dc.contributor.author |
Boughzala, Bochra |
|
dc.contributor.author |
Koldehofe, Boris |
|
dc.date.accessioned |
2025-04-03T05:15:05Z |
|
dc.date.available |
2025-04-03T05:15:05Z |
|
dc.date.issued |
2025-04-03 |
|
dc.identifier.uri |
http://hdl.handle.net/10900/163777 |
|
dc.identifier.uri |
http://nbn-resolving.org/urn:nbn:de:bsz:21-dspace-1637775 |
de_DE |
dc.identifier.uri |
http://dx.doi.org/10.15496/publikation-105107 |
|
dc.description.abstract |
Cloud data center workloads are comprised with a
substantial volume of data-analytics tasks which rely heavily on
data parallel stream processing. Splitting the data streams into
independent data partitions and their distribution across multiple
operators is a heavy operation than can become a performance
bottleneck. Emerging in-network hardware accelerators in cloud
infrastructures can enhance the performance of the splitter function
and improve the parallelism degree of data-intensive cloud
applications. Building on Programming Protocol-independent
Packet Processors (P4), we devised a P4-based splitter fully in the
data plane to benefit from line-rate performance of P4 packet
processors, e.g., Tofino Switch. We present a summary of the
splitter switch capabilities and complement our proposed design
with new discussion points for future consideration. |
en |
dc.language.iso |
en |
de_DE |
dc.publisher |
Universität Tübingen |
de_DE |
dc.subject.ddc |
004 |
de_DE |
dc.title |
In-Network Splitter Function Enabling Highly-Parallel Event Stream Processing |
en |
dc.type |
Article |
de_DE |
utue.publikation.fachbereich |
Informatik |
de_DE |
utue.publikation.fakultaet |
7 Mathematisch-Naturwissenschaftliche Fakultät |
de_DE |
utue.publikation.noppn |
yes |
de_DE |