Embed Size (px)
Citation preview
May 4, 2012 Bell Labs, Crawford Hill
Time-Dependent Pricing of Mobile Data
Soumya Sen
Princeton University
Joint work with:
Sangtae Ha, Carlee-Joe Wong, Mung Chiang
I. Motivation
Wireless Internet Usage Trends
Mobile data growing at 78% annually
Driving Forces
Mobile Video
CloudSync
Data-hungryApps
High-resDevices
A PerfectStorm
Ultra-Heavy Tail
ISP cost structure’s fundamental problem
But Not Heavy All the Time
Large Peak-Valley Differential
Time Elasticity: Opportunities
Time Elasticity
Volu
me
Streamingvideos,Gaming
Texting,Weather, Finance
Email,Social
Network updates
Cloud
SoftwareDownloads
Movies & Multimedia downloads,
P2P
Opportunities
Cost Reduction
ISP’s Spectrum, Capital, Operational costs decrease with reduced peak
Time Time
Before After
Ban
dwid
th
Peak
Peak
Ban
dwid
th
Revenue Increase
Time Time
Before After
Ban
dwid
th
$50 for 5 GB $60 for 10 GB
Create win-win by increasing demand
Ban
dwid
th
II. Feasibility Study
Consumer Response
USA: Online Survey, 130 participants, 25 states
India: Face-to-face Surveys: 550 participants, 5 cities Professionals (36%), Students (36%), Self-employed (8%),
housewives (6%), unemployed (12%)
Time Elasticity: Survey Results
YouTube streaming Downloads
Many applications are time-elastic
Policy Feasibility
FCC Dec. 2010 Statement“...the importance of business
innovation to promote network investment and efficient use of networks, including measures to match price to cost, such as
usage-based pricing”
Industry Moves: US ISPs
Industry Moves: Indian ISPs
Industry Moves: African ISPs
Africa dynamic pricing
Current Practices
✤ Flat Rate, throttling heavy-users
✤ Usage-based Pricing
✤ David Clark, ’95: “The fundamental problem with simple usage fees is that they impose usage costs on users regardless of whether the network is congested or not.”
✤ Dynamic Pricing
✤ MacKie-Mason, ’95: “We argue that a feedback signal in the form of a variable price for network service is a workable tool to aid network operators in controlling Internet traffic. We suggest that these prices should vary dynamically based on the current utilization of network resources.”
History of Pricing Research
Other Markets: Electricity
“Day Ahead” Pricing
* Sen, et al., “A Survey of Broadband Data Pricing: Past Proposals, Current Plans, and Future Trends”, 2012.
III. Challenges
Key Questions
✤ Optimized Price Computation?
✤ Correct Incentives? TUBE Theory
✤ Practical Economic Modeling
✤ System Design Issues
✤ How to assess TDP benefits?
✤ Will real customers respond?TUBE Trial
TUBE System
IV. TUBE Technology
Time Dependent Pricing (TDP)
Large scale ISP cost optimization, taking user reaction into account
ISP’s Optimization Problem
Cost of overshooting
capacity
Cost of rewards
Estimating Waiting Function
Economic modeling
reward
patience indexdelay
waiting function
Patience Index: Initialization
TDP: Shifting Peak to Valley
TDP Performance
V. TUBE Princeton Trial(May 2011-January 2012)
Princeton Trial: Money Flow
• 50 AT&T participants : 27 iPhones, 23 iPads• Faculty, staff, and students• 14 Academic units
TUBE App: Information Screens
TUBE App: Scheduling Screens
VI. Princeton Trial Results
Usage Statistics
✤ How much bandwidth participants use? – ‘Heavy tailed’
✤ Which applications use the most bandwidth? – Video streaming
July-September, 2011
20%75%
Price Sensitivity
✤ Do users wait to use mobile data in return for a monetary discount?
✤ Average usage decrease in high-price periods relative to the changes in low-price periods (iPads: -10% in high-price, 15% in low-price periods)
October 2011
Notification Effectiveness
✤ Do notifications impact usage?
✤ 80-90% of users decrease or did not change their usage after the 1st notification
✤ For all subsequent notifications, about 60-80% of the active users decrease their usage, while the others remained price-insensitive.
iPads iPhones
Psychological Factors
✤ Do users respond more to the numerical values of TDP prices or to the color of the price indicator bar on the home screen?
Period Type 1 and 3 Period Type 1 and 2
Optimized TDP Impact
✤ Does the peak usage decrease with time-dependent pricing? And does this decrease come at the expense of an overall decrease in usage?
✤ Optimized TDP reduce the peak-to-average ratio (max reduction: 30%)
✤ Overall usage increase with TDP (demand gain in valley periods)
Peak-to-Average Ratio Peak Usage Volume
Impact on Web Ecosystem
✤ Does the application usage distribution change due to TDP?
✤ People are motivated to use more bandwidth during low-price periods, “valley filling”.
VII. Post-Trial Survey
Viability
✤ Will you be able to decide on “when” to use?
✤ “I think it's a great idea, ..the iPads would say, 'If you wait a half an hour, you can have...' I thought that was incredibly useful. And I would be able to make that decision.”
✤ Are there apps for which you usually wait?
✤ “[I]f I'm out in my car and I needed it for GPS, I wouldn't care how much money I'm spending… if I just wanted to be on a social network or check my email, I would certainly wait.”
Usefulness
✤ What are your main concerns with TDP?
✤ “If it's predictable, yes, I think so, because let's say I know that definitely everyday from 9 to 10 it's less, then I can plan a little bit.”
✤ Was the color-coded notification bar useful to you?
✤ “I group the colors I would see if it's a good color for me... because I couldn't always figure out what it meant in terms of the dollar amount and translate that into how much I was using”
Opinions
✤ Were you tempted to use more data when the discounts were higher?
✤ “[laughs] Kind of! But that also goes toward my personality of if it's on sale I must buy it!”
✤ Will TDP adversely affect high-bandwidth app developers?
✤ “I don't think this will result in those kinds of applications being developed less, and I think that's because you're giving users the option”
Related Publications:
[1] “TUBE: Time-Dependent Pricing of Mobile Data”, SIGCOMM 2012.
[2] “A Survey of Broadband Data Pricing: Past Proposals, Current Plans, and Future Trends”, under submission in ACM Computing Surveys.
Thank you
http://scenic.princeton.edu/tube/
