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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Lowekamp, B. O'Hallaron, D. Gross, T. |
| Copyright Year | 1999 |
| Description | Author affiliation: Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA (Lowekamp, B.) |
| Abstract | The development and performance of network-aware applications depends on the availability of accurate predictions of network resource properties. Obtaining this information directly from the network is a scalable solution that provides the accurate performance predictions and topology information needed for planning and adapting application behavior across a variety of networks. The performance predictions obtained directly from the network are as accurate as application-level benchmarks, but the network-based technique provides the added advantages of scalability and topology discovery. We describe how to determine network properties directly from the network using SNMP. We provide an overview of SNMP and describe the features it provides that make it possible to extract both available bandwidth and network topology information from network devices. The available bandwidth predictions based on network queries using SNMP are compared with traditional predictions based on application history to demonstrate that they are equally useful. To demonstrate the feasibility of topology discovery, we present results for a large Ethernet at CMU. |
| Starting Page | 38 |
| Ending Page | 46 |
| File Size | 856272 |
| Page Count | 9 |
| File Format | |
| ISBN | 0780356810 |
| ISSN | 10828907 |
| DOI | 10.1109/HPDC.1999.805280 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1999-08-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Intelligent networks Network topology Bandwidth Computer science Availability History Ethernet networks US Government Hardware Data mining |
| Content Type | Text |
| Resource Type | Article |
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