Figure 1.6. Variation of the scores of intelligent radio channels for the entertainment service

Figure 1.6 shows the impact of the dynamic network environment (such as the available bandwidth, the channel’s availability probability and the speed of the vehicle) on selecting the channel best adapted to the infotainment service (restaurant reservation). In Figure 1.6, we can observe that with the high mobility of candidate vehicles on the highways, the channel corresponding to the WiFi bandwidth is not a good candidate. We also observe a degradation of the score of the radio channel corresponding to the bandwidth of the LTE and an increase in the score of the channel corresponding to the TV bandwidth. The evolution of the scores over time justifies the decision to carry out a spectrum handoff, from the suggested module to the TVWS channel. Before running the spectrum handoff, we wait for the choice of the best channel to be confirmed for the following period. This will enable us to avoid unhelpful transfers. And to avoid running the spectrum handoff very late, this wait time will be adjusted automatically. In this scenario, we observe that the choice of TVWS is fully adapted to this context, not only in terms of QoS but also from the perspective of mobility. Indeed, this spectral band is characterized by a long range that is best suited to scenarios with high mobility.

1.5. Conclusion

      In this chapter, we tackled the question of decision-making for effective access to a radio network or a spectrum band in the IoT. An IoT object, having several interfaces and/or with cognitive capacities, can detect several access networks or radio communication channels. Thus, it may be led to choose the access network or radio communication channel that best meets the QoS constraints of the IoT application as well as its energy constraints. Selecting the most appropriate network or radio communication channel will allow the object to remain best connected. In this chapter, we focused on the functioning of the multicriteria decision-making module that we have suggested to tackle the problem of scalability. However, many approaches (Lounis et al. 2012; Gia et al. 2015; Guo et al. 2017; Firouzi et al. 2018; Shrestha et al. 2018; Khan and Lee 2019) have been proposed to solve the scalability issues in an IoT system. In our context, this question remains very important. This is why we plan to study it in future work.

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