Name
Abstract | ||
|---|---|---|
In Big Data era, continuous data with low latency and high throughput makes high-availability essential for stream computing. Traditional availability guarantee is tightly-coupled and inefficient for customization and reuse. In this paper, a framework is proposed to improve the availability of stream computing, in which basic functions are provided as general services like reliable point-to-point communication and distributed status management. With its help, high-level patterns can be achieved effectively. Comprehensive experiments have been designed and evaluated to show the availability improvement with acceptable extra overheads. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/ICWS.2016.82 | 2016 IEEE International Conference on Web Services (ICWS) |
Keywords | Field | DocType |
Big Data,stream computing,high availability,service | Computer science,Reuse,Stream,Latency (engineering),Throughput,High availability,Big data,Database,Overhead (business),Distributed computing,Personalization | Conference |
ISBN | Citations | PageRank |
978-1-5090-2676-0 | 0 | 0.34 |
References | Authors | |
11 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weilong Ding | 1 | 9 | 5.09 |
| Zhuofeng Zhao | 2 | 66 | 15.46 |
| Yanbo Han | 3 | 500 | 59.74 |