Using bandwidth sharing to fairly overcome channel asymmetry

We propose a peer-to-peer architecture designed to overcome asymmetries in upload/download speeds that are ty pical in end-user dialup, broadband and cellular wireless int ernet connections. Our approach allows users at remote locations to access information stored on their home computers at rates o ften exceeding their home connection’s upload capacity. The key to this approach is to share file data when communications are id le using random linear coding, so that, when needed, an end-use r can download a file from several sources at a higher data rate than his home computer’s upload capacity. We prove that our proposed system is asymptotically fair, in that (even malic ious) users are proportionally assigned idle bandwidth dependin g on how much bandwidth they contribute, and that there is a natural incentive to join and cooperate fairly in the system. In addi tion, our approach provides cryptographic security and geographic data robustness to the participating peers. I. I NTRODUCTION AND MOTIVATION Many users connect to the internet through asymmetric links, in which the upload capacities are much smaller than download capacities. Internet service Providers (ISPs) em ploy this asymmetric design based on the premise that casual internet use mostly involves downloading from a relatively small number ofcontent providers . Recently the ‘mostly download’ profile of users has started to change. Users now commonly have access to devices like digital video cameras, high resolution scanners, and high capacity sound recorders that capture large volumes of digi tal data. This change in users’ access profile makes upload speed a bottleneck for typical remote access. Thus, if a user remot ly accesses data stored on a home computer, such as a song or video, his access rate is limited by both his home’s upload capacity and his remote location’s download capacity. This work attempts to correct for such channel asymmetries by filling a high bandwidth download pipe through the aggregation of multiple idle lower bandwidth upload pipes. Our proposed approach has the following features: • Fairness Unallocated bandwidth is re-distributed in proportion to the bandwidth contributed by system peers. • Incentive There is a natural incentive for peers to participate and cooperate with others in the system. • Distributed operation Only local information is needed (i.e. no control information needs to be exchanged). • RobustnessData is available from many sources. In addition, it is not too difficult to add security to the mode l. In effect, our approach permits users to bypass the ‘bandwidth: use it or lose it’ service model offered by commercial ISPs, and instead maintain ‘credit’ for their contribution s within the system as a whole. With hard-disk storage costing under a dollar per gigabyte, the benefits enumerated above quickly surpass the cost of caching other users’ data. The rest of this paper is organized as follows. In Section II we mention some of the related work in the field and contrast it with our approach. Thereafter, we formally introduce the details of our proposed bandwidth sharing method in Section III. In Section IV we analytically prove the fairness of our system and show that it provides a natural incentive for peer contributions. We simulate various aspects of our syst em in Section V to demonstrate its features, including specific cases where malicious peers attempt to take unfair advantag e of the system. We also demonstrate the real-time efficiency o f random linear coding for this application. Finally Section VI concludes our results and suggests directions for future wo rk.

[1]  K. Jain,et al.  Practical Network Coding , 2003 .

[2]  Gustavo de Veciana,et al.  Service capacity of peer to peer networks , 2004, IEEE INFOCOM 2004.

[3]  David K. Y. Yau,et al.  A game theoretic approach to provide incentive and service differentiation in P2P networks , 2004, SIGMETRICS '04/Performance '04.

[4]  Hui Zhang,et al.  Measurement-based optimization techniques for bandwidth-demanding peer-to-peer systems , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[5]  Muriel Medard,et al.  How good is random linear coding based distributed networked storage , 2005 .

[6]  Rudolf Ahlswede,et al.  Network information flow , 2000, IEEE Trans. Inf. Theory.

[7]  Christos Gkantsidis,et al.  Network coding for large scale content distribution , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[8]  Donald F. Towsley,et al.  Modeling peer-peer file sharing systems , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[9]  Kostas G. Anagnostakis,et al.  Exchange-based incentive mechanisms for peer-to-peer file sharing , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[10]  Gustavo de Veciana,et al.  Performance of peer-to-peer networks: Service capacity and role of resource sharing policies , 2006, Perform. Evaluation.

[11]  Hong Zhu,et al.  Nash equilibria in parallel downloading with multiple clients , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[12]  Herbert S. Wilf,et al.  On the Sequential and Random Selection of Subspaces over a Finite Field , 1977, J. Comb. Theory, Ser. A.

[13]  Michael Luby,et al.  A digital fountain approach to reliable distribution of bulk data , 1998, SIGCOMM '98.

[14]  Ben Y. Zhao,et al.  Tapestry: a resilient global-scale overlay for service deployment , 2004, IEEE Journal on Selected Areas in Communications.

[15]  Ben Y. Zhao,et al.  Pond: The OceanStore Prototype , 2003, FAST.