Name
Abstract | ||
|---|---|---|
We consider data intensive cloud-based stream analytics where data transmission through the underlying communication network is the cause of the performance bottleneck. Two key inter-related problems are investigated: task placement and bandwidth allocation. We seek to answer the following questions. How does task placement make impact on the application-level throughput? Does a careful bandwidth allocation among data flows traversing a bottleneck link results in better performance? In this paper, we address these questions by conducting measurement-driven analysis in a SDN-enabled computer cluster running stream processing applications on top of Apache Storm. The results reveal (i) how tasks are assigned to computing nodes make large difference in application level performance; (ii) under certain task placement, a proper bandwidth allocation helps further improve the performance as compared to the default TCP mechanism; and (iii) task placement and bandwidth allocation are collaboratively making effects in overall performance. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ICNP.2017.8117589 | 2017 IEEE 25th International Conference on Network Protocols (ICNP) |
Keywords | Field | DocType |
task placement,data intensive cloud-based stream analytics,data transmission,stream processing applications,bandwidth allocation,communication network,application-level throughput performance,measurement-driven analysis,SDN-enabled computer cluster,Apache Storm,TCP mechanism | Bottleneck,Computer science,Bandwidth allocation,Computer network,Bandwidth (signal processing),Throughput,Analytics,Stream processing,Channel allocation schemes,Computer cluster,Distributed computing | Conference |
ISSN | ISBN | Citations |
1092-1648 | 978-1-5090-6502-8 | 1 |
PageRank | References | Authors |
0.36 | 13 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Walid A. Y. Aljoby | 1 | 1 | 0.36 |
| Tom Z. J. Fu | 2 | 76 | 4.24 |
| Richard T. B. Ma | 3 | 620 | 51.15 |