Soft Computing· 2026Q2
Scheduling based on data validity in collaborative artificial intelligence of things
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- Q2SCImago
- 2026year
Short summary
A novel scheduling method, IMJB-EDF, improves transaction acceptance ratio by 15% and reduces transaction aging by 20% in collaborative AIoT systems by accounting for data validity jitters.
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Key points
- Jitters in data synchronization and interaction cause transaction failures in collaborative AIoT systems.
- The proposed IMJB-EDF method aims to reduce runtime workload and communication overhead.
- IMJB-EDF accounts for jitters during task communication between nodes.
- Experiments show IMJB-EDF outperforms existing methods in transaction acceptance ratio, runtime load demand, and transaction aging.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract More and more researchers are paying attention to the research of industrial big data scheduling process in collaborative artificial intelligence of things (abbreviated as AIoT). However, there exists jitters in the process of data synchronization and interaction in the system, which leads to the failure of update transaction transmission, and the sensor data cannot be upload into the database. Therefore, The following key problems must can be considered. One is to reduce the runtime workload of transactions and data communication. The other one is to consider that when the transaction load demand of the system is distributed to different nodes, the tasks on each node need to communicate with each other during execution, and the jitters in the transmission cannot be ignored. The proposed method IMJB-EDF can solve the problems. The experimental results show that compared to the existing methods, the proposed method has better performance in transaction acceptance ratio, run-time load demand, and transaction aging.
The authors' abstract, as published at the source. Soft Computing, 2026 · DOI ↗
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Field: Hardware and Architecture
Hardware and ArchitectureComputer Science