Name
Abstract | ||
|---|---|---|
In network tomography, we seek to infer link status parameters (delay, congestion, loss rates etc.) inside a network through end-to-end measurements at (external) boundary nodes. As can be expected, such approaches generically suffer from identifiability problems; i.e., status of links in a large number of network topologies is not identifiable. We introduce an innovative approach based on linear network coding that overcomes this problem. We provide sufficient conditions on network coding coefficients and training sequence under which any logical network is guaranteed to be identifiable. In addition, we show that it is possible to locate any congested link inside a network during an arbitrary amount of time by increasing size of transmitted packets, leading to raise in complexity of the method. Further, a probability of success is provided for a random network. OPNET is used to implement the concept and confirm the validity of the claims — simulation results confirm that LNC correctly detects the congested link in situations where standard probing based algorithm fails. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/LCN.2010.5735682 | LCN |
Keywords | Field | DocType |
network tomography,end-to-end measurement,logical network,linear network coding,link failure monitoring,network topology,link status parameter,boundary node,arbitrary amount,congested link,random network,finite field,routing,network coding,tomography,graph theory,random processes,topology | Linear network coding,End-to-end delay,Network delay,Computer science,Network packet,Network simulation,Computer network,Network topology,Network tomography,Network traffic control,Distributed computing | Conference |
ISSN | Citations | PageRank |
0742-1303 | 5 | 0.49 |
References | Authors | |
8 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mohammad H. Firooz | 1 | 141 | 11.12 |
| Sumit Roy | 2 | 2245 | 203.71 |
| Linda Bai | 3 | 12 | 1.28 |
| Christopher Lydick | 4 | 5 | 0.49 |