Location
Hilton Waikoloa Village, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
7-1-2025 12:00 AM
End Date
10-1-2025 12:00 AM
Description
This paper develops a mathematical model to examine the inter-technology relationship between conventional Internet networks and data center interconnection (DCI) networks. The model is based on principles from mathematical biology. It is constructed by treating the data traffic of both networks as variables, analogous to biological populations, and considering their interpopulation and intrapopulation interactions due to density effects. The model's parameters are estimated from measured data traffic. Due to the relatively low regression accuracy of these parameter estimates, Monte Carlo simulations are performed to account for their variability. The conditions for establishing a long-term equilibrium relationship are then statistically analyzed. We found that the two types of data traffic coexist in equilibrium if the variation in the estimated parameters is within 5% of their absolute values.
Recommended Citation
Kawai, Shingo and Toma, Tetsuya, "Relation between Conventional Internet Network and Data Center Interconnection Network: -Competition between Technologies or Technological Transition" (2025). Hawaii International Conference on System Sciences 2025 (HICSS-58). 2.
https://aisel.aisnet.org/hicss-58/in/diffusion_of_ict/2
Relation between Conventional Internet Network and Data Center Interconnection Network: -Competition between Technologies or Technological Transition
Hilton Waikoloa Village, Hawaii
This paper develops a mathematical model to examine the inter-technology relationship between conventional Internet networks and data center interconnection (DCI) networks. The model is based on principles from mathematical biology. It is constructed by treating the data traffic of both networks as variables, analogous to biological populations, and considering their interpopulation and intrapopulation interactions due to density effects. The model's parameters are estimated from measured data traffic. Due to the relatively low regression accuracy of these parameter estimates, Monte Carlo simulations are performed to account for their variability. The conditions for establishing a long-term equilibrium relationship are then statistically analyzed. We found that the two types of data traffic coexist in equilibrium if the variation in the estimated parameters is within 5% of their absolute values.
https://aisel.aisnet.org/hicss-58/in/diffusion_of_ict/2