Name
Title | ||
|---|---|---|
A Quick Recovery Strategy for Network Failure under Multipath Multicast Transmissions |
Abstract | ||
|---|---|---|
The rapid development of immersive multimedia applications puts forward higher requirements for the backbone transmission of CDNs. However, network failures, such as link interruptions, are a considerable challenge to smooth transmission. Ideally, when a failure occurs, the system should handle it seamlessly to avoid QoE degradation. That is, the system should discover more paths to satisfy all users. However, existing recovery strategies for large-scale networks take seconds to minutes to gather network status information and discover new paths, which is unbearable for millisecond-level immersive applications. In this paper, we study the problem of failure recovery in an overlay CDN network. We propose a quick failure recovery strategy. This strategy does not collect network states but re-decides flow transmission schemes with existing multiple paths. This quick recovery strategy aims to obtain an emergency response quickly to minimize the number of users affected by the failure. It is the first line of dealing with the failure so that the system can spend more time collecting network state and discovering new paths to complete its recovery solution until all users are satisfied. Simulations show that our approach can effectively improve the service capability after failures, up to double the performance. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics53846.2021.00056 | 2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics) |
Keywords | DocType | ISBN |
failure recovery,multipath,multicast,overlay CDNs | Conference | 978-1-6654-1763-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chao Xu | 1 | 0 | 0.68 |
| Jessie Hui Wang | 2 | 118 | 20.10 |
| Rui Li | 3 | 0 | 0.34 |
| Yu Tao | 4 | 1 | 5.45 |
| Jilong Wang | 5 | 57 | 19.88 |