, AMD. What Is Heterogeneous Computing? Available online, p.23, 2018.
A survey on modeling and model-driven engineering practices in the embedded software industry, J. Syst. Archit, vol.91, pp.62-82, 2018. ,
Data-Driven Approach for Feature Drift Detection in Embedded Electronic Devices, IFAC, vol.51, pp.1024-1029, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01869747
Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation, Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics, vol.1, pp.338-345, 2017. ,
URL : https://hal.archives-ouvertes.fr/hal-01770233
Accurate Prediction of Available Battery Time for Mobile Applications, ACM Trans. Embed. Comput. Syst, vol.15, pp.1-17, 2016. ,
Understanding application-battery interactions on smartphones: A large-scale empirical study, IEEE Access, vol.5, pp.13387-13400, 2017. ,
Accurate power modeling of modern mobile application processors, J. Syst. Archit, vol.81, pp.17-31, 2017. ,
An Environment for Automated Measuring of Energy Consumed by Android Mobile Devices, Proceedings of the 6th International Joint Conference on Pervasive and Embedded Computing and Communication Systems, pp.28-39, 2016. ,
, Proceedings of the 2017 IEEE International Conference on Software Maintenance and Evolution (ICSME), pp.273-283, 2017.
Energy efficient middleware: Design and development for mobile applications, Proceedings of the 2017 19th International Conference on Advanced Communication Technology (ICACT), pp.541-549, 2017. ,
Reliability-aware scheduling for reducing system-wide energy consumption for weakly hard real-time systems, J. Syst. Archit, vol.78, pp.30-54, 2017. ,
Minimizing energy by thermal-aware task assignment and speed scaling in heterogeneous MPSoC systems, J. Syst. Archit, vol.89, pp.118-130, 2018. ,
Seeing the unseen: Revealing mobile malware hidden communications via energy consumption and artificial intelligence, IEEE Trans. Inf. Forensics Secur, vol.11, pp.799-810, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01247495
Power-aware anomaly detection in smartphones: An analysis of on-platform versus externalized operation, Pervasive Mob. Comput, vol.18, pp.137-151, 2015. ,
Measuring and estimating power consumption in Android to support energy-based intrusion detection, J. Comput. Secur, vol.23, pp.611-637, 2015. ,
Crowdsourced system setting recommendations for mobile devices, Pervasive Mob. Comput, vol.26, pp.71-90, 2016. ,
Profiling, and Debugging the Energy Consumption of Mobile Devices, ACM Comput. Surv, vol.48, pp.1-40, 2015. ,
A Review on mobile application energy profiling: Taxonomy, state-of-the-art, and open research issues, J. Netw. Comput. Appl, vol.58, pp.42-59, 2015. ,
Energy Optimisation for Mobile Device Power Consumption: A Survey and a Unified View of Modelling for a Comprehensive Network Simulation, Mob. Networks Appl, vol.21, pp.575-588, 2016. ,
Android 5.0 APIs, 2017. ,
Measuring Power Values|Android Open Source Project? Available online, 2020. ,
, Qualcomm Innovation Center. Trepn Profiler; Qualcomm Innovation Center, 2019.
Accurate online power estimation and automatic battery behavior based power model generation for smartphones, Proceedings of the Eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis-CODES/ISSS '10, p.105, 2010. ,
Self-constructive high-rate system energy modeling for battery-powered mobile systems, In MobiSys, p.335, 2011. ,
DevScope: A Nonintrusive and Online Power Analysis Tool for Smartphone Hardware Components, Proceedings of the eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis-CODES+ISSS '12, p.353, 2010. ,
Enhancing online power estimation accuracy for smartphones, IEEE Trans. Consum. Electron, vol.58, pp.333-339, 2012. ,
A novel GPU power model for accurate smartphone power breakdown, vol.37, pp.157-164, 2015. ,
Power Profiling and Monitoring in Embedded Systems: A Comparative Study and a Novel Methodology Based on NARX Neural Networks, J. Syst. Archit, p.101805, 2020. ,
URL : https://hal.archives-ouvertes.fr/hal-02740661
PETrA: A Software-Based Tool for Estimating the Energy Profile of Android Applications, Proceedings of the 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), pp.3-6, 2017. ,
Utilization-based power consumption profiling in smartphones, Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics, vol.3, pp.881-886, 2016. ,
Estimating Software Energy Consumption with Energy Measurement Corpora, Proceedings of the 13th International Workshop on Mining Software Repositories-MSR '16, pp.49-60, 2016. ,
FEPMA: Fine-Grained Event-Driven Power Meter for Android Smartphones Based on Device Driver Layer Event Monitoring, Proceedings of the Design, Automation I& Test in Europe Conference and Exhibition (DATE), pp.24-28, 2014. ,
, , pp.1-6
Accurate and Stable Run-Time Power Modeling for Mobile and Embedded CPUs, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst, vol.36, pp.106-119, 2017. ,
Where is the Energy Spent Inside My App?: Fine Grained Energy Accounting on Smartphones with Eprof, Proceedings of the 7th ACM European Conference on Computer Systems, pp.29-42, 2012. ,
Fast self-constructive power modeling of smartphones based on battery voltage dynamics, Proceedings of the 10th USENIX Conference on Networked Systems Design and Implementation, pp.43-55, 2013. ,
On the use of nonlinear methods for low-power CPU frequency prediction based on Android context variables, Proceedings of the 2016 IEEE 15th International Symposium on Network Computing and Applications, pp.250-253, 2016. ,
Modeling of smartphones' power using neural networks, Eurasip J. Embed. Syst, p.22, 2017. ,
Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and Smartphones, Proceedings of the 21st ACM International Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems (MSWIM '18) ,
URL : https://hal.archives-ouvertes.fr/hal-01907145
, , pp.79-82, 2018.
Hotleakage: A Temperature-Aware Model of Subthreshold and Gate Leakage for Architects, 2003. ,
Stabilizing CPU frequency and voltage for temperature-aware DVFS in mobile devices, IEEE Trans. Comput, vol.64, pp.286-292, 2015. ,
Experimental Evaluation and Modeling of Thermal Phenomena on Mobile Devices, Proceedings of the IEEE Euromicro Conference on Digital System Design (DSD), pp.306-313, 2015. ,
Microprocessor Aging Analysis and Reliability Modeling Due to Back-End Wearout Mechanisms, IEEE Trans. Very Large Scale Integr. (VLSI) Syst, vol.23, pp.2065-2076, 2015. ,
Evaluation and mitigation of aging effects on a digital on-chip voltage and temperature sensor, Proceedings of the 2015 IEEE 25th International Workshop on Power and Timing Modeling, Optimization and Simulation, pp.111-117, 2015. ,
URL : https://hal.archives-ouvertes.fr/cea-01838141
Reliability-Aware Runtime Power Management for Many-Core Systems in the Dark Silicon Era, IEEE Trans. Very Large Scale Integr. (VLSI) Syst, vol.25, pp.427-440, 2017. ,
WARM: Workload-Aware Reliability Management in Linux/Android, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst, vol.36, pp.1557-1570, 2017. ,
Thermal-aware correlated two-level scheduling of real-time tasks with reduced processor energy on heterogeneous MPSoCs, J. Syst. Archit, vol.82, pp.1-11, 2018. ,
Therminator: A Thermal Simulator for Smartphones Producing Accurate Chip and Skin Temperature Maps, Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), pp.117-122, 2014. ,
ThermTap: An online power analyzer and thermal simulator for Android devices, Proceedings of the IEEE International Symposium on Low Power Electronics and Design, pp.341-346, 2015. ,
A Survey of Fault Diagnosis and Fault-Tolerant Techniques Part I: Fault Diagnosis, IEEE Trans. Ind. Electron, vol.62, pp.3768-3774, 2015. ,
A survey of fault diagnosis and fault-tolerant techniques-part II: Fault diagnosis with knowledge-based and hybrid/active approaches, IEEE Trans. Ind. Electron, vol.62, pp.3768-3774, 2015. ,
Testing and built-in self-test-A survey, J. Syst. Archit, vol.46, pp.721-747, 2000. ,
Signal Flow Graphs: A Novel Approach for System Testability Analysis and Fault Diagnosis, IEEE Aerosp. Electron. Syst. Mag, vol.10, pp.14-25, 1995. ,
Maintaining diagnostic truth with information flow models, Proceedings of the IEEE Conference Record. AUTOTESTCON '96, pp.447-454, 1996. ,
Optimum Sensor Localization/Selection in A Diagnostic/Prognostic Architecture, 2005. ,
Method of diagnostic tree design for system-level faults based on dependency matrix and fault tree, Proceedings of the 2011 IEEE 18th International Conference on Industrial Engineering and Engineering Management, IE and EM, pp.3-5, 2011. ,
, , pp.1113-1117
An analytical model of electronic fault diagnosis on extension of the dependency theory, Reliab. Eng. I Syst. Saf, vol.133, pp.192-202, 2015. ,
Architectures for online error detection and recovery in multicore processors, Proceedings of the 2011 Design, pp.1-6, 2011. ,
Configurable isolation: Building high availability systems with commodity multi-core processors, ACM Sigarch, vol.35, pp.470-481, 2007. ,
Utilizing dynamically coupled cores to form a resilient chip multiprocessor, Proceedings of the IEEE International Conference on Dependable Systems and Networks, pp.317-326, 2007. ,
Ultra low-cost defect protection for microprocessor pipelines, Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems-ASPLOS-XII, pp.21-25, 2006. ,
, , vol.41, p.73, 2006.
DIVA: A reliable substrate for deep submicron microarchitecture design, Proceedings of theMICRO-32. Proceedings of the 32nd Annual ACM/IEEE International Symposium on Microarchitecture, pp.196-207, 1999. ,
Argus: Low-Cost, Comprehensive Error Detection in Simple Cores, Proceedings of the 40th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO 2007), pp.210-222, 2007. ,
Symptom-based soft error detection in microprocessors, IEEE Trans. Dependable Secur. Comput, vol.3, pp.188-201, 2006. ,
Understanding the Propagation of Hard Errors to Software and Implications for Resilient System Design, SIGOPS Oper. Syst. Rev, vol.42, pp.265-276, 2008. ,
Early prediction of reliability and availability of combined hardware-software systems based on functional failures, J. Syst. Archit, vol.92, pp.23-38, 2019. ,
On-Chip Fault Monitoring Using Self-Reconfiguring IEEE 1687 Networks, IEEE Trans. Comput, vol.67, pp.237-251, 2018. ,
Fault and timing analysis in critical multi-core systems: A survey with an avionics perspective, J. Syst. Archit, vol.87, pp.1-11, 2018. ,
CPU Utilization Is Wrong, 2020. ,
Understanding Processor Utilization on POWER Systems-AIX, 2020. ,
Trepn Power Profiler-FAQs-Qualcomm Developer Network, 2020. ,
Enabling Energy Optimizations in GPGPUs, ACM SIGARCH Comput. Archit. News, vol.41, pp.487-498, 2013. ,
An integrated GPU power and performance model, Proceedings of the 37th Annual International Symposium on Computer Architecture-ISCA '10, vol.38, p.280, 2010. ,
Samsung Opensource Release Center, 2020. ,
, Samsung Inc. Samsung Galaxy
, Samsung Inc: Seoul, 2014.
, Arm Holdings. Technologies|big.LITTLE-Arm Developer; Arm Holdings, 2018.
, ARM Holdings ARM Cortex-A9; ARM Holdings, 2007.
CPU Frequency and Voltage Scaling Code in the Linux(TM) Kernel, 2015. ,
A Computing Profiling Procedure for Mobile Developers to Estimate Energy Cost, Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems-MSWiM '15, pp.301-305, 2015. ,
Real time identification and control of dynamic systems, Artif. Intell. Rev, vol.30, pp.1-17, 2009. ,
Calibrating parameters and formulas for process-level energy consumption profiling in smartphones, J. Netw. Comput. Appl, vol.44, pp.106-119, 2014. ,
Modelling and prediction of machining errors using ARMAX and NARMAX structures, Appl. Math. Model, vol.27, pp.611-627, 2003. ,
Remaining useful life estimation without needing for prior knowledge of the degradation features, IET Sci. Meas. I Technol, vol.11, pp.1071-1078, 2017. ,
Modelling and robust FDI of steam generator using uncertain bond graph model, J. Process. Control, vol.19, pp.149-162, 2009. ,
URL : https://hal.archives-ouvertes.fr/hal-00758142
Fault detection with model parameter structured uncertainties, Proceedings of the 5th European Control Conference, ECC'99, 1999. ,
URL : https://hal.archives-ouvertes.fr/hal-00291696
Lluís de la Rosa, J. A Survey on interval model simulators and their properties related to fault detection, Annu. Rev. Control, vol.24, pp.31-39, 2000. ,
Fast and Robust Fault Diagnosis for a Class of Nonlinear Systems: Detectability Analysis, 2004. ,
Fault detection of backlash phenomenon in mechatronic system with parameter uncertainties using bond graph approach, Proceedings of the 2006 IEEE International Conference on Mechatronics and Automation, ICMA, pp.600-605, 2006. ,
On-board Component Fault Detection and Isolation Using the Statistical Local Approach, Automatica, vol.34, pp.1391-1415, 1998. ,
URL : https://hal.archives-ouvertes.fr/inria-00073437
A Fast Leak Locating Method Based on Wavelet Transform, Tsinghua Sci. Technol, vol.14, pp.70116-70122, 2009. ,
Empirical mode decomposition applied to fluid leak detection and isolation in process engineering, Proceedings of the 18th Mediterranean Conference on Control and Automation, MED'10, pp.1537-1542, 2010. ,
URL : https://hal.archives-ouvertes.fr/hal-00758664
Scheduling non-preemptive tasks with strict periods in multi-core real-time systems, J. Syst. Archit, vol.90, pp.72-84, 2018. ,
PCMark for Android Benchmark, vol.UL, 2019. ,
, , 2018.
AnTuTu Benchmark, 2019. ,
, Primate Labs Inc. Geekbench, vol.4, 2019.
Prototyping of a Data-Driven Monitoring of Systems on Chip for Multifunction Modular Cockpit Display (MMCD) Project, 2020. ,
URL : https://hal.archives-ouvertes.fr/hal-02293986
, This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, Licensee MDPI