Optimizing Multi-Layered Networks Towards a Transparently Optical Internet Presenter: Moshe Zukerman Electronic Engineering Dept., City University of Hong Kong Hong Kong SAR, PRC Authors: Ron Addie, David Fatseas, Moshe Zukerman

Outline The Current Internet Energy considerations Teletraffic implications Tecnology options Flow size dependent routing Conclusion

Outline The Current Internet Background Circuit switching versus packet switching Optical Internet model and design options: OCS, OBS, OFS, fractional lambda, flow routing. Conclusion

Mainly based on Packet switching. Layered approach - flexibility Packets - independent of applications Open Shortest Path First (OSPF) protocol Routers; Look up tables; no state information of connections (net-head approach). Hard to guarantee Quality of Service (QoS). Current Internet

Current Internet – the success So far the Netheads have had the upper-hand. IP dominates the desktop. Users have voted with their feet - satisfied with service received because they get it at supermarket prices. This is a “simple” observation that we can learn from.

Current Internet – the success Why? Efficiency - Statistical multiplexing; Flexibility – new services are designed to cope with the quality (or lack thereof) provided by the Internet (e.g. Skype).

The netheads have had the upper hand This needs to be respected. But where are we going from here?

Scalability QoS Energy consumption (growth - energ. Improv. >> GNP) Efficiency Image: Traffic Prediction and engineering Technology choices Security Reliability Topology Dimensioning Multi-domain

[1] R. S. Tucker, “Green Optical Communications - Part I: Energy Limitations in Transport”, To be published in IEEE Journal of Selected Topics in Quantum Electronics, Special Issue on Green Photonics. Energy/bit/distance for various transatlantic transmission systems

[2] R. S. Tucker, “Green Optical Communications - Part II: Energy Limitations in Networks”, To be published in IEEE Journal of Selected Topics in Quantum Electronics, Special Issue on Green Photonics. “business as usual”

[2] R. S. Tucker, “Green Optical Communications - Part II: Energy Limitations in Networks”, To be published in IEEE Journal of Selected Topics in Quantum Electronics, Special Issue on Green Photonics. PIC = photonic integrated circuit

Towards all-optical Internet Packet Switching at the access is here to stay for many users. For the present and into the near future this means IP But for the core, optical bypass and Optical Circuit Switching (OPC) could be justified more and more based on cost and energy consumption considerations.

Towards All-Optical Internet (cont.) “Old” Electronic Internet: Capacity expensive, buffering cheap Introduction of DWDM makes capacity cheap Future All-Optical Internet (?): Link capacity plentiful, buffering painful (cost, power, space); wavelength conversion (for Optical Packet Switching) is costly. A further case for CS

Services s, Sensor signals (mice) HD-IPTV, Virtual reality (elephants, whales) Others (kangaroos) Traffic engineering and network dimensioning implications

Size-based Routing mice – maybe aggregated together and sent using a permanent/semi-permanent path. HD-IPTV, virtual reality (elephants, whales) –their size may justify setting up a path/light-path –whales need to swim in an ocean (although there are not many big pipes)

Size-based Routing (cont.) Others (kangaroos) – may use the current shortest path routing. Size based routing provides: –Technology choice –Traffic engineering –Dimensioning In a scalable way.

The Traffic model The traffic for each end-to-end demand follows a Poisson Pareto burst process (PPBP) - Poisson arrival process of Pareto distributed bursts/flows.

Flow size distribution (Truncated Pareto) P( F > t ) = Δ = Max flow size  = Min flow size  = rate parameter The case is included

Mean Bitrate (PPBP) E[Bitrate] = λ = Arrival rate of flows

The Approach Layers – each layer - a technology (e.g. IP, ATM, WDM) Traffic model: Poisson arrivals of flows Each flow – Pareto distributed size In principle, each flow is routed on the least-cost path for this flow size in each layer (technology).

The Approach (continued) Lower layer costs less per bit – but modules are larger. Some intuition: –Flocking – so relatively not many large links. –Elephants decide the permanent path and mice use the scraps.

The Approach (continued) A new technology can be incorporated into this model by choosing a collection of cost parameters for traffic delivery. Traffic stream is split between layers according to flow sizes. Traffic stream is split between alternative routes according to flow sizes.

The Approach (continued) So we have here aggregation of flows and splitting of flows in routing and in layers. All the aggregated traffic that needs to use a link in layer n may require (delegation) a path in layer n-1. => link at n => traffic at n-1.

The Approach (continued) The traffic is consistent in routing – the mean is maintained consistent – no traffic is lost – or added. For simplicity and scalability merging of many Pareto models is modeled by a single Pareto model. (Peak and mean are fitted – lower bound is adjusted.)

The Approach (continued) Fixed-point iterations are used to obtain the capacity required for each layer. The convergence criterion is the sum of the capacity differences between two iterations (absolute values) of each link/layer < small value. For simplicity and scalability, merging of many Pareto models is modeled by a single Pareto model. (Peak and mean are fitted – lower bound is adjusted.) In the current implementation, there are 4 types of flow sizes separated by

NETML Demo emo3/netmldemo3.htm

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