Paper Info
Title
A Multi-channel and Real-Time Disaster Recovery Backup Method Based on P2P Streaming
Abstract
The cost of backup for disaster recovery using leased line is high and there is also a conflict between fixed bandwidth of the leased line and dynamic changes of backup data size. The transmission of leased line also has danger of single point failure. In this paper, we put forward a multi-channel and real-time disaster recovery backup method based on P2P streaming. We designed the transmission model and backup algorithm which consisted of node joining and leaving algorithm, data sending and receiving mechanism of multi-channel and self-adaptive bandwidth. We also designed network nodes conflict resolution algorithm to ensure transport channel redundancy. We evaluated the important metrics of RTO and RPO under different conditions and optimized algorithm in terms of metrics improvement and efficiency. Finally, we carried out simulation experiments.
Year
DOI
Venue
2013
10.1109/EIDWT.2013.9
EIDWT
Keywords
Field
DocType
transport channel redundancy,rto,self-adaptive bandwidth,optimized algorithm,backup method,backup,real-time disaster recovery backup,metrics improvement,data sending mechanism,p2p,recovery time objective,real-time disaster recovery backup method,backup algorithm,p2p streaming,backup data size,node joining algorithm,recovery point objective,network nodes conflict resolution,system recovery,network node conflict resolution algorithm,node leaving algorithm,media streaming,internet,rpo,multi-channel,real-time disaster recovery,peer-to-peer computing,multichannel disaster recovery backup method,fixed bandwidth,transmission model,important metrics,real-time systems,metrics efficiency,disaster recovery,data receiving mechanism,real time systems
Algorithm design,Data loss,Computer science,Node (networking),Computer network,Communication channel,Real-time computing,Bandwidth (signal processing),Redundancy (engineering),Backup,Disaster recovery
Conference
ISBN
Citations 
PageRank 
978-1-4799-2140-9
0
0.34
References 
Authors
8
2
Name
Order
Citations
PageRank
Dongyan Zhang165.81
Tao Zhang220240.44