Transcript iDEAL: Incentivized Dynamic Cellular Offloading via Auctions Wei Dong1 Joint work with Swati Rallapalli1, Rittwik Jana2, Lili Qiu1, K.

iDEAL: Incentivized Dynamic Cellular
Offloading via Auctions
Wei Dong1
Joint work with
Swati Rallapalli1, Rittwik Jana2, Lili Qiu1, K. K. Ramakrishnan2,
Leonid V. Razoumov2,Yin Zhang1, Tae Won Cho2
1The
University of Texas at Austin
2 AT&T Labs – Research
1
INFOCOM 2013
Motivation
 Cellular network overloaded
Traffic is highly dynamic
Time (s)
Cellular demand variation
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Large peak-to-average traffic
ratio
• Over 5 times in this
example
=>
Too costly to provision based
on the peak demand
Alternative?
 ISPs augment cellular networks on their own
 Wi-Fi
 Femtocell
 Insufficient as a long-term solution
 High deployment cost
 High management cost
 Interferes with existing infrastructure
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Our approach
 Cellular provider purchases bandwidth on
demand from 3rd party resources
 Wi-Fi, femtocell, or other cellular resources
 Incentivize cellular offloading via auctions
 Effective price discovery
 Avoids long-term contracts
 Cut cost by leveraging the competition
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Unique challenges
 Diverse spatial coverage
 Traffic uncertainty
 Non-truthful bidding and collusion
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Cellular offloading as a reverse auction
 Auction conducted periodically
 Cellular provider (A): buyer
 Hotspots: sellers
A
 Hotspots submit bids
 Cellular provider (A) serves as
auctioneer
 A sector is divided into regions based
on location of hotspots
 Objective: satisfy A’s traffic while
minimizing the total cost
 Cost = cellular cost + hotspots cost
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R1
R2
R3
Naïve solution
Limited competition
R1
R2
Auction 2
Demand 2
Auction 1
Demand 1
Cellular resource
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Cellular resource as a virtual bidder

Inter-region competition
iDEAL overview
 Two phases of iDEAL
 Allocation: determine how to allocate cellular
resources and 3rd party resources to minimize cost
 Pricing: determine payment to 3rd party
resource owners
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Global static allocation
 Input: di, ei, λj, pj, F(z)
 Output: xj, ci, z
𝑗 𝑝𝑗
 Minimize:
∗ 𝑥𝑗 + 𝐹(𝑧)
Total cost: Wi-Fi + cellular
 Subject to:
 [C1]
 [C2]
𝑗:𝑓 𝑗 =𝑖 𝑥𝑗 + 𝑐𝑖
𝑚 𝑐𝑖
𝑖=1 𝑒 = 𝑧
𝑖
= Satisfy
𝑑𝑖 ∀𝑖
= 1,2,
…both
, 𝑚Wi-Fi and cellular
the demand
with
Translate cellular resource usage into spectrum
 [C3] 0 ≤ 𝑥𝑗 ≤ λ𝑗 ∀𝑗 = 1,2,Never
… , 𝑛buy more than offered
 [C4] 0 ≤ 𝑐𝑖 ∀𝑖 = 1,2, … , 𝑚
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Global dynamic allocation
 Traffic in different regions may peak at different times
 Have multiple possible demand vectors
 Optimize for the worst case
 [C1-dynamic]
 [C2-dynamic]
𝑗:𝑓 𝑗 =𝑖 𝑥𝑗 + 𝑐𝑖𝑘 =
𝑚 𝑐𝑖𝑘
𝑖=1 𝑒 = 𝑧 ∀𝑘
𝑑𝑘𝑖 ∀𝑘 𝑎𝑛𝑑 𝑖
𝑖
 Benefits
 Efficiently leverage cellular resource on demand
 Avoid provisioning for the peak in each region
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iDEAL pricing
 VCG principle
 Pay the winners the opportunity cost
 Payment to winner w = the extra amount that other bidders could
sell if w is not present
 iDEAL pricing
 Apply VCG over the whole sector as one auction
 Global opportunity cost
 Captures inter- and intra-region competition
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iDEAL pricing: Example
r: amount of resource
v: valuation of a single unit
d: demand
Allocation if 1 is
not there
r:1 v:$1.5
Optimal
allocation
Consider hotspot 1
Value sold by
others: $1.5
The “local
opportunity
cost” is $9
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Value sold by
others: $3.5
1
r:1 v:$1
3
r:1 v:$9
Region 1 (d: 1)
2
r:1 v:$2
Global
opportunity
cost: $2
Region 2 (d:1)
1. Global opportunity cost captures inter-region competition and lowers cost
2. Payment is higher than bid
Economic properties
 Theorem 1: Truth-telling is optimal.
 Theorem 2: iDEAL is efficient (i.e., winners are the
bidders with lowest valuation).
 Theorem 3: iDEAL is individually rational (i.e.,
bidders of the auction will get non-negative utility).
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Understand collusions
 Collusion strategies
 Single seller collusion
 Multi seller collusion
 In both cases, they use Supply Reduction
 Drop losing bids
 Reduce the capacity offered in winning bids
 Supply reduction: increases the opportunity cost 
drives up price
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Mitigating collusions
 Dynamic demands make collusion hard
 Inaccurate traffic prediction  supply reduction may lead
to missed winning opportunities
 Bidding as a group
 Hotspots owned by same party  bid as group 
considered one bidder
 Removes competition within a group
 no incentive for supply reduction
 Inter-group competition retained
 Multi seller collusion is unstable
 Seller has incentive to leave the bidding ring
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Evaluation methodology
Sector reports
# of users
Event driven trace player
3G HTTP sessions
Detailed aggregated traffic demand
Sector location
Clustering
Regions
Hotspot location
Pricing plan of major ISPs
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Bids
Auctions
Comparison of truthful auctions
40 hotspots
130 hotspots
1. Auction based approaches much better than fixed pricing given enough competition
2. iDEAL consistently beats other auction based approaches
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Comparison of truthful auctions (cont.)
40 hotspots
130 hotspots
1. Global allocation efficiently allocates cellular resource to different regions.
2. Dynamic global allocation avoids provisioning for peak demand in each region.
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0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
First price (KF 0.2)
First price (KF 0.5)
First price (KF 0.8)
Uniform price
iDEAL (static)
iDEAL
0
10
20
Round
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30
Total cost
Total value consumption
Comparison of non-truthful auctions
40
50
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
First price (KF 0.2)
First price (KF 0.5)
First price (KF 0.8)
Uniform price
iDEAL (static)
iDEAL
0
10
20
30
Round
Value consumption
Cost
1. Non-truthful auctions invites gaming behaviors
2. Gaming causes fluctuation and can increase cost
3. VCG in iDEAL is stable, efficient and low-cost
40
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Collusion under dynamic demands
• Used two different sizes of bidding ring: 20 and 50
50: 28% chance of higher utility
20: 5% chance
Significantly weakens the
incentive to collude
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Collusion: Bidding as a group
40 hotspots
130 hotspots
Group bidding removes competition between a seller’s own hotspots and
maintains the competition between different sellers, thus reducing the cost
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Conclusion
 Design incentive framework for cellular offload
 Explicitly account for diverse spatial coverage of different resources
 Cope with dynamic traffic
 Promote truthfulness
 Provably efficient
 Guard against collusions
 Trace-driven simulations show iDEAL is efficient, low-cost and
robust against collusion
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Q&A
Thank you
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Backup slides
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Practical Considerations
 Supporting offloading to femtocells and dynamic roaming
 The same framework applies to purchasing femtocells and other
cellular resources
 Handle partially overlapping spatial coverage
 Revise the constraint [C1] to split the resources from the same
provider into different regions
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Related Work
 Measurement
 Balasubramanian et al. report Wi-Fi is available for 11% time and 3G is
available for 87% time but they are negatively correlated
 Lee et al. find Wi-Fi offload 65% traffic without delay and 83% with
over 1-hour delay
 Auction based offloading
 Zhou et al. uses auction to incentivize mobile users to wait until they
reach Wi-Fi
 Chen et al. uses auction to incentivize femtocell owners to share
resources
 Ignore three unique challenges iDEAL addresses
 Similar to local allocation in spirit
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Design Goals
 Account for different spatial coverage of resources
 Achieve high efficiency
 Promote truthful bidding
 Low cost
 Guard against collusion
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Mitigating Collusions (Cont.)
 Stability of a multi-seller collusion
 Without utility sharing, a seller has no incentive to conduct supply
reduction
 Follows from the truthfulness of VCG and that in our system sellers
submit sealed, separated bids
 Utility sharing is hard to achieve in our system
 Hard to attribute utility change to collusion
Demand and Wi-Fi availability is dynamic
 Hard to validate other bidders’ behavior
 Sellers submit sealed separately bids
 Can make it even harder via system design
 E.g. use delayed payment to further obfuscate the utility

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Supporting Femtocell Offload
Benefit of femtocells is
large when there are
fewer Wi-Fi hotspots
16 femtocells
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Supporting Dynamic Roaming
When Wi-Fi is
insufficient, dynamic
roaming can
significantly cut down
cost even with a small
amount of capacity
40 hotspots
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Implementation
 Dynamic offloading involves three steps
 Identify a network to offload
 Solved by iDEAL
 Automatic authentication
 Solved by Hotspot 2.0
 The roaming partners are updated dynamically according to the offload
decision from iDEAL.
 Seamless offload to maintain the existing sessions
 Addressed by Dual Stack Mobile IP (DSMIP), DSMIPv6, …
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System Architecture
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