A Scheduling Method Based on Packet Combination to Improve End-to-End Delay in TSCH Networks with Constrained Latency

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.

[1]  Maryam Esmaeili,et al.  Optimal energy aware clustering in circular wireless sensor networks , 2017, Ad Hoc Networks.

[2]  Youlong Luo,et al.  Clustering routing based on mixed integer programming for heterogeneous wireless sensor networks , 2018, Ad Hoc Networks.

[3]  Hyunseung Choo,et al.  A Distributed Delay-Efficient Data Aggregation Scheduling for Duty-Cycled WSNs , 2017, IEEE Sensors Journal.

[4]  Hoon Oh,et al.  Constructing an optimally balanced tree to maximize data throughput with multiple channels , 2018, Wirel. Networks.

[5]  Yosuke Ishii Exploiting Backbone Routing Redundancy in Industrial Wireless Systems , 2009, IEEE Transactions on Industrial Electronics.

[6]  Adnan Aijaz,et al.  DeAMON: A Decentralized Adaptive Multi-Hop Scheduling Protocol for 6TiSCH Wireless Networks , 2017, IEEE Sensors Journal.

[7]  Hoon Oh,et al.  A Receiver for Resource-Constrained Wireless Sensor Devices to Remove the Effect of Multipath Fading , 2018, IEEE Transactions on Industrial Electronics.

[8]  Hoon Oh,et al.  SCSMA: A Smart CSMA/CA Using Blind Learning for Wireless Sensor Networks , 2020, IEEE Transactions on Industrial Electronics.

[9]  Arshad Jhumka,et al.  Many-to-many data aggregation scheduling in wireless sensor networks with two sinks , 2017, Comput. Networks.

[10]  Cheng Pan,et al.  A time efficient aggregation convergecast scheduling algorithm for wireless sensor networks , 2016, Wirel. Networks.

[11]  Sushma Jain,et al.  DAHDA: Dynamic Adaptive Hierarchical Data Aggregation for Clustered Wireless Sensor Networks , 2017, Wirel. Pers. Commun..