Abstract
Wireless sensor networks (WSN) are networks for gathering data from sensor nodes that have been applied in industry for a long time. In real-time industrial applications with tight latencies, schedulability is one of the most critical issues. Some authors have proposed centralized scheduling algorithms for time-slotted channel hopping (TSCH) networks for real-time applications in industry, however, they have some disadvantages such as schedulability and high data traffic. In this paper, we improve the schedulability, latency, data traffic by dynamically prioritizing packets which are based on number duplex-conflicts and dynamically combining the packets. As a result, we show that the packet-combining algorithm improves schedulability and minimizes the amount of traffic in a network when compared with existing approaches.
Highlights
Nowadays, a lot of applications are deployed with wireless sensor networks (WSNs)
Our paper proposes a scheduling algorithm that is based on combining packets dynamically and dynamically prioritizing each packet transmission based on its laxity applied to a timeslot channel hopping (TSCH) network with constrained latency to increase schedulability and reduce the number of data transmissions and end-to-end (E2E) delay
A data-aggregation technique is used in gathering data which is collected from sensor nodes in WSNs to reduce energy consumption, reduce the number of transmissions, latency, and energy consumption
Summary
A lot of applications are deployed with wireless sensor networks (WSNs). In these applications, sensor data is transmitted from sensor nodes to a network manager, and especially for real-time applications, sensor nodes have latency requirements. There are some standards for low-power wireless sensor networks which uses IEEE 802.14.5e for the media access control (MAC) protocol and applied in industry such as timeslot channel hopping (TSCH), WirelessHART [3] and ISA100.11 [4]. Scheduling methods can reduce the latency based on eliminating the collisions among the nodes in the network, using parallel transmissions to reduce slot frame size, and using data aggregation to reduce number of transmissions. Our paper proposes a scheduling algorithm that is based on combining packets dynamically and dynamically prioritizing each packet transmission based on its laxity (i.e., the remaining time before the end-to-end deadline) applied to a TSCH network with constrained latency to increase schedulability and reduce the number of data transmissions and end-to-end (E2E) delay.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
