Service Level Management in Emerging Environments. Nader Mbarek

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Service Level Management in Emerging Environments - Nader Mbarek


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16 Scenario 2 3 3 0 0 9/7 Scenario 3 3 3 3 0 7/6/3 Scenario 4 3 3 3 3 6/5/3/2

      1.6.3.2. Results

      The first simulation scenario corresponds to an IoT service based on 3 RTMC objects. This results in an allocation of the 16 slots to the three objects. The second scenario corresponds to IoT services that require three RTMC objects and three RTNMC objects. Consequently, nine slots are allocated to RTMC objects and seven to RTNMC objects. The third scenario corresponds to nine objects (three RTMC, three RTNMC and three Streaming) resulting in a 7/6/3 type configuration of the slots. The last scenario corresponds to the existence of 12 objects (three of each QoS class). This results in a 6/5/3/2 type configuration of the slots.

      The results illustrated in Figures 1.7 and 1.8 show that QBAIoT offers better average delays than the IEEE 802.15.4 standard to the QoS classes that are sensitive to this parameter, i.e. to the RTMC and RTNMC classes. It must be noted that the delays for packets with QBAIoT (when a unique QoS class exists in the gateway environments) is slightly greater than the standard, but respects the requirements of RTMC traffic. This difference is due to the test carried out on the slots to verify that they belong to the QoS CAP, which is not necessary for the standard traditional approach without QoS.

Graph depicts average real-time mission critical delays for different scenarios.

      Figure 1.7. Average real-time mission critical delays for different scenarios

Graph depicts average real-time non-mission critical for different scenarios.

      Figure 1.8. Average real-time non-mission critical delays for different scenarios

Bar chart depicts packet Delivery Ratio for all QoS classe.

      Figure 1.9. Packet Delivery Ratio for all QoS classe. For a color version of this figure, see www.iste.co.uk/mbarek/service.zip

      Security and privacy are essential in the IoT to gain the trust of users and improve the use of services. IoT services impact different areas of daily life and, as a result, the IoT impacts the privacy of users. It is, therefore, essential to comply with European and international regulations concerning privacy protection and this must be integrated into the services offered in an IoT environment. On the other hand, the QoS is another important component of service level that must be considered when offering IoT services. These services can belong to critical fields such as e-health or security. The prioritizing of flows and differentiation of processing are necessary to comply with the requirements and characteristics of these flows corresponding to various fields and services. Several projects have been carried out to set up QoS in the IoT service offering, but there are several challenges that must still be overcome in order to meet the requirements of the IoT environment. In this context, QBAIoT, an approach to guarantee QoS at the device layer of the IoT architecture, makes it possible to differentiate traffic to meet the requirements of each IoT application. This access method based on the IEEE 802.15.4 standard takes into account four categories of service and makes it possible to obtain good performance with a QoS guarantee.

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