Markov Chain Based on Path Selection in the Heterogeneous Internet of Things Model

Wu, Huan; Wen, Xiangming; Lu, Zhaoming; Huang, Shuyang

doi:10.1109/icei.2018.00046

Cited by 5 publications

(12 citation statements)

References 15 publications

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“…In this paper, we propose the heterogeneous PLC and WN model for the IoT, which is the extended work based on our previous work [16]. Different from the two-path model in our previous work, the multipath model for the realistic network scenario is proposed.…”

Section: Introductionmentioning

confidence: 99%

“…Different from the two-path model in our previous work, the multipath model for the realistic network scenario is proposed. Based on the multipath model, the transfer probability and the numeric results of the average queuing delay are also different from that under the two-path model in [16]. In addition, the multiuser scenario is investigated.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, the multiuser scenario is investigated. us, the path selection algorithm based on the multipath Markov chain is extended based on the two-path Markov chain in [16]. en, we add the compared algorithms, which are simple additive weighting (SAW) and interference-suppression resource optimization based on potential game (ISRO_PG), in the simulation.…”

Section: Introductionmentioning

confidence: 99%

“…en, we add the compared algorithms, which are simple additive weighting (SAW) and interference-suppression resource optimization based on potential game (ISRO_PG), in the simulation. Furthermore, we add the comparison of the average queuing delay and the ratio of the different algorithms with the number of different nodes, which are not discussed in [16], to verify the performance of the proposed algorithm in the simulation results. e simulation results show that the algorithm in [16] is not suitable for the multipath scenario with the increased data.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, we add the comparison of the average queuing delay and the ratio of the different algorithms with the number of different nodes, which are not discussed in [16], to verify the performance of the proposed algorithm in the simulation results. e simulation results show that the algorithm in [16] is not suitable for the multipath scenario with the increased data. And the proposed algorithm makes the network scalability (the number of nodes can be very high), reliability (the network may report urgent alarm events), and robustness (transmission nodes are likely to be subject to failures for several reasons).…”

Section: Introductionmentioning

confidence: 99%

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Adaptive Multipath Selection-Based Markov Chain in the Heterogeneous Internet of Things

Wen

et al. 2019

Wireless Communications and Mobile Computing

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The Internet of Things (IoT) is a new heterogeneous system integrated by the various end users (sensors and terminals) with different technologies. However, the limiting factor is bandwidth in the IoT due to the exploding end users and the network bandwidth requirements. A novel IoT model, which integrates the power-line carrier (PLC) and the wireless network (WN), is proposed to solve the bandwidth problem from the architecture, especially in the areas lacking network facilities. In addition, we exploit an effective virtual layer (EVL) which allows the different end users to access the system model seamlessly. Then, the attractor selection algorithm based on Markov chain (MASA) is employed to select an optimal path among the PLC or WN. The simulation results demonstrate that the proposed system model has the smaller average queuing delay than other algorithms and makes the model more stable and robust.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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