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taken in charge by some models is the number of
interactions that have occurred between client and
server when trust in the server is calculated. Indeed,
the trust values computed by probability based mod-
els gain precision as the number of interactions with
the server increases. Now, the number of interactions
could be considered as an information relative to the
execution of a service by a given server and thus be
part of the execution context; This is a first step to-
wards context awareness.
Even though the above two contextual attributes
seem important, they have no influence on the trans-
mission of messages between client and server. We
should now decide which contextual attributes are rel-
evant to these steps of the interaction.
The routing context associated to an experience
should contain representationsfor the factors that may
influence the quality of exchanges between client and
server.
4.1 Hop Count
Works presented in (Hekmat and Mieghem, 2003)
show that the probability of success of a communi-
cation between agents is highly dependent on the dis-
tance, in terms of hop count, between the participants;
the higher the hop count, the lower the probability of
success. For this reason we consider the hop count be-
tween client and server to be a crucial information for
caracterising the context of an interaction. This infor-
mation is freely available in the routing table, for any
node with which a communication is possible. How-
ever, the client can only retrieve, the distance to the
server, from its routing table; It cannot determine the
length of the return trip taken by the server’s response.
Indeed, existing routing algorithms, do not necessar-
ily use the same route from one node to another, as
they do than they do when returning. Nevertheless,
we can assume that the return trip is similar, in terms
of number of hops and therefore that the length of the
route from the client to the server also characterises
the travelling of the response.
From our point of view, hop count between client
and server is the first contextual information to be
considered in manets.
4.2 Mobility
The performance in terms of communication, of a
manet is closely related to the capacity of its rout-
ing algorithm to adapt to the mobility of the nodes.
Nevertheless, however efficient routing is in dealing
with mobility, communication between very mobile
nodes, or through a very dynamic network will be less
reliable than between stationnary nodes, or in a sta-
ble environment. Finding out a metric for mobility in
manets is a challenge. There exists few researchs that
have focused on such a topic. In (Boleng et al., 2002),
the authors have used link stability as a metric for mo-
bility to show that mobility has a direct effect on end
to end delay and data packet deliveryratio. Authors in
(Ghassemian et al., 2005) have used a similar metric,
deduced from the frequency of link state change and
link connectivity duration. It thus seems natural to in-
clude information concerning mobility in the routing
context. Moreover, intuitively, it seems to us gener-
ally more efficient for an agent to choose the most
stable server in order to have the greatest probability
that its requets reach the destination server.
What is mobility, how can it be defined and mea-
sured? Is it useful to consider the mobility of the en-
tire network or should we only study that of the path
between client and server? All these questions should
be answered before considering mobility as a part of
the routing context.
Mobility in ad hoc networks is a topic of research
that has been considered through various angles : the
specification of mobility aware routing protocols, the
effect of mobility on the performances of routing pro-
tocols, the definition of mobility models for simula-
tion, the definition of metrics to measure the mobility
of a given simulated network. Here, our aim is, for
any node of an operating network, to be able to de-
termine both the mobility of any other node and the
general mobility of the network.
This, of course, should be done using information
held by each node concerning the others ; namely the
routing table.
We can generally define mobility as the behav-
ior of an object (entity, person, thing, etc) that has a
changing position over time. However, in our case, it
is important to point out that, what we refer to as mo-
bility is in fact relative mobility. If two nodes move
in the same direction and with equal speed, they can
both be considered stable with respect to one another.
However, if the other agents in the network are static
then the two nodes have very high mobility relatively
to the rest of the network. Thus, two measures of
mobility may be considered: individual mobility of
nodes and global mobility of the network. In our case,
global mobility of the network should be considered
because it gives an idea on the mobility of the sur-
rounding environment. This general measure, how-
ever, does not reflect the individual mobility of each
node because it is an average measure and thus sta-
ble nodes can not be discovered using it. Thus, in
our opinion, it is also useful to consider the individual
mobility of nodes. In such a case, it will be easier for
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