The rapidly increasing number of Internet of Things(IoT)devices and Quality of Service(QoS)requirements have made the provisioning of network solutions to meet this demand a major research topic.Providing fast and rel...The rapidly increasing number of Internet of Things(IoT)devices and Quality of Service(QoS)requirements have made the provisioning of network solutions to meet this demand a major research topic.Providing fast and reliable routing paths based on the QoS requirements of IoT devices is very important task for Industry 4.0.The software-defined network is one of the most current interesting research developments,offering an efficient and effective solution for centralized control and network intelligence.A new SDN-IoT paradigm has been proposed to improve network QoS,taking advantage of SDN architecture in IoT networks.At the present time,most publish-subscribe IoT platforms assume the same QoS requirements for all customers.However,in many real-world scenarios of IoT applications,different subscribers may have different E2E delay requirements.Providing reliable differentiated services has become a relevant problem.For this we developed a technique for classifying IoT flows with the individual subscriber recommendation on the importance of certain parameters for particular classes of traffic taken into account.To improve the QoS for mission-critical IoT applications in large-scale SDN-IoT infrastructure,we focused on optimizing routing in the SDN.For this purpose,a centralized routing model based on QoS parameters and IoT priority flow for the SDN was proposed and implemented.We have compared the proposed routing model with the state-of-art deterministic multiconstrained centralized QoS routing model(DMCQR).The developed centralized routing model in comparison with the known DMCQR flow routing achieved better balance of channel resources load due to rational choice of transmission paths for different traffic.And it was possible to reduce up to 3 times the average delay of real time flows service from end to end,for which with the existing DMCQR routing model the permissible delay rates were not met.展开更多
基金This research was supported by the Ukrainian project No.0120U102201“Development the methods and unified software-hardware means for the deployment of the energy efficient intent-based multi-purpose information and communication networks”and Comenius University in Bratislava,Faculty of Management.
文摘The rapidly increasing number of Internet of Things(IoT)devices and Quality of Service(QoS)requirements have made the provisioning of network solutions to meet this demand a major research topic.Providing fast and reliable routing paths based on the QoS requirements of IoT devices is very important task for Industry 4.0.The software-defined network is one of the most current interesting research developments,offering an efficient and effective solution for centralized control and network intelligence.A new SDN-IoT paradigm has been proposed to improve network QoS,taking advantage of SDN architecture in IoT networks.At the present time,most publish-subscribe IoT platforms assume the same QoS requirements for all customers.However,in many real-world scenarios of IoT applications,different subscribers may have different E2E delay requirements.Providing reliable differentiated services has become a relevant problem.For this we developed a technique for classifying IoT flows with the individual subscriber recommendation on the importance of certain parameters for particular classes of traffic taken into account.To improve the QoS for mission-critical IoT applications in large-scale SDN-IoT infrastructure,we focused on optimizing routing in the SDN.For this purpose,a centralized routing model based on QoS parameters and IoT priority flow for the SDN was proposed and implemented.We have compared the proposed routing model with the state-of-art deterministic multiconstrained centralized QoS routing model(DMCQR).The developed centralized routing model in comparison with the known DMCQR flow routing achieved better balance of channel resources load due to rational choice of transmission paths for different traffic.And it was possible to reduce up to 3 times the average delay of real time flows service from end to end,for which with the existing DMCQR routing model the permissible delay rates were not met.
