Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Energy efficiency and CAPEX minimization for backbone network planning: is there a tradeoff?
ANTS'09 Proceedings of the 3rd international conference on Advanced networks and telecommunication systems
Power-efficient multi-layer networking: design and evaluation
ONDM'10 Proceedings of the 14th conference on Optical network design and modeling
Energy Efficiency in Telecom Optical Networks
IEEE Communications Surveys & Tutorials
Dynamic routing at different layers in IP-over-WDM networks - Maximizing energy savings
Optical Switching and Networking
Minimizing ISP network energy cost: formulation and solutions
IEEE/ACM Transactions on Networking (TON)
Power consumption modeling in optical multilayer networks
Photonic Network Communications
Energy-aware IP traffic engineering with shortest path routing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Sleep modes effectiveness in backbone networks with limited configurations
Computer Networks: The International Journal of Computer and Telecommunications Networking
| Hi-index | 0.00 |
We consider the power-efficient design of an Internet Protocol (IP)-over-Wavelength Division Multiplexing (WDM) network, tackling the problem of deciding which equipment needs to be installed in both the optical and IP layer. Our model explicitly targets the minimization of cost considered as either Capital Expenditures (CapEx) or power. In contrast to the models already presented in the literature, we take into account routing constraints and consider a comprehensive set of realistic scenarios defined by a network topology, traffic, cost and power values of network devices in both layers. Results indicate that the introduction of realistic constraints and parameters still allows power-efficient networks to be designed. The total power consumption in the considered network scenarios is at most 26.5% higher than when using previous models.