Title:
KStreams: Kernel Support for Efficient End-to-End Data Streaming
KStreams: Kernel Support for Efficient End-to-End Data Streaming
| dc.contributor.author | Kong, Jiantao | |
| dc.contributor.author | Schwan, Karsten | |
| dc.date.accessioned | 2004-08-11T18:51:26Z | |
| dc.date.available | 2004-08-11T18:51:26Z | |
| dc.date.issued | 2004 | |
| dc.description.abstract | Technology advances are enabling increasingly data-intensive applications, ranging from peer-to-peer file sharing, to multimedia, to remote graphics and data visualization. One outcome is the considerable memory pressure imposed on the machines involved, caused by application-specific data movements and by repeated crossings of user/kernel boundaries. We address this problem with a novel system service, termed KStreams, a general facility for manipulating data without using intermediate buffers when it moves across multiple kernel objects, like files or sockets. KStreams may be used to implement kernel-level services that range from application-specific implementations of sendfile commands, to data mirroring or proxy functions, to fast path data conversions and transformations for data streaming. The KStreams API permits individual applications to define fast path operations, which will then execute at kernel level and if desired, without further application involvement. By placing application-specific data manipulations into data movement fast paths, user/kernel boundary crossings are avoided. By operating on data streams `in-flight', data buffering is made unnecessary, thereby further reducing the memory pressure imposed on machines. KStreams is implemented on Linux kernel version 2.4.22. Its evaluation uses data-intensive tasks performed in conjunction with modern web services, such as proxy functions, remote media streaming, data visualization, etc. Initial experiences with the KStreams implementation are encouraging. Fast path data transformation via KStreams results in increased throughput of 20-50% compared to user-level data manipulations. Future work with KStreams uses it with complex multi-machine web services, evaluated with representative user loads and applications. | en |
| dc.format.extent | 229777 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/89 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.relation.ispartofseries | CERCS;GIT-CERCS-04-04 | |
| dc.subject | Data objects | |
| dc.subject | Data streaming | |
| dc.subject | Data intensive applications | |
| dc.subject | Fast paths | |
| dc.subject | Increased throughputs | |
| dc.subject | Kernel level services | |
| dc.subject | Kernels | |
| dc.subject | Kstreams | |
| dc.subject | Memory resources | |
| dc.title | KStreams: Kernel Support for Efficient End-to-End Data Streaming | en |
| dc.type | Text | |
| dc.type.genre | Technical Report | |
| dspace.entity.type | Publication | |
| local.contributor.author | Schwan, Karsten | |
| local.contributor.corporatename | Center for Experimental Research in Computer Systems | |
| local.relation.ispartofseries | CERCS Technical Report Series | |
| relation.isAuthorOfPublication | a89a7e85-7f70-4eee-a49a-5090d7e88ce6 | |
| relation.isOrgUnitOfPublication | 1dd858c0-be27-47fd-873d-208407cf0794 | |
| relation.isSeriesOfPublication | bc21f6b3-4b86-4b92-8b66-d65d59e12c54 |