily target cyber-physical systems running on off-the-shelf heterogeneous multi-core platforms. We illustrate our approach by means of a real-world use case, an unmanned aerial vehicle for autonomous reconnaissance mission, which we develop in close collaboration with industry.

Fighting malware involves analyzing large numbers of suspicious binary files. In this context, disassembly is a crucial task in malware analysis and reverse engineering. It involves the recovery of assembly instructions from binary machine code. Correct disassembly of binaries is necessary to produce a higher level representation of the code and thus allow the analysis to develop high-level understanding of its behavior and purpose. Nonetheless, it can be problematic in the case of malicious code, as malware writers often employ techniques to thwart correct disassembly by standard tools.In this paper, we focus on the disassembly of x86 selfmodifying binaries with overlapping instructions. Current state-of-the-art disassemblers fail to interpret these two common forms of obfuscation, causing an incorrect disassembly of large parts of the input. We introduce a novel disassembly method, called concatic disassembly, that combines CONCrete path execution with stATIC disassembly. We have developed a standalone disassembler called CoDisasm that implements this approach. Our approach substantially improves the success of disassembly when confronted with both self-modification and code overlap in analyzed binaries. To our knowledge, no other disassembler thwarts both of these obfuscations methods together.

Satisfying real-time requirements in cyber-physical systems is challenging as timing behaviour depends on the application software, the embedded hardware, as well as the execution environment. This challenge is exacerbated as realworld, industrial systems often use unpredictable hardware and software libraries or operating systems with timing hazards and proprietary device drivers. All these issues limit or entirely prevent the application of established real-time analysis techniques.In this paper we propose PReGO, a generative methodology for satisfying real-time requirements in industrial commercial-off-the-shelf (COTS) systems. We report on our experience in applying PReGO to a use-case: a Search & Rescue application running on a fixed-wing drone with COTS components, including an NVIDIA Jetson board and a stock Ubuntu/Linux. We empirically evaluate the impact of each integration step and demonstrate the effectiveness of our methodology in meeting real-time application requirements in terms of deadline misses and energy consumption.

Commercial-off-the-shelf (COTS) heterogeneous platforms provide immense computational power, but are difficult to program and to correctly use when real-time requirements come into play: A sound configuration of the operating system scheduler is needed, and a suitable mapping of tasks to computing units must be determined. Flawed designs lead to sub-optimal system configurations and, thus, to wasted resources or even to deadline misses and system failures.We propose YASMIN, a middleware to schedule end-user applications with real-time requirements in user space and on behalf of the operating system. YASMIN combines an easy-to-use programming interface with portability across a wide range of architectures. It treats heterogeneity on COTS embedded platforms as a first-class citizen: YASMIN supports multiple functionally equivalent task implementations with distinct extra-functional behaviour. This enables the system designer to quickly explore different scheduling policies and task-to-core mappings, and thus, to improve overall system performance.In this paper, we present the design and implementation of YAS-MIN and provide an analysis of the scheduling overhead on an Odroid-XU4 platform. We demonstrate the merits of YASMIN on an industrial use-case involving a search-and-rescue drone. CCS CONCEPTS• Computer systems organization → Real-time operating systems; Embedded software; • Software and its engineering → Software libraries and repositories.

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