원문정보
초록
영어
In the paper, we propose a TSCH-based scheduling scheme for IEEE 802.15.4e, which is able to perform the scheduling of its own network by avoiding collision from interference network cluster (INC). Firstly, we model a bipartite graph structure for presenting the slot-frame (channel-slot assignment) of TSCH. Then, based on the bipartite graph edge weight, we utilize the Hungarian assignment algorithm to implement a scheduling scheme. We have employed two features (maximization and minimization) of the Hungarian-based assignment algorithm, which can perform the assignment in terms of minimizing the throughput of INC and maximizing the throughput of own network. Further, in this work, we called the scheme “dual-stage Hungarian-based assignment algorithm”. Furthermore, we also propose deep learning (DL) based deep neural network (DNN) scheme, where the data were generated by the dual-stage Hungarian-based assignment algorithm. The performance of the DNN scheme is evaluated by simulations. The simulation results prove that the proposed DNN scheme provides similar performance to the dual-stage Hungarian-based assignment algorithm while providing a low execution time.
목차
1. Introduction
2. System Model
2.1 Network Model
2.2 Problem Formulation
2.3 Channel Model
3. The Proposed Dual-Stage Hungarian Based Assignment Algorithm
4. The Proposed Deep Learning Based DNN Scheme
5. Performance Evaluation
2.1 Execution of TSCH-Based Scheduling
2.2 Building a DNN Scheme
2.3 Assignment Method: TSCH-Based Scheduling
2.4 Throughput Measurement
2.5 DNN model accuracy
6. Conclusion
Acknowledgement
References