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Wei Dong 1 Joint work with Swati Rallapalli 1, Rittwik Jana 2, Lili Qiu 1, K. K. Ramakrishnan 2, Leonid V. Razoumov 2, Yin Zhang 1, Tae Won Cho 2 1 The.

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Presentation on theme: "Wei Dong 1 Joint work with Swati Rallapalli 1, Rittwik Jana 2, Lili Qiu 1, K. K. Ramakrishnan 2, Leonid V. Razoumov 2, Yin Zhang 1, Tae Won Cho 2 1 The."— Presentation transcript:

1 Wei Dong 1 Joint work with Swati Rallapalli 1, Rittwik Jana 2, Lili Qiu 1, K. K. Ramakrishnan 2, Leonid V. Razoumov 2, Yin Zhang 1, Tae Won Cho 2 1 The University of Texas at Austin 2 AT&T Labs – Research INFOCOM 2013 iDEAL: Incentivized Dynamic Cellular Offloading via Auctions 1

2 Motivation 2 Cellular network overloaded Traffic is highly dynamic Large peak-to-average traffic ratio Over 5 times in this example => Too costly to provision based on the peak demand Time (s) Cellular demand variation

3 Alternative? 3 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

4 Our approach 4 Cellular provider purchases bandwidth on demand from 3 rd 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

5 Unique challenges Diverse spatial coverage Traffic uncertainty Non-truthful bidding and collusion 5

6 Cellular offloading as a reverse auction 6 Auction conducted periodically Cellular provider (A): buyer Hotspots: sellers 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 R1 R2 R3 A

7 Naïve solution 7 Auction 1 Demand 1 Auction 2 Demand 2 Limited competition Cellular resource Cellular resource as a virtual bidder  Inter-region competition R1R2

8 iDEAL overview 8 Two phases of iDEAL Allocation: determine how to allocate cellular resources and 3 rd party resources to minimize cost Pricing: determine payment to 3 rd party resource owners

9 Global static allocation 9 Satisfy the demand with both Wi-Fi and cellular Translate cellular resource usage into spectrum Never buy more than offered Total cost: Wi-Fi + cellular

10 Global dynamic allocation 10

11 iDEAL pricing 11 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

12 iDEAL pricing: Example Region 1 (d: 1) Region 2 (d:1) r:1 v:$1 r:1 v:$9 r:1 v:$2 r:1 v:$1.5 Optimal allocation Allocation if 1 is not there Value sold by others: $3.5 Global opportunity cost: $2 The “local opportunity cost” is $9 r: amount of resource v: valuation of a single unit d: demand 1.Global opportunity cost captures inter-region competition and lowers cost 2.Payment is higher than bid Consider hotspot 1 Value sold by others: $1.5

13 Economic properties 13 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).

14 Understand collusions 14 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

15 Mitigating collusions 15 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

16 Evaluation methodology 16 Sector reports 3G HTTP sessions # of users Event driven trace player Detailed aggregated traffic demand Sector location Hotspot location Clustering Regions Pricing plan of major ISPs Bids Auctions

17 Comparison of truthful auctions 17 1.Auction based approaches much better than fixed pricing given enough competition 2.iDEAL consistently beats other auction based approaches 40 hotspots130 hotspots

18 40 hotspots130 hotspots Comparison of truthful auctions (cont.) 18 1.Global allocation efficiently allocates cellular resource to different regions. 2.Dynamic global allocation avoids provisioning for peak demand in each region.

19 Comparison of non-truthful auctions 19 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

20 Collusion under dynamic demands 20 50: 28% chance of higher utility 20: 5% chance Significantly weakens the incentive to collude Used two different sizes of bidding ring: 20 and 50

21 Collusion: Bidding as a group 21 Group bidding removes competition between a seller’s own hotspots and maintains the competition between different sellers, thus reducing the cost 40 hotspots130 hotspots

22 Conclusion 22 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

23 Q&A Thank you 23

24 Backup slides 24

25 Practical Considerations 25 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

26 Related Work 26 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

27 Design Goals Account for different spatial coverage of resources Achieve high efficiency Promote truthful bidding Low cost Guard against collusion 27

28 Mitigating Collusions (Cont.) 28 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

29 Supporting Femtocell Offload 29 Benefit of femtocells is large when there are fewer Wi-Fi hotspots 16 femtocells

30 Supporting Dynamic Roaming 30 When Wi-Fi is insufficient, dynamic roaming can significantly cut down cost even with a small amount of capacity 40 hotspots

31 Implementation 31 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, …

32 System Architecture 32

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