Background:
- Telephony call becomes an important application in today’s network.
- In the current network, the performance of telephony call is poor. And there are limit work on how internet influence telephony call QoE.
- So authors analyze how internet influence telephony call QoE and then present a relay selection algorithm to improve the QoE of telephony call.
Contribution:
- Analyzing, at scale, the impact of network performance on audio call quality.
- Present VIA, a centralized control system for telephony call. Quantifying the potential benefits of a managed overlay network for improving audio call quality.
- Highlighting the challenges in achieving these benefits and presenting a practical relay selection algorithm that delivers close-to-optimal performance.
In the rest part of this reading note, I describe the work according to these 3 contributions.
Analyzing the impact of network performance on telephony call quality
This paper analyzes 3 network metrics: (i) round-trip time (RTT), (ii) loss rate, and (iii) jitter.
Conclusions:
- These 3 metrics are all important to QoE. Improving any one of them can improve QoE dramatically.
- Wide-area communication, such as international and inter-domain calls, are more prone to bad network performance, and have a large room of improvement.
- Poor QoE happens spatially and temporally.
These conclusions motivate the need for a network overlay (Conclusion 1) that provides better paths with a global footprint of overlay nodes (Conclusion 2), and the need to choose routes selectively and dynamically (Conclusion 3).
Present VIA, a centralized control system for telephony call
Optimal function:
Min \sum Q(c,Assign(c))
C: a pair of clients.
Assign(C): assignment for clients c. Which two relay nodes should be selected to connect these 2 clients. (of course, we can also choose only one, or let 2 client connet directly if they close to each other)
Q(c,Assign(c)): QoE of the assignment for client pair c.
Presenting a practical relay selection algorithm
In this paper, a traditional exploration and predict method is applied.
2 challenges when applying this method to this problem:
- Exploration challenge: huge decision space. (client * client * relay_node1 * relay_node2) Impossible to exploration all of them to find a good choice.
- Predict challenge: because of the huge decision space, most of the choices have no historical record. So how to know the predictive QoE of these choices?
Solutions of these 2 challenges:
For exploration challenge: Only explore the choice in the rank N.
For predict challenge: Network tomography is applied to predict the QoE of a choice which has no historical record.
Some thoughts:
- A really well-written paper. Need to learn the writing skill.
- The motivation of this paper has problem: Why “RTT, loss rate, jitter influence QoE —-à we need a control plane to do relay node selection”?
- In the experimental results, authors test each feature of their method and analyze the benefits can be obtained by each of them. Good experiments.