Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Zhou, Xuan; Huagang, Xiong; He, Feng

doi:10.1016/j.cja.2019.08.027

Cited by 11 publications

(6 citation statements)

References 18 publications

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“…The reference nodes and task relationships were combined together to design the multilevel reference node group mobility (ML-RNGM) model, for better real-time performance guarantee for task and mission and better network connectivity. For the inner real-time performance evaluation of a UAV, literature [34,35] gave general schemas to solve it.…”

Section: Reference Point Group Mobilitymentioning

confidence: 99%

Group Mobility Model for Complex Multimission Cooperation of UAV Swarm

Xiao-yan

Wang

et al. 2022

International Journal of Aerospace Engineering

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In the unmanned aerial vehicle (UAV) swarm combat system, multiple UAVs’ collaborative operations can solve the bottleneck of the limited capability of a single UAV when they carry out complicated missions in complex combat scenarios. As one of the critical technologies of UAV collaborative operation, the mobility model is the basic infrastructure that plays an important role for UAV networking, routing, and task scheduling, especially in high dynamic and real-time scenarios. Focused on real-time guarantee and complex mission cooperative execution, a multilevel reference node mobility model based on the reference node strategy, namely, the ML-RNGM model, is proposed. In this model, the task decomposition and task correlation of UAV cluster execution are realized by using the multilayer task scheduling model. Based on the gravity model of spatial interaction and the correlation between tasks, the reference node selection algorithm is proposed to select the appropriate reference node in the process of node movement. This model can improve the real-time performance of individual tasks and the overall mission group carried out by UAVs. Meanwhile, this model can enhance the connectivity between UAVs when they are performing the same mission group. Finally, OMNeT++ is used to simulate the ML-RNGM model with three experiments, including the different number of nodes and clusters. Within the three experiments, the ML-RNGM model is compared with the random class mobility model, the reference class mobility model, and the associated class mobility model for the network connectivity rate, the average end-to-end delay, and the overhead caused by algorithms. The experimental results show that the ML-RNGM model achieves an obvious improvement in network connectivity and real-time performance for missions and tasks.

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Section: Reference Point Group Mobilitymentioning

confidence: 99%

Group Mobility Model for Complex Multimission Cooperation of UAV Swarm

Xiao-yan

Wang

et al. 2022

International Journal of Aerospace Engineering

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“…Distributed modular electronics (DME), i.e., second-generation integrated modular avionics (IMA), are considered to be the most promising basis for OCNs [3][4][5][6]. DME-based OCNs are distributed computing systems characterised by a large number of computational nodes with large computing power and a wide range of supported aircraft functions.…”

Section: Introductionmentioning

confidence: 99%

A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems

et al. 2022

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The paper proposes a method for implementing a universal neural network processor with hysteresis dynamics. This processor allows a wide range of heterogeneous tasks in real time to be performed without reprogramming and changing their internal structure. Adding hysteresis behavior to the system makes it possible to increase resistance to external influences, the complexity as well as non-linearity of intelligent output. The paper discusses the use of this processor as part of an on-board intelligent avionics system.

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“…Currently, avionics technology is further evolving towards a new IMA system-Distributed Integrated Modular Avionics (DIMA) [3]. IMA reconfiguration, the significant technology of the next-generation DIMA system, not only effectively reduces hardware redundancy, but also greatly strengthens the system flexibility and the ability to cope with different missions and resource failures [4,5]. The safety requirements of the IMA reconfiguration are significant to ensure the flight safety and proper mission execution.…”

Section: Introductionmentioning

confidence: 99%

Safety Assessment of the Reconfigurable Integrated Modular Avionics Based on STPA

Zhao

Dong

Li³

et al. 2021

International Journal of Aerospace Engineering

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The reconfiguration technology, which is the significant feature of the newly designed Integrated Modular Avionics (IMA) system, enables the transfer of avionics functions from the failed module to the residual normal module, thereby enhancing the robustness of the whole system. The basic target of the IMA reconfiguration is to ensure the safe flight and correct execution of the mission. To solve the problem of lack of effective management mechanism for the IMA system development and safety assessment, a safety analysis method based on STAMP/STPA and UPPAAL for IMA reconfiguration is proposed. The method focuses mainly on system characteristics and multiparty interactions. On the basis of this approach, some studies and analyses have been carried out. Firstly, the STAMP/STPA principle is studied and used to identify unsafe control actions in the reconfiguration process. Secondly, a formal model of IMA reconfiguration is developed using UPPAAL. Finally, the accessibility analysis of the formal model is used to analyze UCAs and the corresponding loss scenarios. The method enables a detailed description of the interactions between the components and a rigorous mathematical analysis of the system, thereby diluting the effect of human factors while ensuring the accuracy and reliability of the safety constraints.

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Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Cited by 11 publications

References 18 publications

Group Mobility Model for Complex Multimission Cooperation of UAV Swarm

Group Mobility Model for Complex Multimission Cooperation of UAV Swarm

A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems

Safety Assessment of the Reconfigurable Integrated Modular Avionics Based on STPA

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