Chapter SW Annotation Techniques and RTOS Modelling for Native Simulation of Heterogeneous Embedded Systems

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A hardware-assisted translation cache for dynamic binary translation in embedded systems

Approaches to Dynamic Binary Translation (DBT) on resource-constrained embedded systems are not straight forward, leading to several improvements and acceleration suggestions that rely on dedicated hardware. Software to hardware offloading is a common acceleration procedure used when software-only approaches do not meet the performance requirements, making such approach suitable to be successfully applied to DBT. This article approaches hardware offloading to address some limitations of an in-house DBT engine, the DBTOR, regarding its Translation Cache (TCache) management mechanism. The suggested approaches are non-intrusive to the target architecture, which cope with the commercial-off-the-shelf (COTS)-driven deployment of DBT for the resource-constrained embedded devices. This work proposes a TCache management hardware module that overpasses the linked list and hash table software-only approaches, resulting in a performance improvement of 25% and 26%, respectively..This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013

MODELA DBT: Model-driven elaboration language applied to dynamic binary translation

Industrial solutions design is a highly complex topic due to the challenge of integrating multiple technologies into a single solution, the inherent complexity of the problems to be solved and also because the proposed solutions often require a great level of interoperability among their components and also the outside world. Dynamic Binary Translation has been used as a tool to deal with such interoperability issues, e.g., legacy support, virtualization and secure execution, among others. However its integration in the industry as an end-product is hampered by the intricate variability management required in this subject. To address these issues and in an attempt to power DBT utilization as an interoperability-providing tool, we propose a model-driven DSL modeling language for DBT architectures. The developed DSL proved to be efficient to model an in-house DBT engine, and MODELA DBT, a framework for ready-to-use DBT solutions was obtained. MODELA DBT provides design validation, easy configuration of customizable DBT parameters and components, as well as code generation features.This work has been supported by COMPETE: POCI-Ol-0145-FEDER-007043 and FCT - Fundação para a Ciência e figuration granularity, code generation efficiency and design verification. Tecnologia within the Project Scope: UID/CEC/00319/2013. F. Salgado is supported by FCT (grant SFRH/BD/81681/2011)

Simulation-based Fault Injection with QEMU for Speeding-up Dependability Analysis of Embedded Software

Simulation-based fault injection (SFI) represents a valuable solu- tion for early analysis of software dependability and fault tolerance properties before the physical prototype of the target platform is available. Some SFI approaches base the fault injection strategy on cycle-accurate models imple- mented by means of Hardware Description Languages (HDLs). However, cycle- accurate simulation has revealed to be too time-consuming when the objective is to emulate the effect of soft errors on complex microprocessors. To overcome this issue, SFI solutions based on virtual prototypes of the target platform has started to be proposed. However, current approaches still present some draw- backs, like, for example, they work only for specific CPU architectures, or they require code instrumentation, or they have a different target (i.e., design errors instead of dependability analysis). To address these disadvantages, this paper presents an efficient fault injection approach based on QEMU, one of the most efficient and popular instruction-accurate emulator for several microprocessor architectures. As main goal, the proposed approach represents a non intrusive technique for simulating hardware faults affecting CPU behaviours. Perma- nent and transient/intermittent hardware fault models have been abstracted without losing quality for software dependability analysis. The approach mini- mizes the impact of the fault injection procedure in the emulator performance by preserving the original dynamic binary translation mechanism of QEMU. Experimental results for both x86 and ARM processors proving the efficiency and effectiveness of the proposed approach are presented

A System-Level Dynamic Binary Translator using Automatically-Learned Translation Rules

System-level emulators have been used extensively for system design, debugging and evaluation. They work by providing a system-level virtual machine to support a guest operating system (OS) running on a platform with the same or different native OS that uses the same or different instruction-set architecture. For such system-level emulation, dynamic binary translation (DBT) is one of the core technologies. A recently proposed learning-based DBT approach has shown a significantly improved performance with a higher quality of translated code using automatically learned translation rules. However, it has only been applied to user-level emulation, and not yet to system-level emulation. In this paper, we explore the feasibility of applying this approach to improve system-level emulation, and use QEMU to build a prototype. ... To achieve better performance, we leverage several optimizations that include coordination overhead reduction to reduce the overhead of each coordination, and coordination elimination and code scheduling to reduce the coordination frequency. Experimental results show that it can achieve an average of 1.36X speedup over QEMU 6.1 with negligible coordination overhead in the system emulation mode using SPEC CINT2006 as application benchmarks and 1.15X on real-world applications.Comment: 10 pages, 19 figures, to be published in International Symposium on Code Generation and Optimization (CGO) 202

A PUF-and biometric-based lightweight hardware solution to increase security at sensor nodes

Security is essential in sensor nodes which acquire and transmit sensitive data. However, the constraints of processing, memory and power consumption are very high in these nodes. Cryptographic algorithms based on symmetric key are very suitable for them. The drawback is that secure storage of secret keys is required. In this work, a low-cost solution is presented to obfuscate secret keys with Physically Unclonable Functions (PUFs), which exploit the hardware identity of the node. In addition, a lightweight fingerprint recognition solution is proposed, which can be implemented in low-cost sensor nodes. Since biometric data of individuals are sensitive, they are also obfuscated with PUFs. Both solutions allow authenticating the origin of the sensed data with a proposed dual-factor authentication protocol. One factor is the unique physical identity of the trusted sensor node that measures them. The other factor is the physical presence of the legitimate individual in charge of authorizing their transmission. Experimental results are included to prove how the proposed PUF-based solution can be implemented with the SRAMs of commercial Bluetooth Low Energy (BLE) chips which belong to the communication module of the sensor node. Implementation results show how the proposed fingerprint recognition based on the novel texture-based feature named QFingerMap16 (QFM) can be implemented fully inside a low-cost sensor node. Robustness, security and privacy issues at the proposed sensor nodes are discussed and analyzed with experimental results from PUFs and fingerprints taken from public and standard databases.Ministerio de Economía, Industria y Competitividad TEC2014-57971-R, TEC2017-83557-