원문정보
초록
영어
Data generated by various fields are increasing exponentially and thus results in challenges for data performances in both scales of diversity and complexity. The problem how to solve the bottlenecks of low -bandwidth networks has been of fatal significance for all kinds of network status. We present a new approach on improved optimization for data disaster recovery system (DDRS) over low-bandwidth networks that not only aims to improve the defects and deficiencies of mainstream DDRS but also helps ensure the reliable network resources for operators to conduct multi-services. A novel bandwidth self-adaptive approach (BSAA) for data packing replication was essentially established to make contribution to the integral performance improvement. A Hidden Markov Model (HMM) for predicting network status was also built to ensure system availability and stability. Experiments showed that the DDRS over low-bandwidth networks named InfoDr can effectively optimize the workload with better performance and better application self-adaptability for multi-services. Keywords: Data Disaster Recovery System; Low-bandwidth network; Deduplication
목차
1. Introduction
2. Related Work
3. Architecture
4. A Novel Bandwidth Self-adaptive Approach
4.1. Deduplication and Delta Compression
4.2. Data Collision and Consistency Policy
5. A Hidden Markov Model Over Low-bandwidth Networks
6. Experimental Evaluation
6.1. Experiment Environment
6.2. Performance Evaluation
7. Conclusion
Acknowledgement
References