Abstract
Traffic loads have a significant impact on the performance of routing algorithms. Many analytical models for adaptive routing in interconnection networks have been reported. However, most existing studies are based on the assumption that the arrivals of traffic follow a non-bursty Poisson process and the message destinations are uniformly distributed over the network. With the aim of obtaining a deep understanding of network performance under more realistic working conditions, this study develops an analytical performance model for adaptive-routed hypercubic networks under hot-spot and batch arrival traffic. This model adopts the Compound Poisson Process (CPP) to capture the properties of the batch arrival traffic. Extensive simulation experiments are conducted to validate the accuracy of the analytical model.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - Conference on Local Computer Networks, LCN |
| Pages | 583-590 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2007 |
| Event | 32nd IEEE Conference on Local Computer Networks, LCN 2007 - Dublin, Ireland Duration: Oct 15 2007 → Oct 18 2007 |
Other
| Other | 32nd IEEE Conference on Local Computer Networks, LCN 2007 |
|---|---|
| Country | Ireland |
| City | Dublin |
| Period | 10/15/07 → 10/18/07 |
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Keywords
- Compound Poisson Process (CPP)
- Hot-spot traffic
- Interconnection networks
- Performance evaluation
ASJC Scopus subject areas
- Engineering(all)
Cite this
Performance modelling of adaptive routing in hypercubic networks under non-uniform and batch arrival traffic. / Min, Geyong; Wu, Yulei; Wang, Lan; Ould-Khaoua, Mohamed.
Proceedings - Conference on Local Computer Networks, LCN. 2007. p. 583-590 4367890.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Performance modelling of adaptive routing in hypercubic networks under non-uniform and batch arrival traffic
AU - Min, Geyong
AU - Wu, Yulei
AU - Wang, Lan
AU - Ould-Khaoua, Mohamed
PY - 2007
Y1 - 2007
N2 - Traffic loads have a significant impact on the performance of routing algorithms. Many analytical models for adaptive routing in interconnection networks have been reported. However, most existing studies are based on the assumption that the arrivals of traffic follow a non-bursty Poisson process and the message destinations are uniformly distributed over the network. With the aim of obtaining a deep understanding of network performance under more realistic working conditions, this study develops an analytical performance model for adaptive-routed hypercubic networks under hot-spot and batch arrival traffic. This model adopts the Compound Poisson Process (CPP) to capture the properties of the batch arrival traffic. Extensive simulation experiments are conducted to validate the accuracy of the analytical model.
AB - Traffic loads have a significant impact on the performance of routing algorithms. Many analytical models for adaptive routing in interconnection networks have been reported. However, most existing studies are based on the assumption that the arrivals of traffic follow a non-bursty Poisson process and the message destinations are uniformly distributed over the network. With the aim of obtaining a deep understanding of network performance under more realistic working conditions, this study develops an analytical performance model for adaptive-routed hypercubic networks under hot-spot and batch arrival traffic. This model adopts the Compound Poisson Process (CPP) to capture the properties of the batch arrival traffic. Extensive simulation experiments are conducted to validate the accuracy of the analytical model.
KW - Compound Poisson Process (CPP)
KW - Hot-spot traffic
KW - Interconnection networks
KW - Performance evaluation
UR - http://www.scopus.com/inward/record.url?scp=47249121726&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47249121726&partnerID=8YFLogxK
U2 - 10.1109/LCN.2007.125
DO - 10.1109/LCN.2007.125
M3 - Conference contribution
AN - SCOPUS:47249121726
SN - 0769530001
SN - 9780769530000
SP - 583
EP - 590
BT - Proceedings - Conference on Local Computer Networks, LCN
ER -