Efficient and Fair Collaborative Mobile Internet Access

The surging global mobile data traffic challenges the economic viability of cellular networks and calls for innovative solutions to reduce the network congestion and improve user experience. In this context, user-provided networks (UPNs), where mobile users share their Internet access by exploiting their diverse network resources and needs, turn out to be very promising. Heterogeneous users with advanced handheld devices can form connections in a distributed fashion and unleash dormant network resources at the network edge. However, the success of such services heavily depends on users’ willingness to contribute their resources, such as network access and device battery energy. In this paper, we introduce a general framework for UPN services and design a bargaining-based distributed incentive mechanism to ensure users’ participation. The proposed mechanism determines the resources that each user should contribute in order to maximize the aggregate data rate in UPN, and fairly allocate the benefit among the users. The numerical results verify that the service can always improve users’ performance, and such improvement increases with the diversity of the users’ resources. Quantitatively, it can reach an average 30% increase of the total served traffic for a typical scenario even with only six mobile users.

[1]  Jörg Widmer,et al.  Survey on Energy Consumption Entities on the Smartphone Platform , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[2]  George C. Polyzos,et al.  Controlled Wi-Fi Sharing in Cities: A Decentralized Approach Relying on Indirect Reciprocity , 2010, IEEE Transactions on Mobile Computing.

[3]  Giuseppe Bianchi,et al.  Per-Frame Energy Consumption in 802.11 Devices and Its Implication on Modeling and Design , 2015, IEEE/ACM Transactions on Networking.

[4]  Nalini Venkatasubramanian,et al.  CrowdMAC: A Crowdsourcing System for Mobile Access , 2012, Middleware.

[5]  John C. S. Lui,et al.  On the Access Pricing and Network Scaling Issues of Wireless Mesh Networks , 2007, IEEE Transactions on Computers.

[6]  Rachel Botsman,et al.  What's Mine Is Yours: The Rise of Collaborative Consumption , 2010 .

[7]  Dimitrios Koutsonikolas,et al.  Power-throughput tradeoffs of 802.11n/ac in smartphones , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[8]  Kang G. Shin,et al.  Aggregating Bandwidth for Multihomed Mobile Collaborative Communities , 2007, IEEE Transactions on Mobile Computing.

[9]  Narseo Vallina-Rodriguez,et al.  When David helps Goliath: the case for 3G onloading , 2012, HotNets-XI.

[10]  Murali S. Kodialam,et al.  Characterizing the capacity region in multi-radio multi-channel wireless mesh networks , 2005, MobiCom '05.

[11]  Mohammad Hadi Afrasiabi,et al.  Pricing strategies for user-provided connectivity services , 2012, 2012 Proceedings IEEE INFOCOM.

[12]  Daniel Pérez Palomar,et al.  A tutorial on decomposition methods for network utility maximization , 2006, IEEE Journal on Selected Areas in Communications.

[13]  Nikolaos Laoutaris,et al.  Collaborative Consumption for Mobile Broadband: A Quantitative Study , 2014, CoNEXT.

[14]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[15]  Xinbing Wang,et al.  INDAPSON: An incentive data plan sharing system based on self-organizing network , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[16]  Catherine Rosenberg,et al.  A game theoretic framework for bandwidth allocation and pricing in broadband networks , 2000, TNET.

[17]  W. Jevons Money and the Mechanism of Exchange , 2001 .

[18]  Marcus Felson,et al.  Community Structure and Collaborative Consumption: A Routine Activity Approach , 1978 .

[19]  J. Nash THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[20]  J. Walrand,et al.  WiFi access point pricing as a dynamic game , 2006, IEEE/ACM Transactions on Networking.

[21]  Leandros Tassiulas,et al.  Enabling crowd-sourced mobile Internet access , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[22]  Rute C. Sofia,et al.  User-provided networks: consumer as provider , 2008, IEEE Communications Magazine.

[23]  Feng Qian,et al.  A close examination of performance and power characteristics of 4G LTE networks , 2012, MobiSys '12.

[24]  Xiaojun Lin,et al.  Distributed and Provably Efficient Algorithms for Joint Channel-Assignment, Scheduling, and Routing in Multichannel Ad Hoc Wireless Networks , 2009, IEEE/ACM Transactions on Networking.

[25]  Wing Cheong Lau,et al.  An Empirical Study on the Capacity and Performance of 3G Networks , 2008, IEEE Transactions on Mobile Computing.

[26]  Elizabeth M. Belding-Royer,et al.  Cool-Tether: energy efficient on-the-fly wifi hot-spots using mobile phones , 2009, CoNEXT '09.

[27]  Lenin Ravindranath,et al.  COMBINE: leveraging the power of wireless peers through collaborative downloading , 2007, MobiSys '07.

[28]  Leandros Tassiulas,et al.  Hybrid data pricing for network-assisted user-provided connectivity , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[29]  Jon Crowcroft,et al.  Architecting Citywide Ubiquitous Wi-Fi Access , 2007, HotNets.

[30]  Dimitrios Koutsonikolas,et al.  TDM MAC protocol design and implementation for wireless mesh networks , 2008, CoNEXT '08.

[31]  Julien Freudiger,et al.  On Wireless Social Community Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[32]  Kok-Kiong Yap,et al.  Making use of all the networks around us: a case study in android , 2012, CCRV.

[33]  Ryoichi Shinkuma,et al.  Bandwidth exchange: an energy conserving incentive mechanism for cooperation , 2010, IEEE Transactions on Wireless Communications.

[34]  Xu Yuan,et al.  UPS: A United Cooperative Paradigm for Primary and Secondary Networks , 2013, 2013 IEEE 10th International Conference on Mobile Ad-Hoc and Sensor Systems.

[35]  Leandros Tassiulas,et al.  A Double-Auction Mechanism for Mobile Data-Offloading Markets , 2015, IEEE/ACM Transactions on Networking.

[36]  Franci Pivec,et al.  Measuring the information society , 2003 .

[37]  Jon Crowcroft,et al.  Modelling incentives for collaboration in mobile ad hoc networks , 2004, Perform. Evaluation.

[38]  Martin Nilsson,et al.  Investigating the energy consumption of a wireless network interface in an ad hoc networking environment , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[39]  Leandros Tassiulas,et al.  Mobile edge-networking architectures and control policies for 5G communication systems , 2016, 2016 14th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[40]  Hyoseop Lee,et al.  Understanding Quota Dynamics in Wireless Networks , 2014, TOIT.

[41]  Lorenzo Keller,et al.  Cooperative video streaming on smartphones , 2011, 2011 49th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[42]  Leandros Tassiulas,et al.  Incentive mechanisms for user-provided networks , 2014, IEEE Communications Magazine.

[43]  LinXiaojun,et al.  Distributed and provably efficient algorithms for joint channel-assignment, scheduling, and routing in multichannel ad hoc wireless networks , 2009 .

[44]  Leandros Tassiulas,et al.  Bits and coins: Supporting collaborative consumption of mobile internet , 2015, 2015 IEEE Conference on Computer Communications (INFOCOM).

[45]  Arun Venkataramani,et al.  Energy consumption in mobile phones: a measurement study and implications for network applications , 2009, IMC '09.

[46]  Roger B. Myerson,et al.  Game theory - Analysis of Conflict , 1991 .

[47]  A. Banerjee Convex Analysis and Optimization , 2006 .

[48]  Christina Fragouli,et al.  MicroCast: cooperative video streaming on smartphones , 2012, MobiSys '12.

[49]  Yichuan Wang,et al.  User-profile-driven collaborative bandwidth sharing on mobile phones , 2010, MCS '10.