Dynamic QoE/QoS-Aware Queuing for Heterogeneous Traffic in Smart Home

Abstract

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. INDEX TERMS Quality of service, quality of experience, smart home, traffic scheduling optimization.

Quality of Service- and Fairness-Aware Resource Allocation Techniques for IEEE802.11ac WLAN

“…PSNR = 20 log 10 MAX Bit rate √ µ exp − µ current (9) where MAX Bit rate , µ exp and µ current are the maximum transmitted bit rates, expected throughput, and current achieved throughput of a video flow, respectively. The instantaneous video frame delay distribution of the Fixed − TXOP and EAS algorithms are presented: in Figure 18.…”

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