Name
Abstract | ||
|---|---|---|
As random network coding (RNC) considerably increases the network throughput, it has been of great interest for video streaming over wireless mesh networks (WMNs). However, mobile video users suffer from high transmission overhead due to the transmission of large coefficient vectors as headers and an excessive imposed decoding computational complexity due to using the Gauss---Jordan elimination method in RNC. This complexity cannot be supported by the embedded mobile processors. To overcome these limitations, this study analyses the impact of applying a method that simplifies RNC requirements on WMNs. This method is based on the generation of a full rank coefficients matrix without any linear dependency among its vectors. Nodes encapsulate one instead of $$n$$n coefficients entries into a packet which leads to very low transmission overhead. Receivers can obtain the inverted coefficients matrix by performing very few arithmetic operations. Consequently, wireless nodes experience very low decoding computational complexity eliminating the need for powerful processors and high battery energy sources. The wireless medium is also less occupied and the transmission processes are shorter. Simulation results in the OMNeT++ framework depict that the applied method provides high video quality on the nodes by addressing the mentioned challenges, even if high mobility rates exist in the WMN. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s11277-014-2112-5 | Wireless Personal Communications |
Keywords | Field | DocType |
Random network coding, Hybrid wireless mesh networks, Peer-to-peer networking, Live video streaming, Performance evaluation | Wireless,Computer science,Network packet,Mobile processor,Computer network,Real-time computing,Decoding methods,Throughput,Wireless mesh network,Video quality,Computational complexity theory | Journal |
Volume | Issue | ISSN |
80 | 4 | 1572-834X |
Citations | PageRank | References |
11 | 0.51 | 292 |
Authors | ||
10 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Behrang Barekatain | 1 | 43 | 4.66 |
| Dariush Khezrimotlagh | 2 | 35 | 3.00 |
| Mohd. Aizaini Maarof | 3 | 138 | 22.20 |
| Hamid Reza Ghaeini | 4 | 30 | 3.62 |
| Alfonso Ariza-Quintana | 5 | 31 | 4.14 |
| Alicia Triviño-cabrera | 6 | 79 | 7.75 |
| MaarofMohd Aizaini | 7 | 11 | 0.51 |
| GhaeiniHamid Reza | 8 | 11 | 0.51 |
| QuintanaAlfonso Ariza | 9 | 11 | 0.51 |
| CabreraAlicia Triviño | 10 | 11 | 0.51 |