Deterministic Scheduling With Optimization of Average Transmission Delays in Industrial Wireless Sensor Networks

Heng Wang,Yuanjie Zhu,Min Li,Shuai Tan

doi:10.1109/access.2020.2968491

Heng Wang, Yuanjie Zhu + Show 2 more

Open Access

https://doi.org/10.1109/access.2020.2968491

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Abstract

As a key characteristic for industrial wireless sensor networks, deterministic scheduling aims to ensure that real-time data flows arrive at destination devices under deadline constraints by allocating necessary communication resources, such as time slots and channels. Current research on deterministic scheduling mainly focuses on how to obtain a feasible scheduling solution. However, optimizing average transmission delays under deterministic flow deadlines is rarely considered when multiple scheduling solutions exist. To address this issue, in this paper we propose two scheduling algorithms: branch and bound based on link conflict classification, and least conflict degree first. The prior algorithm obtains optimal schedulable ratio by constructing a search tree and adopting necessary conditions of scheduling. The latter algorithm dynamically adjusts the scheduling order of flows to distribute channels in a heuristic manner, and achieves approximate optimal schedulable ratio in a short time with low complexity. Simulation results show that both of the proposed algorithms effectively reduce the average transmission delays of real-time data flows while guaranteeing that all flows are delivered before their deadlines.

Highlights

Industrial 4.0, which is defined in Germany, has received more attention for countries, companies and researchers in recent years
In order to compare the performance of algorithms, we evaluate them from three metrics: (a) Schedulable ratio shows the ability of the algorithms in finding a feasible scheduling solution, (b) Average transmission delays reflect the performance of improving real-time transmission in the Industrial wireless sensor networks (IWSNs), (c) Average execution time represents the average time of an algorithm which successfully schedules different instances in the current network size
When the Least Conflict degree First (LCF) is compared to the C-Least Laxity First (LLF) that the complexity is O T ∗ N 2 ∗ H ∗ D/P [21], its average execution time is better than the C-LLF, where H ∗ D/P > 1, H represents the maximum length among all routes, D is the maximum relative deadline and P is the minimum period for all flows

Summary

Introduction

Industrial 4.0, which is defined in Germany, has received more attention for countries, companies and researchers in recent years. Use laxity to obtain the order of links within a conflict set and the order of inter-conflict sets, the algorithm chooses the effective scheduling subset from all combinations of conflict sets to become the child node for the extended node at this slot.

Results

Conclusion