Background of Network Economics

Wireless communication networks over time have evolved from a simple and small-scale system with the centralized control into a highly complex and large-scale system, operated and maintained by various decentralized and self-interested network entities. Along with this evolution, traditional network optimization technologies based on pure engineering considerations often fail to get implemented, due to the lack of incentive to reconcile the conflict of interest (or competition) among various entities. As a consequence, economic incentive emerges as an increasingly important issue in the network design and optimization. At the same time, new emerging wireless access technologies and network architectures, such as cognitive radio networks and cellular-WiFi internetworks, usually require the cooperation of various network entities (e.g., cooperative spectrum sharing between primary users and secondary users, and cooperative interconnection between cellular networks and WiFi networks). Promoting cooperation among various self-interested network entities also bring economic incentive issues to the fore.

My main research interests lie in the area of wireless communications and networking, in particular, the economic incentives in various communication and network scenarios, including cooperative communications, cognitive radio networks, TV white space networks, cellular-WiFi internetworks, and user-provided networks. My graduate and postdoctoral researches focus on the network economics, mainly including the game-theoretic and economic modeling and analysis of communication network problems. In particular,

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  1. Dynamic Spectrum Sharing for Cognitive Radio Networks
    (PhD Research, May 2007 - July 2010)
  2. Secondary Spectrum Market for Cognitive Radio Networks
    (PhD Research, May 2008 - July 2010)
  3. Cooperative Spectrum Sharing for Cognitive Radio Networks
    (PhD and Postdoctoral Research, June 2009 - Oct. 2012)
  4. Integrated Spot and Futures Spectrum Market Modeling and Analysis
    (Postdoctoral Research, Oct. 2010 - Jan. 2013)
  5. TV White Space Network and White Space Ecosystem
    (Postdoctoral Research, Nov. 2011 - Present)
  6. Cellular-WiFi Inter-Networking (Mobile Data Offloading)
    (Postdoctoral Research, March 2012 - Present)
  7. User-Provided Networking (Crowd-sourced Internet Access)
    (Postdoctoral Research, April 2013 - Present)

Selected Research Topics

7. User-Provided Networking (Crowd-sourced Internet Access)

(Postdoctoral Research in CUHK, Hong Kong, April 2013 - Present)
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Nowadays we are witnessing an unprecedented worldwide growth of mobile cellular data traffic, which is expected to reach 15.9 exabytes per month by 2018, nearly an 11-fold increase over 2013. However, traditional network expansion methods such as acquiring more spectrum licenses, deploying new macrocells of small size, and upgrading access technologies are costly and time-consuming. Clearly, cellular network operators need to find novel methods to resolve the mismatch between demand and supply growth. User-provided networking, also called user-centric networking, appears as one of the attractive solutions, where mobile users act as hotspots (hosts) providing internet connectivities for others (clients). In this project, we study the economic incentive for host users to share their internet connections with client users. We also study a more general crowd-soruced mobile internet access model, where each user can act as host, relay, and client at the same time.

  • Selected Publications:

  1. Lin Gao, G. Iosifidis, J. Huang, and L. Tassiulas, "Hybrid Data Pricing for Network-Assisted User-Provided Connectivity," IEEE International Conference on Computer Communications (INFOCOM), Toronto, Canada, April 2014 [ Slides]
  2. G. Iosifidis, Lin Gao, J. Huang, and L. Tassiulas, "Enabling Crowd-Sourced Mobile Internet Access," IEEE International Conference on Computer Communications (INFOCOM), Toronto, Canada, April 2014 [ Slides]
  3. G. Iosifidis, Lin Gao, J. Huang, and L. Tassiulas, "Incentive Mechanisms for User-Provided Networks," IEEE Communications Magazine, vol.52, no.9, pp.20-27, September 2014 (IF:5.125)
  4. Lin Gao, F. Hou, and J. Huang, "Providing Long-Term Participation Incentive in Participatory Sensing," IEEE International Conference on Computer Communications (INFOCOM), Hong Kong, 2015 [ Slides]
  5. Q. Ma, Lin Gao, Y.F. Liu, and J. Huang, "A Game-Theoretic Analysis of User Behaviors in Crowdsourced Wireless Community Networks," International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Mumbai, Indian, May 2015 (Best Student Paper Award)
  6. H. Yu, M. Cheung, Lin Gao, and J. Huang, "Economics of Public Wi-Fi Monetization and Advertising," IEEE International Conference on Computer Communications (INFOCOM), San Francisco, USA, April 2016 (Best Paper Award Finalist) (Rank top 5 among all 300 accepted papers in INFOCOM 2016)
  7. Q. Ma, Lin Gao, Y.F. Liu, and J. Huang, "Economic Analysis of Crowdsourced Wireless Community Networks," IEEE Transactions on Mobile Computing (TMC), 2016 (IF:3.822) (Corresponding Author)
  8. M. Zhang, Lin Gao, J. Huang, and M. Honig, "Cooperative and Competitive Operator Pricing for Mobile Crowdsourced Internet Access," accepted by IEEE International Conference on Computer Communications (INFOCOM), Atlanta, GA, USA, May 2017
  9. M. Tang, S. Wang, Lin Gao, J. Huang, and L. Sun, "MOMD: A Multi-Object Multi-Dimensional Auction for Crowdsourced Mobile Video Streaming," accepted by IEEE International Conference on Computer Communications (INFOCOM), Atlanta, GA, USA, May 2017
  10. M. Tang, Lin Gao, H. Pang, J. Huang, and L. Sun, "Optimizations and Economics of Crowdsourced Mobile Streaming," to appear in IEEE Communications Magazine, 2017 (IF:5.125)
  11. H. Yu, M.H. Cheung, Lin Gao, and J. Huang, "Public Wi-Fi Monetization via Advertising," to appear in IEEE/ACM Transactions on Networking (TON), 2017 (IF:3.376)
  12. C. Jiang, Lin Gao, L. Duan, and J. Huang, "Scalable Mobile Crowdsensing via Peer-to-Peer Data Sharing," to appear in IEEE Transactions on Mobile Computing (TMC), 2017 (IF:3.822)
  13. C. Jiang, Lin Gao, L. Duan, and J. Huang, "Data-Centric Mobile Crowdsensing," to appear in IEEE Transactions on Mobile Computing (TMC), 2017 (IF:3.822)

6. Cellular-WiFi Inter-Networking (Mobile Data Offloading)

(Postdoctoral Research in CUHK, Hong Kong, March 2012 - Present)
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Cellular-WiFi inter-networking is another promising approach to alleviate the cellular network congestion problem. A typical cellular-WiFi inter-networking scheme is mobile data offloading. Simply speaking, mobile data offloading is the use of complementary network technologies, such as WiFi and femtocell, for delivering data traffic originally targeted for cellular networks. The benefit of data offloading through WiFi networks (also called WiFi offloading) has been studied and quantified using real data traces in existing literature, and it is shown that in a typical urban environment, WiFi can offload about 65% cellular traffic and save 55% battery energy for mobile users. This performance gain can be further enlarged with the use of delaying transmission and the prediction of WiFi availability. However, the existing results focus only on the technical aspect of WiFi offloading, without considering the economic incentive for WiFi network operators to admit cellular traffic. This incentive issue is particularly important for the scenario where WiFi networks are privately operated by third-party entities, who are expected to be reluctant to admit non-registered cellular traffic without proper incentives. In this project, we study the necessary economic incentives that cellular network operators need to provide for WiFi operators in order to encourage such a cooperative data offloading.

  • Selected Publications:

  1. Lin Gao, G. Iosifidis, J. Huang, and L. Tassiulas, "Economics of Mobile Data Offloading," IEEE Workshop on Smart Data Pricing (SDP) (co-located with IEEE INFOCOM), Turin, Italy, April 2013
  2. G. Iosifidis, Lin Gao, J. Huang, and L. Tassiulas, "An Iterative Double Auction for Mobile Data Offloading," International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Tsukuba Science City, Japan, May 2013 (Best Paper Award) [ Slides]
  3. G. Iosifidis, Lin Gao, J. Huang, and L. Tassiulas, "A Double Auction Mechanism for Mobile Data Offloading Markets," IEEE/ACM Transactions on Networking (TON), vol.23, no.5, pp.1634-1647, September 2014 (IF:3.376)
  4. Lin Gao, G. Iosifidis, J. Huang, L. Tassiulas, and D. Li, "Bargaining-based Mobile Data Offloading," IEEE Journal on Selected Areas in Communications (JSAC), vol.32, no.6, pp.1114-1125, June 2014 (IF:8.085) [ arXiv] [ Slides]
  5. G. Iosifidis, Lin Gao, J. Huang, and L. Tassiulas, "Efficient and Fair Collaborative Mobile Internet Access," to appear in IEEE/ACM Transactions on Networking (TON), 2016 (IF:3.376)

5. TV White Space Network and White Space Ecosystem

(Postdoctoral Research in CUHK, Hong Kong, Nov. 2011 - Present)
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TV white space network is one of the most promising commercial realizations of dynamic spectrum sharing and cognitive radio, where unlicensed white space devices (WSDs) explore and exploit the unused or under-utilized broadcast television spectrum (called TV white spaces) via a third-party white space geo-location database. This database-driven network archecture, instead of sensing-based, has been supported by many spectrum regulatory bodies (e.g., FCC in the US and OFCOM in the UK), standardization organizations (e.g., IEEE and ECC), and major IT companies (e.g., Google, Microsoft, and SpectrumBridge). The long-term success of such networks requires the coordination and cooperation of all involved parties, including spectrum licensees, white space databases, secondary operators, and end-users, which form the White Space Ecosystem. While most of the existing studies focused on the technical issues in deploying a database-driven white space database network, we consider in this project the economic issue in operating such a network. More specifically, we propose and analyze two different market models for this incentive issue: white space market and information market.

  • Selected Publications:

  1. Y. Luo, Lin Gao, and J. Huang, "Spectrum Broker by Geo-location Database," IEEE Global Communications Conference (GLOBECOM), Anaheim, USA, December 2012
  2. Y. Luo, Lin Gao, and J. Huang, "White Space Ecosystem: A Secondary Network Operator's Perspective," IEEE Global Communications Conference (GLOBECOM), Atlanta, USA, December 2013
  3. Y. Luo, Lin Gao, and J. Huang, "Trade Information, Not Spectrum: A Novel TV White Space Information Market Model," International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt), Hammamet, Tunisia, May 2014 (Best Paper Award) [ Slides]
  4. Y. Luo, Lin Gao, and J. Huang, "Information Market for TV White Space," IEEE Workshop on Smart Data Pricing (SDP) (co-located with IEEE INFOCOM) (invited), Toronto, Canada, May 2014 [ Slides]
  5. Y. Luo, Lin Gao, and J. Huang, "Price and Inventory Competition in Oligopoly TV White Space Markets," IEEE Journal on Selected Areas in Communications (JSAC), vol.33, no.5, pp.1002-1013, October 2014 (IF:8.085)
  6. Y. Luo, Lin Gao, and J. Huang, "Business Modeling for TV White Space Networks," IEEE Communications Magazine, vol.53, no.5, pp.82-88, May 2015 (IF:5.125)
  7. Y. Luo, Lin Gao, and J. Huang, "HySIM: A Hybrid Spectrum and Information Market for TV White Space Networks," IEEE International Conference on Computer Communications (INFOCOM), Hong Kong, 2015
  8. Y. Luo, Lin Gao, and J. Huang, "Spectrum Reservation Contract Design in TV White Space Networks," IEEE Transactions on Cognitive Communications and Networks (TCCN) (invited), vol.1, no.2, pp.147-160, November 2015
  9. Y. Luo, Lin Gao, and J. Huang, "MINE GOLD to Deliver Green Cognitive Communications," IEEE Journal on Selected Areas in Communications (JSAC), vol.33, no.12, pp.2749-2760, December 2015 (IF:8.085)
  10. Y. Luo, Lin Gao, and J. Huang, "An Integrated Spectrum and Information Market for Green Cognitive Communications," IEEE Journal on Selected Areas in Communications (JSAC), 2016 (IF:8.085)

4. Integrated Spot and Futures Spectrum Market Modeling and Analysis

(Postdoctoral Research in CUHK, Hong Kong, Oct. 2010 - Jan. 2013)
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Futures market and Spot market are two of the widely-used and well-studied market forms in practice. The futures market insures buyers against uncertainties of future supply through predefined contracts, while the spot market allows buyers to compete for goods based on their real-time demands and preferences. A hybrid market combining the futures and spot markets has both the reliability of the futures market and the flexibility of the spot market, and thus is highly non-trivial for quality of service (QoS) differentiations in dynamic spectrum access. Specifically, a mobile user with elastic services (e.g., file transferring) may be more interested in spot transactions to achieve flexible resource-price tradeoff, while a mobile user with inelastic services requiring a minimum data rate (e.g., video streaming and VoIP) may prefer the certainty of contract in the futures market. In this project, we study the optimal trading mechanism in a hybrid secondary spectrum market with a monopoly PU (seller) and multiple SUs (buyers). We propose an integrated contract and auction design-ContrAuction, which achieves the optimal spectrum allocation among spot market users with elastic application/demand and contract users with inelastic application/demand..

  • Selected Publications:

  1. Lin Gao, J. Huang, Y. Chen, and B. Shou, "ContrAuction: An Integrated Contract and Auction Design for Dynamic Spectrum Sharing," IEEE Conference on Information Sciences and Systems (CISS) (invited), Princeton, NJ, USA, March 2012 [ Slides]
  2. Lin Gao, J. Huang, Y. Chen, and B. Shou, "An Integrated Contract and Auction Design for Secondary Spectrum Trading," IEEE Journal on Selected Areas in Communications (JSAC), vol.31, no.3, pp.581-592, March 2013 (IF:8.085)
  3. Lin Gao, B. Shou, Y. Chen, and J. Huang, "Combining Spot and Futures Markets: A Hybrid Market Approach to Dynamic Spectrum Access," Operations Research, 2016 (IF:1.777) (A+ Journal in OR & MS)

3. Cooperative Spectrum Sharing for Cognitive Radio Networks

(PhD Research in SJTU, China and Postdoctoral Research in CUHK, Hong Kong, June 2009 - Oct. 2012)
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Radio spectrum is becoming more congested and scarce with the explosive development of wireless services and networks. At the same time, however, many frequency bands are largely under-utilized by their legal licensees (e.g., the average spectrum occupancy is less than 25% in the UHF/VHF licensed for broadcast television service). Cognitive radio emerges as a promising paradigm to improve spectrum efficiency and alleviate spectrum scarcity, by allowing unlicensed secondary users access the licensed spectrum opportunistically. The successful deployment of cognitive radio networks requires economic incentives both for primary users (PUs) to open their licensed spectrum for secondary sharing, and for secondary users (SUs) to utilize the new spectrum opportunities after considering potential costs. Cooperative spectrum sharing is a promising approach to address these incentive issues through the cooperation of PUs and SUs. The key idea is to offer incentives for both PUs and SUs using the resource exchange between PUs and SUs, that is, SUs relay traffics for PUs (with their limited power) in exchange for the access time on PUs' spectrum.

  • Selected Publications:

  1. H. Wang, Lin Gao, X. Gan, X. Wang, and E. Hossain, "Cooperative Spectrum Sharing in Cognitive Radio Networks: A Game-Theoretic Approach," IEEE International Conference on Communications (ICC), South Africa, May 2010
  2. L. Duan, Lin Gao, and J. Huang, "Contract-Based Cooperative Spectrum Sharing," IEEE Dynamic Spectrum Access Networks (DySPAN), Aachen, Germany, May 2011
  3. L. Duan, Lin Gao, and J. Huang, "Cooperative Spectrum Sharing: A Contract-based Approach," IEEE Transactions on Mobile Computing (TMC), vol.13, no.1, pp.174-187, January 2014 (IF:3.822) (ESI Highly Cited Paper)
  4. Z. Zheng, Lin Gao, L. Song, and J. Huang, "Topology Effect in Cooperative Relay Networks," IEEE Global Communications Conference (GLOBECOM), San Diego, USA, December 2015
  5. Lin Gao, L. Duan, and J. Huang, "Two-Sided Matching Based Cooperative Spectrum Sharing," IEEE Transactions on Mobile Computing (TMC), 2016 (IF:3.822)

2. Secondary Spectrum Market for Cognitive Radio Networks

(PhD Research in SJTU, China, May 2008 - July 2010)
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Market-driven dynamic spectrum access, also called dynamic spectrum trading or secondary spectrum market, is one of the most promising approaches to address the incentive issues in cognitive radio networks. With dynamic spectrum trading, PUs temporarily lease the under-utilized spectrum to SUs for additional profits. Thus, with a proper design of the trading machanism, PUs have the incentive to open their licensed spectrum for secondary sharing, and SUs also have the incentive to utilize the new spectrum opportunities. In this project, we study dynamic spectrum trading mechanisms under different market scenarios.

  • Selected Publications:

  1. Lin Gao, X. Wang, Y. Xu, and Q. Zhang, "Spectrum Trading in Cognitive Radio Networks: A Contract-Theoretic Modeling Approach," IEEE Journal on Selected Areas in Communications (JSAC), vol.29, no.4, pp.843-855, April 2011 (IF:8.085)
  2. Lin Gao, Y. Xu, and X. Wang, "MAP: Multi-Auctioneer Progressive Auction for Dynamic Spectrum Access," IEEE Transactions on Mobile Computing (TMC), vol.10, no.8, pp.1144-1161, November 2011 (IF:3.822)
  3. L. Qian, F. Ye, Lin Gao, X. Gan, et al., "Spectrum Trading in Cognitive Radio Networks: An Agent-based Model under Demand Uncertainty," IEEE Transactions on Communications (TCOM), vol.59, no.11, pp.3192-3203, October 2011 (IF:4.058)

1. Dynamic Spectrum Sharing for Cognitive Radio Networks

(PhD Research in SJTU, China, May 2007 - July 2010)
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Radio spectrum is the single most important resource in wireless communications, yet it is a limited and scarce resource. Thus, spectrum efficient utilization is an important issue in wireless networks. This issue is particularly important and challenging in decentralized networks with open sharing protocols (e.g., 802.11 WLAN and cognitive radio networks), where self-interested mobile devices compete for spectrum openly. In such networks, proper economic incentive is necessary to reconcile the competing interests among various devices, and further to avoid the free-rider problem. In this project, we focus on the game-theoretic modeling and analysis of dynamic spectrum open sharing under different network scenarios.

  • Selected Publications:

  1. Lin Gao, and X. Wang, "A Game Approach for Multi-Channel Allocation in Multi-Hop Wireless Networks," ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), Hong Kong, May 2008
  2. Lin Gao, X. Wang, and Y. Xu, "Multiradio Channel Allocation in Multihop Wireless Networks," IEEE Transactions on Mobile Computing (TMC), vol.8, no.11, pp.1454-1468, May 2009 (IF:3.822)
  3. H. Yu, Lin Gao, Z. Li, X. Wang, and E. Hossain, "Pricing for Uplink Power Control in Cognitive Radio Networks," IEEE Transactions on Vehicular Technology (TVT), vol.59, no.4, pp.1769-1778, January 2010 (IF:2.243)
  4. Lin Gao, X. Wang, G. Sun, and Y. Xu, "A Game Approach for Cell Selection and Resource Allocation in Heterogeneous Wireless Networks," IEEE International Conference on Sensing, Communication, and Networking (SECON), Utah, USA, June 2011