Dynamic QoE/QoS-Aware Queuing for Heterogeneous Traffic in Smart Home
Smart home gateways have to forward multi-sourced network traffic generated with different distributions and with different quality-of-service (QoS) requirements. The state-of-the-art QoS-aware scheduling methods consider only the conventional priority metrics based on the IP type of service (ToS) f...
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description | Smart home gateways have to forward multi-sourced network traffic generated with different distributions and with different quality-of-service (QoS) requirements. The state-of-the-art QoS-aware scheduling methods consider only the conventional priority metrics based on the IP type of service (ToS) field to make a decision for bandwidth allocation. Such priority-based scheduling methods are not optimal to provide both QoS and quality of experience (QoE), since higher priority traffic may not require lower delay than lower priority traffic (for example, traffic generated from medical sensors has a higher priority than traffic from streaming devices, but the latter one requires lower maximum delay). To solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in the smart home network (QP-SH) to make dynamic QoS-aware scheduling decisions meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric that combines the ToS field and the maximum number of packets that can be processed by the system' s service during the maximum required delay is defined. Our experiments show that the proposed solution increases 15% of packets that meet their priorities and 40% of packets that meet their maximum delays as well as 25% of the total number of packets in the system. |
doi_str_mv | 10.1109/ACCESS.2019.2914658 |
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The state-of-the-art QoS-aware scheduling methods consider only the conventional priority metrics based on the IP type of service (ToS) field to make a decision for bandwidth allocation. Such priority-based scheduling methods are not optimal to provide both QoS and quality of experience (QoE), since higher priority traffic may not require lower delay than lower priority traffic (for example, traffic generated from medical sensors has a higher priority than traffic from streaming devices, but the latter one requires lower maximum delay). To solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in the smart home network (QP-SH) to make dynamic QoS-aware scheduling decisions meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric that combines the ToS field and the maximum number of packets that can be processed by the system' s service during the maximum required delay is defined. 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A new metric that combines the ToS field and the maximum number of packets that can be processed by the system' s service during the maximum required delay is defined. 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A new metric that combines the ToS field and the maximum number of packets that can be processed by the system' s service during the maximum required delay is defined. Our experiments show that the proposed solution increases 15% of packets that meet their priorities and 40% of packets that meet their maximum delays as well as 25% of the total number of packets in the system.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2019.2914658</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-5527-2922</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Communications traffic Computer networks Delays Gateways Priority scheduling Quality of experience Quality of service Quality of service architectures Scheduling Smart buildings smart home Smart homes Streaming media Traffic delay Traffic flow Traffic models traffic scheduling optimization Wireless networks |
title | Dynamic QoE/QoS-Aware Queuing for Heterogeneous Traffic in Smart Home |
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