Mobile data offloading under attractor selection in heterogeneous networks

Wu, Huan; Wen, Xiangming; Lu, Zhaoming; Pan, Qi

doi:10.1109/iswcs.2017.8108103

Cited by 8 publications

(4 citation statements)

References 16 publications

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“…e value of activity A is a measure of the adaptation of the path to the environment. From Equation (35), the solution set includes a solution with high value and many solutions with low value, which correspond to the optimal path and the other paths in the HIoT. e variation of the selection probabilities over the parameter A is shown in Figure 6.…”

Section: Extend Attractor Selectionmentioning

confidence: 99%

“…] and D(A) � A, where parameters a and b are the factors which can be set at a � 5 and b � 2 [35]. Figure 7 depicts the multipath selection process, and it can be seen that the two nodes are connected by many paths.…”

Section: Extend Attractor Selectionmentioning

confidence: 99%

“…However, the node executes the algorithm of scheduling to select the new path under the performance degradation or transmission failure condition which means that the CP is not suitable to transmit the data. at is to say, the environment is not suitable to transmit the data with the decrease of the value of A, and then, the node selects the new optimal transmission path according to Equation (35). In contrast, the node continues to transmit the data by the CP under the high value of A, which means that the system adapts to the environment.…”

Section: Extend Attractor Selectionmentioning

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: Extend Attractor Selectionmentioning

confidence: 99%

Section: Extend Attractor Selectionmentioning

confidence: 99%

Section: Extend Attractor Selectionmentioning

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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“…Power line has obvious advantages in the wider coverage areas, stability and reliability, which are important and cost-effective for users in IoT to coverage the blind areas and hotspots, such as the countryside, mountain area, no-human-zone and commercial hotspots or community hotspots. In our previous work [9], [10], the PLC has been used as a transmission medium to integrate the wireless network (WN) to achieve better capacity, low-cost performances, etc.…”

Section: Introductionmentioning

confidence: 99%

3D Markov chain based multi-priority path selection in the heterogeneous Internet of Things

2019

KSII TIIS

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Internet of Things (IoT) based sensor networks have gained unprecedented popularity in recent years. With the exponential explosion of the objects (sensors and mobiles), the bandwidth and the speed of data transmission are dwarfed by the anticipated emergence of IoT. In this paper, we propose a novel heterogeneous IoT model integrated the power line communication (PLC) and WiFi network to increase the network capacity and cope with the rapid growth of the objects. We firstly propose the mean transmission delay calculation algorithm based the 3D Markov chain according to the multi-priority of the objects. Then, the attractor selection algorithm, which is based on the adaptive behavior of the biological system, is exploited. The combined the 3D Markov chain and the attractor selection model, named MASM, can select the optimal path adaptively in the heterogeneous IoT according to the environment. Furthermore, we verify that the MASM improves the transmission efficiency and reduce the transmission delay effectively. The simulation results show that the MASM is stable to changes in the environment and more applicable for the heterogeneous IoT, compared with the other algorithms.

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Analysis and Research of Dynamic Data Path Selection Algorithm in Heterogeneous Networks

2019

Advances in Intelligent Systems and Computing

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Mobile data offloading under attractor selection in heterogeneous networks

Cited by 8 publications

References 16 publications

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

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

3D Markov chain based multi-priority path selection in the heterogeneous Internet of Things

Analysis and Research of Dynamic Data Path Selection Algorithm in Heterogeneous Networks

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