6,719 research outputs found
A Game Theoretic Analysis of Incentives in Content Production and Sharing over Peer-to-Peer Networks
User-generated content can be distributed at a low cost using peer-to-peer
(P2P) networks, but the free-rider problem hinders the utilization of P2P
networks. In order to achieve an efficient use of P2P networks, we investigate
fundamental issues on incentives in content production and sharing using game
theory. We build a basic model to analyze non-cooperative outcomes without an
incentive scheme and then use different game formulations derived from the
basic model to examine five incentive schemes: cooperative, payment, repeated
interaction, intervention, and enforced full sharing. The results of this paper
show that 1) cooperative peers share all produced content while non-cooperative
peers do not share at all without an incentive scheme; 2) a cooperative scheme
allows peers to consume more content than non-cooperative outcomes do; 3) a
cooperative outcome can be achieved among non-cooperative peers by introducing
an incentive scheme based on payment, repeated interaction, or intervention;
and 4) enforced full sharing has ambiguous welfare effects on peers. In
addition to describing the solutions of different formulations, we discuss
enforcement and informational requirements to implement each solution, aiming
to offer a guideline for protocol designers when designing incentive schemes
for P2P networks.Comment: 31 pages, 3 figures, 1 tabl
A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints
We consider caching in cellular networks in which each base station is
equipped with a cache that can store a limited number of files. The popularity
of the files is known and the goal is to place files in the caches such that
the probability that a user at an arbitrary location in the plane will find the
file that she requires in one of the covering caches is maximized.
We develop distributed asynchronous algorithms for deciding which contents to
store in which cache. Such cooperative algorithms require communication only
between caches with overlapping coverage areas and can operate in asynchronous
manner. The development of the algorithms is principally based on an
observation that the problem can be viewed as a potential game. Our basic
algorithm is derived from the best response dynamics. We demonstrate that the
complexity of each best response step is independent of the number of files,
linear in the cache capacity and linear in the maximum number of base stations
that cover a certain area. Then, we show that the overall algorithm complexity
for a discrete cache placement is polynomial in both network size and catalog
size. In practical examples, the algorithm converges in just a few iterations.
Also, in most cases of interest, the basic algorithm finds the best Nash
equilibrium corresponding to the global optimum. We provide two extensions of
our basic algorithm based on stochastic and deterministic simulated annealing
which find the global optimum.
Finally, we demonstrate the hit probability evolution on real and synthetic
networks numerically and show that our distributed caching algorithm performs
significantly better than storing the most popular content, probabilistic
content placement policy and Multi-LRU caching policies.Comment: 24 pages, 9 figures, presented at SIGMETRICS'1
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