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Publikasjoner (10 av 37) Visa alla publikasjoner
Zhang, Y.-W., Ma, J.-P., Zheng, H. & Gu, Z. (2024). Criticality-aware EDF scheduling for constrained-deadline imprecise mixed-criticality systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 43(2), 480-491
Åpne denne publikasjonen i ny fane eller vindu >>Criticality-aware EDF scheduling for constrained-deadline imprecise mixed-criticality systems
2024 (engelsk)Inngår i: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151, Vol. 43, nr 2, s. 480-491Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

EDF-VD first focuses on the classic mixed-criticality task model in which all low criticality (LO) tasks are abandoned in the high criticality mode, which is an effective dynamic priority scheduling algorithm for mixed-criticality systems. However, it has low schedulability for the imprecise mixed-criticality (IMC) task model with constrained-deadlines, in which LO tasks are provided graceful degradation services instead of being abandoned. In this paper, we study how to improve schedulability for the IMC tasks model. First, we propose a novel criticality-aware EDF scheduling algorithm (CA-EDF) that tries to delay the LO task execution to improve schedulability. Second, we derive sufficient conditions of schedulability for CA-EDF based on the Demand Bound Function. Finally, we evaluate CA-EDF through extensive simulation. The experimental results indicate that CA-EDF can improve the schedulability ratio by about 13.10% compared to the existing algorithms.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2024
Emneord
Computational modeling, demand bound function, graceful degradation, imprecise mixed-criticality, Industries, Job shop scheduling, Program processors, real-time scheduling, Scheduling algorithms, Switches, Task analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-219518 (URN)10.1109/TCAD.2023.3318512 (DOI)2-s2.0-85181578343 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Tilgjengelig fra: 2024-01-22 Laget: 2024-01-22 Sist oppdatert: 2024-01-22bibliografisk kontrollert
Zhang, Y.-W., Zheng, H. & Gu, Z. (2024). EDF-based energy-efficient semi-clairvoyant scheduling with graceful degradation. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 43(2), 468-479
Åpne denne publikasjonen i ny fane eller vindu >>EDF-based energy-efficient semi-clairvoyant scheduling with graceful degradation
2024 (engelsk)Inngår i: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151, Vol. 43, nr 2, s. 468-479Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Recent works introduce a semi-clairvoyant model, in which the system mode transition is revealed on the arrival of high criticality jobs. To solve the problem of inconsistency between the correctness criterion for mixed-criticality systems (MCS) with a semi-clairvoyant and the actual situation, we study the problem of schedulability and energy in MCS with the semi-clairvoyant model in this paper. First, we propose a new correctness criterion for MCS with semi-clairvoyant and graceful degradation and develop the schedulability test based on Demand Bound Function methods denoted as SCS-GD. Second, we propose an energy-efficient semi-clairvoyant scheduling algorithm based on SCS-GD denoted as EE-SCS-GD. Finally, we conduct an experimental evaluation of SCS-GD and EE-SCS-GD by synthetically generated task sets. The experimental results show that SCS-GD can improve the schedulability ratio by 5.98% compared to existing algorithms while EE-SCS-GD can save 56.17% energy compared to SCS-GD.

sted, utgiver, år, opplag, sider
IEEE, 2024
Emneord
Degradation, DVFS, Dynamic scheduling, Energy consumption, Energy efficiency, energy management, graceful degradation, mixed-criticality, Scheduling algorithms, semi-clairvoyant, Switches, Task analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-216110 (URN)10.1109/TCAD.2023.3321970 (DOI)001166816300016 ()2-s2.0-85174801429 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Tilgjengelig fra: 2023-11-14 Laget: 2023-11-14 Sist oppdatert: 2024-04-26bibliografisk kontrollert
Niu, L., Rawat, D. B., Musselwhite, J., Gu, Z. & Deng, Q. (2024). Energy-constrained scheduling for weakly hard real-time systems using standby-sparing. ACM Transactions on Design Automation of Electronic Systems, 29(2), Article ID 29.
Åpne denne publikasjonen i ny fane eller vindu >>Energy-constrained scheduling for weakly hard real-time systems using standby-sparing
Vise andre…
2024 (engelsk)Inngår i: ACM Transactions on Design Automation of Electronic Systems, ISSN 1084-4309, E-ISSN 1557-7309, Vol. 29, nr 2, artikkel-id 29Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

For real-time embedded systems, QoS (Quality of Service), fault tolerance, and energy budget constraint are among the primary design concerns. In this research, we investigate the problem of energy constrained standby-sparing for both periodic and aperiodic tasks in a weakly hard real-time environment. The standby-sparing systems adopt a primary processor and a spare processor to provide fault tolerance for both permanent and transient faults. For such kind of systems, we firstly propose several novel standby-sparing schemes for the periodic tasks which can ensure the system feasibility under tighter energy budget constraint than the traditional ones. Then based on them integrated approachs for both periodic and aperiodic tasks are proposed to minimize the aperiodic response time whilst achieving better energy and QoS performance under the given energy budget constraint. The evaluation results demonstrated that the proposed techniques significantly outperformed the existing state-of-the-art approaches in terms of feasibility and system performance while ensuring QoS and fault tolerance under the given energy budget constraint.

sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM), 2024
Emneord
Energy constraint, fault tolerance, quality of service, real-time scheduling, standby-sparing
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-223744 (URN)10.1145/3631587 (DOI)001193665600006 ()2-s2.0-85190598772 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Tilgjengelig fra: 2024-05-06 Laget: 2024-05-06 Sist oppdatert: 2024-05-06bibliografisk kontrollert
Feng, Z., Wu, C., Deng, Q., Lin, Y., Gao, S. & Gu, Z. (2024). On the scheduling of fault-tolerant time-sensitive networking with IEEE 802.1CB. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Åpne denne publikasjonen i ny fane eller vindu >>On the scheduling of fault-tolerant time-sensitive networking with IEEE 802.1CB
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2024 (engelsk)Inngår i: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151Artikkel i tidsskrift (Fagfellevurdert) Epub ahead of print
Abstract [en]

Time-Sensitive Networking (TSN) has become the most popular technique in modern safety-critical Automotive and Industrial Automation Networks by providing deterministic transmission policies. However, the data of TSN messages may be affected by transient faults. IEEE 802.1CB, a reliability standard in TSN, protects against such faults by providing disjoint redundant routes for each stream. However, the unique assumption may present a new challenge, i.e., an inadequate number of redundant routes that may negatively impact stream scheduling. This paper presents an offline fault-tolerant TSN scheduling approach that considers such impacts for real-time streams (such as Time-Trigger (TT) and Audio Video Bridging (AVB) streams). Specifically, we intend to calculate the minimum upper bound number of disjoint routes required for each stream to meet the reliability requirements, subsequently enhancing the network’s schedulability. We also propose a service degradation function for AVB streams when the network is under heavy load caused by redundant transmissions of TT streams. This function will maintain schedulability and reliability for AVB streams. Experiments with small-and large-scale synthetic networks show the efficiency.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2024
Emneord
Circuit faults, Computer network reliability, Fault tolerance, Fault tolerant systems, Fault-Tolerant Scheduling, Job shop scheduling, Number of Redundant routes, Reliability, Service Degradation, Time-Sensitive Networking, Time-Triggered Streams, Transient analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-220141 (URN)10.1109/TCAD.2024.3352925 (DOI)2-s2.0-85182925116 (Scopus ID)
Forskningsfinansiär
Swedish Research Council, 2023-04485
Tilgjengelig fra: 2024-02-13 Laget: 2024-02-13 Sist oppdatert: 2024-02-13
Jiang, Z., Dai, X., Burns, A., Audsley, N., Gu, Z. & Gray, I. (2023). A high-resilience imprecise computing architecture for mixed-criticality systems. IEEE Transactions on Computers, 72(1), 29-42
Åpne denne publikasjonen i ny fane eller vindu >>A high-resilience imprecise computing architecture for mixed-criticality systems
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2023 (engelsk)Inngår i: IEEE Transactions on Computers, ISSN 0018-9340, E-ISSN 1557-9956, Vol. 72, nr 1, s. 29-42Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Conventional mixed-criticality systems (MCS)s are designed to terminate the execution of less critical tasks in exceptional situations so that the timing properties of more critical tasks can be preserved. Such a strategy can be controversial and has proven difficult to implement in practice, as it can lead to hazards and reduced functionality due to the absence of the discarded tasks. To mitigate this issue, the imprecise mixed-critically system model (IMCS) has been proposed. In such a model, instead of completely dropping less-critical tasks, these tasks are executed as much as possible through the use of decreased computation precision. Although IMCS could effectively improve the survivability of the less-critical tasks, it also introduces three key drawbacks - run-time computation errors, real-time performance degradation, and lack of flexibility. In this paper, we present a novel IMCS framework, which can (i) mitigate the computation errors caused by imprecise computation; (ii) achieve real-time performance near to that of a conventional MCS; (iii) enhance system-level throughput; and (iv) provide flexibility for run-time configuration. We describe the design details of HIART-MCS, and then present the corresponding theoretical analysis and optimisation method for its run-time configuration. Finally, HIART-MCS is evaluated against other MCS frameworks using a variety of experimental metrics.

sted, utgiver, år, opplag, sider
IEEE, 2023
Emneord
Clocks, Computational modeling, Hardware, Hardware/Software Co-design, Imprecise Computing, Real-Time Mixed-Criticality Systems, Registers, Schedulability Analysis, Software, Task analysis, Timing
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-199468 (URN)10.1109/TC.2022.3202721 (DOI)000899952600004 ()2-s2.0-85137584727 (Scopus ID)
Tilgjengelig fra: 2022-09-26 Laget: 2022-09-26 Sist oppdatert: 2023-09-05bibliografisk kontrollert
Saremi, A., Ramkumar, B., Ghaffari, G. & Gu, Z. (2023). An acoustic echo canceller optimized for hands-free speech telecommunication in large vehicle cabins. EURASIP Journal on Audio, Speech, and Music Processing, 2023(1), Article ID 39.
Åpne denne publikasjonen i ny fane eller vindu >>An acoustic echo canceller optimized for hands-free speech telecommunication in large vehicle cabins
2023 (engelsk)Inngår i: EURASIP Journal on Audio, Speech, and Music Processing, ISSN 1687-4714, E-ISSN 1687-4722, Vol. 2023, nr 1, artikkel-id 39Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Acoustic echo cancelation (AEC) is a system identification problem that has been addressed by various techniques and most commonly by normalized least mean square (NLMS) adaptive algorithms. However, performing a successful AEC in large commercial vehicles has proved complicated due to the size and challenging variations in the acoustic characteristics of their cabins. Here, we present a wideband fully linear time domain NLMS algorithm for AEC that is enhanced by a statistical double-talk detector (DTD) and a voice activity detector (VAD). The proposed solution was tested in four main Volvo truck models, with various cabin geometries, using standard Swedish hearing-in-noise (HINT) sentences in the presence and absence of engine noise. The results show that the proposed solution achieves a high echo return loss enhancement (ERLE) of at least 25 dB with a fast convergence time, fulfilling ITU G.168 requirements. The presented solution was particularly developed to provide a practical compromise between accuracy and computational cost to allow its real-time implementation on commercial digital signal processors (DSPs). A real-time implementation of the solution was coded in C on an ARM Cortex M-7 DSP. The algorithmic latency was measured at less than 26 ms for processing each 50-ms buffer indicating the computational feasibility of the proposed solution for real-time implementation on common DSPs and embedded systems with limited computational and memory resources. MATLAB source codes and related audio files are made available online for reference and further development.

sted, utgiver, år, opplag, sider
Springer, 2023
Emneord
Acoustic echo cancelation, Adaptive filters, Automotive speech processing, Automotive voice assistant, Hands-free telephony, Keyword spotting, NLMS, Speech signal enhancement
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-215398 (URN)10.1186/s13636-023-00305-7 (DOI)2-s2.0-85173557384 (Scopus ID)
Tilgjengelig fra: 2023-10-27 Laget: 2023-10-27 Sist oppdatert: 2023-10-27bibliografisk kontrollert
Yin, L., Sun, J., Zhou, J., Gu, Z. & Li, K. (2023). ECFA: an efficient convergent firefly algorithm for solving task scheduling problems in cloud-edge computing. IEEE Transactions on Services Computing, 1-14
Åpne denne publikasjonen i ny fane eller vindu >>ECFA: an efficient convergent firefly algorithm for solving task scheduling problems in cloud-edge computing
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2023 (engelsk)Inngår i: IEEE Transactions on Services Computing, E-ISSN 1939-1374, s. 1-14Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

In cloud-edge computing paradigms, the integration of edge servers and task offloading mechanisms has posed new challenges to developing task scheduling strategies. This paper proposes an efficient convergent firefly algorithm (ECFA) for scheduling security-critical tasks onto edge servers and the cloud datacenter. The proposed ECFA uses a probability-based mapping operator to convert an individual firefly into a scheduling solution, in order to associate the firefly space with the solution space. Distinct from the standard FA, ECFA employs a low-complexity position update strategy to enhance computational efficiency in solution exploration. In addition, we provide a rigorous theoretical analysis to justify that ECFA owns the capability of converging to the global best individual in the firefly space. Furthermore, we introduce the concept of boundary traps for analyzing firefly movement trajectories, and investigate whether ECFA would fall into boundary traps during the evolutionary procedure under different parameter settings. We create various testing instances to evaluate the performance of ECFA in solving the cloud-edge scheduling problem, demonstrating its superiority over FA-based and other competing metaheuristics. Evaluation results also validate that the parameter range derived from the theoretical analysis can prevent our algorithm from falling into boundary traps.

sted, utgiver, år, opplag, sider
IEEE, 2023
Emneord
Cloud computing, cloud-edge computing, Convergence, convergence proof, firefly algorithm, Processor scheduling, Scheduling, Servers, Task analysis, task scheduling, Trajectory, trajectory analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-212325 (URN)10.1109/TSC.2023.3293048 (DOI)2-s2.0-85164678733 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Tilgjengelig fra: 2023-07-25 Laget: 2023-07-25 Sist oppdatert: 2024-04-26bibliografisk kontrollert
Wu, Y., Zhang, L., Gu, Z., Lu, H. & Wan, S. (2023). Edge-AI-driven framework with efficient mobile network design for facial expression recognition. ACM Transactions on Embedded Computing Systems, 22(3), Article ID 57.
Åpne denne publikasjonen i ny fane eller vindu >>Edge-AI-driven framework with efficient mobile network design for facial expression recognition
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2023 (engelsk)Inngår i: ACM Transactions on Embedded Computing Systems, ISSN 1539-9087, E-ISSN 1558-3465, Vol. 22, nr 3, artikkel-id 57Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

Facial Expression Recognition (FER) in the wild poses significant challenges due to realistic occlusions, illumination, scale, and head pose variations of the facial images. In this article, we propose an Edge-AI-driven framework for FER. On the algorithms aspect, we propose two attention modules, Arbitrary-oriented Spatial Pooling (ASP) and Scalable Frequency Pooling (SFP), for effective feature extraction to improve classification accuracy. On the systems aspect, we propose an edge-cloud joint inference architecture for FER to achieve low-latency inference, consisting of a lightweight backbone network running on the edge device, and two optional attention modules partially offloaded to the cloud. Performance evaluation demonstrates that our approach achieves a good balance between classification accuracy and inference latency.

sted, utgiver, år, opplag, sider
Association for Computing Machinery (ACM), 2023
Emneord
cloud offloading, Deep learning, edge computing, Facial Expression Recognition
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-212242 (URN)10.1145/3587038 (DOI)2-s2.0-85164280960 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Tilgjengelig fra: 2023-07-20 Laget: 2023-07-20 Sist oppdatert: 2023-07-20bibliografisk kontrollert
Luan, S., Gu, Z. & Wan, S. (2023). Efficient performance prediction of end-to-end autonomous driving under continuous distribution shifts based on anomaly detection. Journal of Signal Processing Systems, 95(12), 1455-1468
Åpne denne publikasjonen i ny fane eller vindu >>Efficient performance prediction of end-to-end autonomous driving under continuous distribution shifts based on anomaly detection
2023 (engelsk)Inngår i: Journal of Signal Processing Systems, ISSN 1939-8018, E-ISSN 1939-8115, Vol. 95, nr 12, s. 1455-1468Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

A Deep Neural Network (DNN)’s prediction may be unreliable outside of its training distribution despite high levels of accuracy obtained during model training. The DNN may experience different degrees of accuracy degradation for different levels of distribution shifts, hence it is important to predict its performance (accuracy) under distribution shifts. In this paper, we consider the end-to-end approach to autonomous driving of using a DNN to map from an input image to the control action such as the steering angle. For each input image with possible perturbations that cause distribution shifts, we design a Performance Prediction Module to compute its anomaly score, and use it to predict the DNN’s expected prediction error, i.e., its expected deviation from the ground truth (optimal) control action, which is not available after deployment. If the expected prediction error is too large, then the DNN’s prediction may no longer be trusted, and remedial actions should be taken to ensure safety. We consider different methods for computing the anomaly score for the input image, including using the reconstruction error of an Autoencoder, or applying an Anomaly Detection algorithm to a hidden layer of the DNN. We present performance evaluation of the different methods in terms of both prediction accuracy and execution time on different hardware platforms, in order to provide a useful reference for the designer to choose among the different methods.

sted, utgiver, år, opplag, sider
Springer, 2023
Emneord
Machine learning, Deep learning, Distribution shifts, Performance prediction, End-to-end autonomous driving
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-214350 (URN)10.1007/s11265-023-01893-5 (DOI)2-s2.0-85177063760 (Scopus ID)
Forskningsfinansiär
The Kempe Foundations
Merknad

Originally included in thesis in manuscript form. 

Tilgjengelig fra: 2023-09-12 Laget: 2023-09-12 Sist oppdatert: 2024-04-29bibliografisk kontrollert
Zhang, Y.-W., Chen, R.-K. & Gu, Z. (2023). Energy-Aware Partitioned Scheduling of Imprecise Mixed-Criticality Systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 1-1
Åpne denne publikasjonen i ny fane eller vindu >>Energy-Aware Partitioned Scheduling of Imprecise Mixed-Criticality Systems
2023 (engelsk)Inngår i: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, ISSN 0278-0070, E-ISSN 1937-4151, s. 1-1Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We consider partitioned scheduling of an Imprecise Mixed-Criticality (IMC) taskset on a uniform multiprocessor platform, with Earliest Deadline First-Virtual Deadline (EDF-VD) as the uniprocessor task scheduling algorithm, and address the optimization problem of finding a feasible task-to-processor assignment and low-criticality (LO) mode processor speed with the objective of minimizing the system’s average energy consumption in LO mode. We propose a task-to-processor assignment algorithm Criticality-Unaware Worst-Fit Decreasing (CU-WFD) algorithm, which allocates tasks with the Worst-Fit Decreasing (WFD) heuristic method based on utilization values at their respective criticality levels. We determine the energy-efficient speed for each processor based on EDF-VD scheduling, and present our algorithm Energy-Efficient Partitioned Scheduling for Imprecise Mixed-Criticality (EEPSIMC) with the CU-WFD heuristic algorithm to minimize system energy consumption. The experimental results show that our proposed algorithm has good performance in terms both schedulability ratio and normalized energy consumption compared to seven comparison baselines.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2023
Emneord
EDF-VD, Energy consumption, Energy efficiency, energy-aware scheduling, Heuristic algorithms, Imprecise mixed-criticality, Job shop scheduling, multiprocessor, partitioned scheduling, Partitioning algorithms, Switches, Task analysis
HSV kategori
Identifikatorer
urn:nbn:se:umu:diva-213599 (URN)10.1109/TCAD.2023.3246926 (DOI)2-s2.0-85149061429 (Scopus ID)
Tilgjengelig fra: 2023-08-29 Laget: 2023-08-29 Sist oppdatert: 2023-10-13bibliografisk kontrollert
Organisasjoner
Identifikatorer
ORCID-id: ORCID iD iconorcid.org/0000-0003-4228-2774