Introduction The past decade has seen the rapid increase of content
distribution using the Internet as the medium of delivery Lab09. Users and
applications expect a low cost for content, but at the same time require high
levels of quality of service. However, providing content distribution at a low
cost is challenging. The major costs associated with meeting demand at a good
quality of service are (i) the high cost of hosting services on the managed
infrastructure of CDNs such as Akamai nor07,akamai, and (ii) the lost revenue
associated with the fact that digital content is easily duplicable, and hence
can be shared in an illicit peer-to-peer (P2P) manner that generates no
revenue for the content provider. Together, these factors have led content
distributors to search for methods of defraying costs.

One technique that is often suggested for defraying distribution costs is to
use legal peer-to-peer (P2P) networks to supplement provider distribution
pando,rawflow,RodTan06. It is well documented that the efficient use of P2P
methods can result in significant cost reductions from the perspective of ISPs
KarRod05,nor07; however there are substantial drawbacks as well. Probably the
most troublesome is that providers fear losing control of content ownership,
in the sense that they are no longer in control of the distribution of the
content and worry about feeding illegal P2P activity.

Thus, a key question that must be answered before we can expect mainstream
utilization of P2P approaches is: How can users that have obtained content
legally be encouraged to reshare it legally? Said in a different way, can
mechanisms be designed that ensure legitimate P2P swarms will dominate the
illicit P2P swarms?

In this paper, we investigate a “revenue sharing” approach to this issue. We
suggest that users can be motivated to reshare the content legally by allowing
them to share the revenue associated with future sales. This can be
accomplished through either a lottery scheme or by simply sharing a fraction
of the sale price. Recent work on using lotteries to promote societally
beneficial conduct MerPra09 suggests that such schemes could potentially see
wide spread adoption.

Such an approach has two key benefits: First, obviously, this mechanism
ensures that users are incentivized to join the legitimate P2P network since
they can profit from joining. Second, less obviously, this approach actually
damages the illicit P2P network. Specifically, despite the fact that content
is free in the illicit P2P network, since most users expect a reasonable
quality of service, if the delay in the illegitimate swarm is large they may
be willing to use the legitimate P2P network instead. Thus, by encouraging
users to reshare legitimately, we are averting them from joining the illicit
P2P network, reducing its capacity and performance; thus making it less likely
for others to use it.

The natural concern about a revenue sharing approach is that by sharing
profits with users, the provider is losing revenue. However, the key insight
provided by the results in this paper is that by discouraging users from
joining illicit P2P network, the increased share (possibly exponentially more)
of legitimate copies makes up for the cost of sharing revenue with end-users.

More specifically, the contribution of this paper is to develop and analyze a
model to explore the revenue sharing approach described above. Our model (see
Section s.model) is a fluid model that builds on work studying the capacity of
P2P content distribution systems. The key novel component of the model is the
competition for users among an illicit P2P system and a legal content
distribution network (CDN), which may make use of a supplementary P2P network
with revenue sharing. The main results of the paper (see Section s.results)
are Theorems thm:inefficient-thm:efficient-bass, which highlight the order-of-
magnitude gains in revenue extracted by the provider as a result of
participating in revenue sharing. Further, In addition to the analytic
results, to validate the insights provided by our asymptotic analysis of the
fluid model we also perform numerical experiments of the underlying finite
stochastic model. Tables tbl:ineff and tbl:eff summarize these experiments,
which highlight both that the results obtained in the fluid model are quite
predictive for the finite setting and that there are significant beneficial
effects of revenue sharing.

There is a significant body of prior work modeling and analyzing P2P systems.
Perhaps the most related work from this literature is the work that focuses on
server-assisted P2P content distribution networks
WanYeo07,SetApo07,LiuZha08,ChePon08,ShaJoh10,ParSha11A in which a central
server is used to “boost” P2P systems. This boost is important since pure P2P
systems suffer poor performance during initial stages of content distribution.
In fact, it is this initially poor performance that our revenue sharing
mechanism exploits to ensure that the legitimate P2P network dominates.

Two key differentiating factors of the current work compared to this work are:
(i) We model the impact of competition between legal and illegal swarms on the
revenue extraction of a content provider. (ii) Unlike most previous works on
P2P systems, we consider a time varying viral demand model for the evolution
of demand in a piece of content based on the Bass diffusion model (see Section
s.model). Thus, we model the fact that interest in content grows as interested
users contact others and make them interested.

With respect to (i), there has been prior work that focuses on identifying the
relative value of content and resources for different users gamenets,MisIon10.
For instance, gamenets deals with creating a content exchange that goes beyond
traditional P2P barter schemes, while MisIon10 attempts to characterize the
relative value of peers in terms of their impact on system performance as a
function of time. However, to the best of our knowledge, ours is the first
work that considers the question of economics and incentives in hybrid P2P
content distribution networks.

With respect to (ii), there has been prior work that considers fluid models of
P2P systems such as QiuSri04,MasVoj05,YanVec06. However, these all focus on
the performance evaluation of a P2P system with constant demand rate. As
mentioned above, a unique facet of our approach is that we explicitly make use
the transient nature of demand in our modeling. In the sense of explicitly
accounting for transient demand, the closest work to ours is ShaJoh10.
However, ShaJoh10 focuses only on jointly optimizing server and P2P usage in
the case of transient demand in order to obtain a target delay guarantee at
the lowest possible server cost.

The remainder of the paper is organized as follows. We first introduce the
details of our model in Section s.model. Then, Section s.results summarizes
analytic and numeric results, the proofs of which are included in the
appendix. Finally, Section s.conclusion provides concluding remarks.