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resources, decreasing their responsiveness bonus and
consequently their bandwidth.
The proposed incentive mechanism encourages
cooperative behavior between the peers preventing
the free-riding problem. Using the game theory con-
cept of ”core”, the peers forming the coalition get
in return a fair utility in relation to the bandwidth
they supply (achieving fairness in bandwidth shar-
ing); And in addition, it allows the formation of coali-
tions of peers that help each other in downloading
files, increasing the performance of the P2P network.
2 DOWNLOADING WITH
COALITIONS
In this section, we describe the model of the environ-
ment in which the system is deployed and the mech-
anism of coalition formation among peers. We firstly
describe a simplified situation, illustrating the advan-
tages of forming coalitions for P2P downloads and the
way of computing and dividing the utility or profit ob-
tained by peer that participates in the coalition. Sec-
ondly, and in more general terms, we describe the
coalition formation process and how the data and the
bandwidth are distributed among the coalition mem-
bers.
2.1 P2P Network Type
For our work, we have selected a P2P system with a
partially centralized architecture and an unstructured
network. The first characteristic is related to the de-
gree of centralization of the peer’s network, and the
second with the fact that the network is created in a
non-deterministic way as peers and files are added.
When a peer wants to download a file, it directs its
request to a supernode and this searches the file in its
index (a supernode is a peer that acts as a central in-
dex for files shared for a subpart of the peer network).
When the file is located, supernode sends to the ”re-
quester” peer an indexed result with the set of nodes
that store the requested file. Then, the requester peer
opens a direct connection with one or more peers that
hold the requested file, and proceeds to download it.
2.2 Coalition Formation Model
Coalition formation is an important mechanism for
cooperation in Multi-Agent Systems (MAS). In or-
der to be used by autonomous agents, a coalition for-
mation mechanism must solve the following issues:
i) maximize the agents’ profit or utility. For every
coalition S, coalitional value V(S) must be computed,
i.e., the total utility obtained by S as a whole ii) di-
vide the total utility among agents in a fair and stable
way, so that the agents in the coalition are not mo-
tivated to abandon it. For every coalition S and ev-
ery agent i ∈ S, payment configuration x(i) must be
computed, i.e., the share of V(S) that is assigned to
the agent i. iii) do this within a reasonable amount
of time and using a reasonable amount of computa-
tional efforts. Our coalition formation model allows
cooperation to take place among autonomous, ratio-
nal and self-interested agents in a class of superaddi-
tive task oriented domains (Belmonte et al., 2006a).
Each agent has the necessary resources to carry out
its own task, however it is possible to form a coali-
tion among agents with a new re-distribution of the
task that may allow them to obtain benefits. The pro-
posed model guarantees an optimum task allocation
and a stable payoff division. Furthermore, computa-
tional complexity problems are solved.
In this section the coalition formation scheme is
applied with the goal of improving the performance
of P2P file exchange systems. In this case, the central
idea is based on sharing the task of downloading a file
among a set of peers forming a coalition. From the
point of view of the peer that wants to download the
file there is a clear advantage, since the total download
time is reduced. From the point of view of uploading
peers, for each one the task of transferring the file is
alleviated, since it is divided between the members of
the coalition.
Let us consider the simplified situation illustrated
in figure 1. In this scenario, p
b
, asks p
a
for a file
Z. This peer p
a
forms a coalition S with three other
nodes p
h
, p
l
and p
m
to transfer that file. In P2P file
sharing systems, every node p
m
has an upload b
in
i
and download b
out
i
bandwidth dedicated to file shar-
ing. Usually these bandwidths are user defined and
indicate maximum values, and b
in
i
is much lower than
b
out
i
. This simplified scenario can be generalized, we
can consider that the downloader peer splits its band-
width in order to perform simultaneous downloads,
determining the b
out
i
dedicated for each download.
The model is valid for both scenarios.
In general, there will be an initial uploading agent
p
0
(in the figure p
a
) and a set of n additional upload-
ing agents, p
1
,..., p
n
(in the figure p
h
, p
l
and p
m
), all
of which have the file that has to be downloaded and
they dedicate their upload capacity b
in
i
to this transfer.
Let us call size(Z) = T the size of the file to down-
load. Let us also assume that
∑
n
0
b
in
i
≤ b
out
b
.
Then an estimation of the time necessary for the
transfer of file Z by the coalition S is given by the
ratio between the size of the file and the coalition
bandwidth(1):
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