Loading...
Please wait, while we are loading the content...
Similar Documents
On the capabilities of application level traffic measurements to differentiate and classify Internet traffic (2001)
| Content Provider | CiteSeerX |
|---|---|
| Author | Ilvesmäki, Mika Luoma, Marko |
| Description | The use of network based traffic classification to differentiate aggregate traffic has been introduced with the development of new Internet service architectures, especially with the Differentiated Services. We present measurements and analysis of various packet and flow statistics to aid in classifying or differentiating traffic flows according to the application nature. Our study on methods traffic classification includes the background analysis of traffic traces to detect applications of varying nature by measuring packet inter-arrival times, packet lengths, flow inter-arrival times, and packet and flow shares of total tra#c. Most promising results with a single statistic are achieved when classifying traffic based on packet inter-arrival patterns. The interarrival time distributions of packets seem to be able to divide the traffic into two distinguishable classes. However, the division to three or more classes remains as somewhat ambiguous issue and needs further research. However, the results also indicate that no single statistic is able to classify application flows with reasonable certainty but that this might be achieved when several statistics and their analysis results are combined. A good method of increasing the classification result would be to increase the dimensionality of the classification. For instance, combining the classification results of packet IAT and packet length distributions would almost certainly lead to the detection of applications of different nature. |
| File Format | |
| Language | English |
| Publisher Date | 2001-01-01 |
| Publisher Institution | Internet Perfomance and Control of Network Systems II, Proceedings of SPIE |
| Access Restriction | Open |
| Subject Keyword | Analysis Result Method Traffic Classification Classification Result Interarrival Time Distribution Flow Statistic Traffic Classification Ambiguous Issue Flow Share Several Statistic Promising Result Packet Length Present Measurement Differentiated Service Reasonable Certainty Application Level Traffic Measurement Packet Length Distribution Distinguishable Class Aggregate Traffic New Internet Service Architecture Packet Inter-arrival Time Internet Traffic Single Statistic Total Tra Packet Inter-arrival Pattern Different Nature Packet Iat Application Nature Various Packet Background Analysis Good Method Flow Inter-arrival Time Traffic Trace |
| Content Type | Text |
| Resource Type | Article |
