Execution-Efficient Response Time Analysis on Global Multiprocessor Platforms

Zhou, Quan; Li, Guohui; Li, Jianjun; Deng, Chenggang

doi:10.1109/tpds.2018.2843763

Cited by 8 publications

(1 citation statement)

References 21 publications

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“…RTA is a typical method for schedulability analysis in systems with the fixed priority (FP) scheduling [1][2] or the earliest deadline first (EDF) scheduling [3][4][5]. Compared with other schedulability analysis methods, RTA has a higher accuracy and can better ensure the high throughput of the system.…”

Section: Introductionmentioning

confidence: 99%

The Execution Efficiency of the Response Time Analysis under Different Task Sequencing Strategies

Ma¹,

Zhou²,

Zhou³

et al. 2022

J. Phys.: Conf. Ser.

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Tasks in real-time systems have strict time requirements and need to be completed before their deadlines. Whenever the real-time task set changes, the real-time system reruns the schedulability analysis method to determine whether the tasks in the new task set can be completed before their deadlines. Since new tasks can not be executed until the execution of the schedulability analysis method is completed, the execution efficiency of the schedulability analysis method directly affects the actual performance of the real-time system. Response time analysis (RTA) is a typical method for schedulability analysis. It calculates the response times of tasks and tests the schedulability of tasks by comparing the calculation results and the relative deadlines of tasks. We found that the execution efficiency of existing RTAs can be improved by reasonably sorting the calculation order of the tasks. A task sequencing strategy is proposed to improve the execution efficiency of existing RTAs.

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Section: Introductionmentioning

confidence: 99%

The Execution Efficiency of the Response Time Analysis under Different Task Sequencing Strategies

Ma¹,

Zhou²,

Zhou³

et al. 2022

J. Phys.: Conf. Ser.

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Performance comparison of partitioned and global approaches for weakly hard real-time systems

Ismail

Jawawi

Ahmedy

et al. 2020

IOP Conf. Ser.: Mater. Sci. Eng.

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One way to minimizing resource requirements is through the careful management and allocation, in example, scheduling. Research on weakly hard real-time scheduling on multiprocessor has been extremely limited; most prior research on real-time scheduling on weakly hard real-time has been confined to uniprocessors. The need for multiprocessor is due to issues that impose limits on the performance of a single processor. As real-time application systems increasingly come to be implemented upon multiprocessor environments, thus, this study applies multiprocessor scheduling approach for verification of weakly hard real-time tasks and to guaranteeing the timing requirements of the tasks. In fact, within the multiprocessor, the task allocation and migration problems seem even harder than in uniprocessor case; thus, in order to cater that problem, the sufficient and efficient scheduling algorithm supported by accurate schedulability analysis technique is present to provide weakly hard real-time guarantees. The proposed approach involves the two existing multiprocessor real-time scheduling algorithms combining with the hyperperiod analysis and deadline models; weakly hard constraints and μ-pattern. In this paper, the Matlab simulation tool is used in order to validate the result of analysis. From the experimental and performance evaluation results, it proved that the proposed approach is satisfied the tasks deadlines with less number of misses.

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Fog-Computing-Based Approximate Spatial Keyword Queries With Numeric Attributes in IoV

Zhu

Mao

et al. 2020

IEEE Internet Things J.

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Due to the popularity of on-board geographic devices, a large number of spatial-textual objects are generated in Internet of Vehicles (IoV). This development calls for Approximate Spatial Keyword Queries with numeric Attributes in IoV (A 2 SKIV), which takes into account the locations, textual descriptions, and numeric attributes of spatial-textual objects. Considering huge amounts of objects involved in the query processing, this paper comes up with the ideal of utilizing vehicles as fog-computing resource, and proposes the network structure called FCV, and based on which the fog-based Top-k A 2 SKIV query is explored and formulated. In order to effectively support network distance pruning, textual semantic pruning, and numerical attribute pruning simultaneously, a two-level spatialtextual hybrid index STAG-tree is designed. Based on STAGtree, an efficient Top-k A 2 SKIV query processing algorithm is presented. Simulation results show that, our STAG-based approach is about 1.87x (17.1x, resp.) faster in search time than the compared ILM (DBM, resp.) method, and our approach is scalable.

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Execution-Efficient Response Time Analysis on Global Multiprocessor Platforms

Cited by 8 publications

References 21 publications

The Execution Efficiency of the Response Time Analysis under Different Task Sequencing Strategies

The Execution Efficiency of the Response Time Analysis under Different Task Sequencing Strategies

Performance comparison of partitioned and global approaches for weakly hard real-time systems

Fog-Computing-Based Approximate Spatial Keyword Queries With Numeric Attributes in IoV

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