On the Economic Viability of Network Architectures Roch Guerin, Kartik Hosanagar (University of Pennsylvania) Andrew Odlyzko, Zhi-Li Zhang (University of Minnesota)

Motivation  Success of new technologies depends on economic factors. Many technologies have failed to widely deploy. Ex: IPv6, various QoS services  How do we design network architectures that are not only technically superior but also economically viable? 2

Objectives  Identify key economic factors that influence design choices and trade-offs in developing, deploying and evolving network architectures.  Model the functional relationships between the economic factors and new technologies in network architecture designs.  Compare alternative network architectures in terms of their economic viability. 3

Key Research Topics  Identify the impact of incumbent technology on new network architecture adoption Model the dynamics of technology adoption  Quantify the trade-off between diversity and integration in network offerings Many services over a single network vs. Many services over separate multiple networks and the impact of virtualization on those choices  Assess the benefits of open and flexible network architectures. 4

A View of Technology Adoption 5

Economic Parameters of Significance  Intrinsic benefits of an architecture/technology  Network externalities  Cost Fixed cost: deployment cost Variable cost: operation and maintenance cost  Pricing strategies  Compatibility with existing systems (converters/ gateways)  Switching costs (to switch from one to another) 6

Initial Investigations  Identify the impact of incumbent technology on the (eventual) success of new network architectures Model the dynamics of technology adoption Diffusion, price competition and technical evolution of incumbent and new technologies  Our current focus Understand factors affecting the transition from one architecture to another leading to eventual success Capture the dynamics of the transition process  Find static equilibrium of market share at time t.  Find the trajectory of equilibrium. 7

Modeling Assumptions  Two competing technologies.  Rational users A user chooses a technology only if it gives a positive utility. A user chooses the technology that gives a higher utility.  Each user has its own preference. The distribution of preferences is known. 8

Utility function  Utility of technology i at time t U i (x i,t) = benefit – cost Benefit = f( , q i (t), v(x i )), where x i : fraction of users adopting technology i,  : individual user preference, q i (t) : utility of the technology i at time t, v(x i ) : network externality.  Cost = g (price, negative network feedback) 9

Adoption Indifference Points  Indifference points for technology adoption  Ex: under some conditions 10

Static Equilibrium  At a fixed time t, the adoption equilibrium is  Equilibrium adoption path as a function of t Time varying utility functions q i (t) Adoption path may be discontinuous  Extensions and alternative approaches Introduction of converters and pricing strategies Diffusion model based approach  Better capture dynamics of changing market share?  Easier introduction of “switching” costs. 11

Future Work and Directions  Model the evaluation of benefits of diversity  Model the impact of flexibility and openness  Method: Using real options  “Validation” of models and their application Looking at the past (known adoption evolution) Looking at the present (extracting cost & utility functions) Looking at the future (evaluating proposed architectures)  Synergy with existing FIND projects Economic aspect  Market-Enabling Network Architecture Virtualization and diversity  An Architecture for a Diversified Internet  CABO: Concurrent Architectures are Better than One 12