Memetic-based schedule synthesis for communication on time-triggered embedded systems

Heyuan Shi, Kun Tang, Chengbao Liu, Xiaoyu Song, Chao Hu and Jiaguang Sun

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 10, 1550147717738167

Abstract: Time-triggered systems play an important role in industrial embedded systems. The time-triggered network is deployed on the time-triggered network-on-chip implementation. It ensures the safety-critical industrial communication for real-time embedded multiprocessor systems. To guarantee the safety-critical requirements for communication, each message is transmitted by a predefined static schedule. However, synthesizing a feasible schedule is a challenge because both spatial and temporal constraints should be considered. This article presents a novel memetic-based schedule synthesis algorithm to derive a feasible schedule by determining the offset of messages on the time-triggered network-on-chip. Memetic-based schedule synthesis algorithm is based on memetic algorithm, which incorporates local search in the iterations of general genetic algorithm. We compare memetic-based schedule synthesis algorithm with genetic algorithm in different scale of time-triggered network-on-chip and number of messages. The experimental results show that the memetic-based schedule synthesis algorithm is effective to synthesize a feasible schedule, and the failure schedule synthesized by memetic-based schedule synthesis algorithm is only 34.2% in average compared to the conventional genetic algorithm.

Keywords: Real-time systems; time-triggered networks; network-on-chip; scheduling; memetic algorithm (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147717738167 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:10:p:1550147717738167

DOI: 10.1177/1550147717738167

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().