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Soumya Sen Dept. of Electrical & Systems Engineering University of Pennsylvania ssoumya@seas.upenn.edu www.seas.upenn.edu/~ssoumya Joint Work with: R. Guerin, K. Hosanagar, Y. Jin. On the Adoption and Deployment of New Network Technologies: An Economic Perspective.
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Soumya Sen Dept. of Electrical & Systems Engineering University of Pennsylvania ssoumya@seas.upenn.edu www.seas.upenn.edu/~ssoumya Joint Work with: R. Guerin, K. Hosanagar, Y. Jin On the Adoption and Deployment of New Network Technologies: An Economic Perspective 18th November, 2010. Penn Seminar on Communications & Networking
Networked Systems have a ubiquitous presence e.g., Internet, Power grid, Facilities Management networks, Distributed databases Success of new network technologies depends on: Technical advantage Economic factors (e.g. price, costs, demand) Shortcomings: Many technologies have failed to get adopted e.g., IPv6 migration, QoS solutions Ad-hoc decisions for deployment e.g. Cloud Coimputing, U-Verse versus. FiOS How to assess (design) new network technologies (architectures) for technicaland economicviability? Analytical frameworks Multi-disciplinary approach Research Motivation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 2
On Developing Analytical Models: What are the key economic aspects? What factors are specific to network technologies? (e.g. externality, gateways) What are the ‘qualitative’ insights from the model? Are the results robust to changes in the underlying model? Some Dimensions for Assessing Network Technologies: Topic 1: Network Technology Adoption/ Migration How can a provider help its technology (service) to succeed? Topic 2: Network Infrastructure Choice What infrastructure should the new technology (service) be deployed on? Understanding Trade-offs between Shared and Dedicated networks Topic 3: Trade-offs between Functionality-rich versus Minimalist Designs Research Approach S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 3
Network Technology Adoption Dependencies across users (externality) Incumbent’s advantage of installed base Gateway’s impact on adoption Explored the dynamics of adoption among heterogeneous users Characterized the trajectories and equilibrium outcomes Analyzed the role of gateways in migration Shared vs. Dedicated Networks Many services on a common (shared) network vs. Many services over separate (dedicated) networks Choice depends on compatibility among services, demand uncertainty Identified trade-offs and guideline for network design Research Contributions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 4
Network Technology Adoption 1. Problem Formulation 2. Model & Solution Methodology 3. Key Findings & Examples 4. Conclusions A Two-part Talk: Outline S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 5
Two competing and incompatible network technologies (e.g., IPv4 IPv6) Different qualities and price Different installed base Users individually (dis)adopt the technology that gives them the highest positive utility Depends on technology’s intrinsic value and price Depends on number of other users reachable (externality) Gateways offer a migration path Overcome chicken-and-egg problem of first users Independently developed by each technology Effectiveness depends on gateways (converters) characteristics/ performance Duplex vs. Simplex (independent in each direction or coupled) Asymmetric vs. Symmetric (performance/ functionality wise) Constrained vs. Unconstrained (performance/functionality wise) Problem Formulation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 7
A Basic User Model Technology 1: U1(,x1,x2) = q1+(x1+α1β x2) – p1 Technology 2: U2(,x1,x2) = q2+(βx2+α2x1) – p2 • Users evaluate relative benefits of each technology • Intrinsic value of the technology ( q1) • Tech. 2 better than Tech.1 (q2>q1) • denotes user valuation (captures heterogeneity), Є[0,1]. • Externalities: linear in no. of users (0≤x1+x2≤1) - Metcalfe’s Law • Possibly different across technologies (captured through β) • αi, 0αi1, i = 1,2, captures gateway’s performance • Cost (recurrent) for each technology (pi) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 8
Low-def. video (Tech.1) High-def video (Tech. 2) • Technology 1: U1(,x1,x2) = q1+(x1+α1β x2) – p1 • Technology 2: U2(,x1,x2) = q2+(βx2+α2x1) – p2 • User sensitivity to technology quality ( ) • Private information for each user, but known distribution • Low-def & High def video-conferencing service • Low-def has a lower price (p1< p2)but lower quality (q1< q2) • Video is an asymmetric technology • Encoding is hard, decoding is easy • Low-def subscribers could display high-def signals but not generate them • Externality benefits of High-def are higher than those of Low-def • Converter characteristics (β>1) • High/Low-def user can decode Low/High-def video signal • αi, 0αi1, i = 1,2, captures gateways’ performance • Simplex, asymmetric, unconstrained (α1β>1) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 10
User Adoption Process • Decision threshold associated with indifference points for each technology choice: 10(x), 20(x), 21(x),wherex=(x1, x2) • U1(, x) > 0if≥10(x) - Tech. 1 becomes attractive • U2(, x) > 0 if≥20(x) - Tech. 2 becomes attractive • U2(, x) > U1(, x)if≥21(x) - Tech. 2 over Tech. 1 • Users rationally choose • None if U1< 0, U2<0 • Technology 1 if U1>0, U1> U2 • Technology 2 if U2>0, U1< U2 • Decisions change as x evolves over time (myopic) x1 x2 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 11
Diffusion Model • Assume a given level of technology penetration x(t)=(x1(t),x2(t)) at time t • Hi(x(t)) is the number of users for whom it is rational to adopt technology i at time t (users can change their mind) • At equilibrium, Hi(x*) = xi*, i {1,2} • DetermineHi(x(t)) from user utility function • Adoption dynamics: • Users differ in learning and reacting to adoption information • Diffusion process with constant rate γ< 1 H1( x(t)) H2( x(t)) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 12
Solution Methodology • Delineate each region in the (x1,x2) plane, where Hi(x)has a different expression • There are 9 such regions, i.e., R1,…, R9 • Regions can intersect the feasibility region S • 0 x1+x21 in a variety of ways • This is in part what makes the analysis complex • trajectories cross boundaries R1 x2=1 R4 P R2 R5 R6 Q R3 R7 0 R8 x1=1 R9 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 13
Computing Equilibria & Trajectories • Solve Hi(x*) = xi*, i {1,2} in each region • Identify “candidate” equilibrium for each Region Rk • Candidates are valid onlyif they lie in their region • Equilibria can be stable or unstable • Trajectories: • λ1and λ2can be positive, negative, or even complex S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 14
What are possible adoption outcomes? Combinations of equilibria Stable/ Unstable Adoption trajectories? Monotonic vs. chaotic (cyclic) What is the role of gateways? Do they help and how much? Key Questions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 15
Theorem 1: There can be multiple stable equilibria (at most two) Coexistence of technologies is possible even in absence of gateways Final outcome is hard to predict simply from observing the initial adoption trends Results (1): A Typical Outcome S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 16
Theorem 2:Gateways can help a technology alter market equilibrium from a scenario where it has been eliminated to one where it coexists with the other technology, or even succeeds in nearly eliminating it. Gateways need not be useful to entrant always! No gateways: Tech. 2 wipes out Tech.1 Perfect gateways: Tech. 1 nearly wipes out Tech. 2 Results (2): Gateways may help Incumbents S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 17
Theorem 3:Incumbent can hurt its market penetration by introducing a gateway and/or improving its efficiency if entrant offers higher externality benefits (β>1) and users of incumbent are able to access these benefits (α1β>1) Theorem 4: Both technologies can hurt overall market penetration through better gateways. Entrant can have such an effect only when (α1β<1). Conversely, Incumbent demonstrates this behavior only when (α1β>1) Takeaway: Gateways can be harmful at times. They can lower market share for an individual technology or even both. Results (3): More Harmful Gateway Behaviors S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 18
Theorem 5: Gateways can create “boom-and-bust” cycles in adoption process. This arises only when entrant exhibits higher externality benefits (β>1) than incumbent and the users of the incumbent are unconstrained in their ability to access these benefits (α1β>1) Corollary: This cannot happen without gateways, i.e., in the absence of gateways, technology adoption always converges Takeaway: Gateways can create perpetual cycles of adoption/ disadoption P.S: Behavioral Results were tested for robustness across wide range of modeling changes Results (4): More Harmful Gateway Behaviors S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 19
Limit Cycles: An Intuitive Explanation α1β>1 Technology 1 Technology 2 Full-circle! Technology 1: U1(,x1,x2) = q1+(x1+α1β x2) – p1 Technology 2: U2(,x1,x2) = q2+(βx2+α2x1) – p2 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 20
Gateways can be useful to: Promote coexistence & improve market penetration Help lessen price sensitivity But, Gateways can be harmful too: Hurt an individual technology Lower Overall Market Introduce Market Instabilities Analytical model is useful in: Identifying scenarios for policy intervention developing long-term strategic vision Qualitative results are robust to: switching costs variation in utility function non-uniform distr. of user preferences Conclusions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 21
Network Infrastructure Choice:Shared Versus Dedicated Networks 1. Problem Formulation 2. Model & Solution Methodology 3. Key Findings & Examples 4. Conclusions Part 2: Outline S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 22
Emergence of new services require: Network provider has to decide between: Common (shared) Network Infrastructure Separate (dedicated) Network Infrastructure Examples: Facilities Management services & IT e.g. IT & HVAC systems Video and Data services e.g. Internet & IPTV services Cloud Computing e.g. Private (dedicated) cloud Vs Shared cloud Broadband over Power lines Lack of Framework to evaluate choices: Ad-hoc decisions (AT&T U-Verse versus Verizon FiOS) Manufacturing Systems Literature: Plant-product allocation, optimal resource allocation Motivation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 23
Two network services (technologies) One existing (mature) service One new service with demand uncertainty Costs show economies or diseconomies of scope New service has demand uncertainty Needs capacity provisioning beforedemand gets realized Dynamic resource “reprovisioning” But some penalty will be incurred (portion of excess demand is lost) Technology advances allow Reprovisioning (e.g., using virtualization) How critical is reprovisioning ability in choosing network design? Compare networks based on profits Problem Formulation S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 25
Model Formulation • Basic Model: • A Two-Service Model • Service 1 (existing service) • Service 2 (new service with uncertain demand) • Three-stage sequential decision process • Compare Infrastructure choices based on expected profits Infrastructure Choice Stage Capacity Allocation Stage Solve backwards Reprovisioning Stage S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 26
Model Variables • Provider’s profit depends on: • Costs: • Fixed costs • Variable costs • - grows with the number of subscribers (e.g. access equipment, billing) • Capacity costs • - incurred irrespective of how many users join (e.g. provisioning, operational) Gross Profit Margin = pi - ai , i={s2, d2} Return on capacity = pi /ai S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 27
Solution (1): Reprovisioning Stage • Service 2 revenue: (i={s2, d2} for Shared and Dedicated respectively) • when D2 ≤ Ki: Ri (D2 ≤ Ki) = pi D2 – aiKi • when D2>Ki: • Reprovisioning Ability: • A fraction “α” of the excess demand can be accommodated User contribution Capacity cost • Ri (D2 > Ki) = (pi – ai )(Ki + α(D2 - Ki)) • A word about reprovisioning ability, α • Independent of the magnitude of excess demand • Captures feasibility of and latency in securing additional resources • So what do α =0 and α =1mean? S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 28
Solution (2): Capacity Allocation Stage • Expected Revenue, E(Ri|Ki), for a given provisioned level Ki: • Optimal Provisioning Capacity: • For demand distribution ~U[0, D2max]: S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 29
Solution (3): Infrastructure Choice Stage • Dedicated Networks: • Service 1 revenue: • Service 2 revenue under optimal provisioning: • Total profit: • Shared Network: • Infrastructure Choice: • Common if , else separate Profit from Service 2 Profit from Service 1 S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 30
Choice of Infrastructure • Impact of system parameters: • Varying cost parameters affect the choice of infrastructure • Shared to Dedicated (or Dedicated to Shared) • Single threshold for switching n/w choice • Surprisingly, ad-hoc “reprovisioning” ability also impacts in even more interesting ways! • Common is preferred over separate when Depends on provisioningdecision Independent of provisioning decision h(α)= Diff. in optimal capacity cost Function of pi, ai, α, i={s2,d2} S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 31
Analyzing the effect of αon h(α) • Proposition 1: Increase in α benefits both shared and dedicated networks. • (i) if increases in α benefits shared (dedicated) n/w more than dedicated (shared) • (ii) if increases in α benefits shared (dedicated) more at low α and dedicated (shared) more at high α • The value of h'(0) and h'(1) fully characterize the shape of h(α) Return on Capacity Gross Profit Margin S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 32
Results: Impact of Reprovisioning GPMded(pd2-ad2) is sufficiently lower than GPMshr(ps2-as2) GPMded> GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded<ROCshr i.e. (pd2/ad2) <(ps2/as2) GPMded> GPMshr i.e. (pd2-ad2) >(ps2-as2) and ROCded>ROCshr i.e. (pd2/ad2) >(ps2/as2) S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 33
Developed a generic model that captures economies and diseconomies of scope between shared and dedicated networks Reprovisioning can affect the outcome in non-intuitive ways Validates the need for models to incorporate this feature Yields guidelines on how reprovisioning affects choice of architecture Identified key operational metrics to consider Provided decision guideline Whether α has an effect depends on The sign of the derivative h'(α) Use the two metrics to identify operational region The magnitude of γ (how far from zero) Outcomes: zero, one or two switches in network choice Conclusions S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 35
Network Technology Adoption: Different User Preference (θ) Non-uniform distribution positively & negatively skewed β-distribution) Extended to externality benefits (i.e. θβx instead of θq+βx) Alternative Externality Models Non-linear externalities Sublinear: xα, 0 < α < 1 Superlinear: xα, α > 1 Logarithmic: log(x+1) Pure externalities (no intrinsic technology values, q≈1) Presence of Switching costs, Learning costs Network Infrastructure Choice: Different Demand Distribution Non-uniform distribution positively & negatively skewed β-distribution) Economies and diseconomies of scale Different reprovisioning abilities for shared and dedicated networks (α1, α2 ≠α) Closing Remarks: On Robustness S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 36
Network Technology Adoption: S. Sen, Y. Jin, R. Guerin and K. Hosanagar. Modeling the Dynamics of Network Technology Adoption and the Role of Converters. IEEE/ACM Transactions on Networking. 2010 S. Sen, Y. Jin, R. Guerin and K. Hosanagar. Technical Report: Modeling the Dynamics of Network Technology Adoption and the Role of Converters. Technical Report. June, 2009. Available at http://repository.upenn.edu/ese papers/496/. Y. Jin, S. Sen, R. Guerin, K. Hosanagar and Zhi-Li Zhang. Dynamics of competition between incumbent and emerging network technologies. In Proc. Of ACM NetEcon'08, pp.49-54, Seattle, WA, 2008. Network Infrastructure Choice: (4) S. Sen, R. Guerin and K. Hosanagar. Shared Versus Separate Networks - The Impact of Reprovisioning. In Proc. ACM ReArch'09, Rome, Italy, December 2009. S. Sen, K. Yamauchi, R. Guerin and K. Hosanagar. The Impact of Reprovisioning on the Choice of Shared versus Dedicated Networks, Proc. of Ninth Workshop on E-business, WEB, St. Louis, MO, December 2010. Bibliography Thank You! S. Sen On the Adoption and Deployment of New Network Technologies: An Economic Perspective 38