Real-time scheduling of massive data in time sensitive networks with a limited number of schedule entries

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

7 Scopus Citations
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Author(s)

  • Xi JIN
  • Changqing XIA
  • Chi XU
  • Dong LI
  • Yue YIN
  • Peng ZENG

Detail(s)

Original languageEnglish
Article number8951090
Pages (from-to)6751-6767
Journal / PublicationIEEE Access
Volume8
Online published7 Jan 2020
Publication statusPublished - 2020
Externally publishedYes

Link(s)

Abstract

Time sensitive networks support deterministic schedules over Ethernet networks. Due to their high determinism, high reliability and high bandwidth, they have been considered as a good choice for the backbone network of industrial internet of things. In industrial applications, the backbone network connects multiple industrial field networks together and has to carry massive real-time packets. However, the off-the-shelf time-sensitive network (TSN) switches can deterministically schedule no more than 1024 real-time flows due to the limited number of schedule table entries. The excess real-time flows have to be delivered by best-effort services because the switch only supports the two scheduling services. The best-effort services can reduce average delay, but cannot guarantee the hard real-time constraints of industrial applications. To make the limited number of schedule table entries support more real-time flows, first, we relax scheduling rules to reduce the requirement for schedule table entries and formulate the process of transmitting packets as a satisfiability modulo theories (SMT) specification. Then, we divide the SMT specification into multiple optimization modulo theories (OMT) specifications so that the execution time of solvers can be reduced to an acceptable range. Second, we propose fast heuristic algorithms that combine schedule tables and packet injection control to eliminate scheduling conflicts. Finally, we conduct extensive evaluations. The evaluation results indicate that, compared to existing algorithms, our proposed algorithm requires only one-twentieth the number of schedule entries to schedule the same flow set.

Research Area(s)

  • Industrial Internet of Things, massive data, real-time scheduling, time sensitive networks

Citation Format(s)

Real-time scheduling of massive data in time sensitive networks with a limited number of schedule entries. / JIN, Xi; XIA, Changqing; GUAN, Nan; XU, Chi; LI, Dong; YIN, Yue; ZENG, Peng.

In: IEEE Access, Vol. 8, 8951090, 2020, p. 6751-6767.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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