![](bg3.png)
the Depth (level) of the concept c in the reference on-
tology.
Subsequently, the semantic similarity is computed
using the hypothesis that greater semantic distance
between concepts means smaller similarity and vice
versa (Roelleke and Wang, 2008). As the seman-
tic distance could range widely in a non-normalised
way, then there is a need for a normalization func-
tion to convert the semantic distance values in to a
logically acceptable semantic similarity values which
could then be used to rank the resources providers as
shown in figure 1. To do so, and as describes in (Ge
and Qiu, 2008), the semantic function needs to sup-
port three main properties:
• The semantic similarity values are a real numbers
in the range between [0, 1].
• The semantic similarity between any concepts and
itself = 1.
• he relation between semantic distance and seman-
tic similarity is inversed.
Accordingly, for the purpose of this paper we have
used a linear function to compute the semantic simi-
larity from the semantic distance as proposed by (Ge
and Qiu, 2008) which is shown in Equation 3.
SSem =
1
(p + SD + 1)
(0 < p ≤ 1) (3)
Where: SSem is the semantic similarity value.
From the experimental results we have chosen p
which produced the best subjectively observed re-
sults. After that, the requester will sort the providers
based on the semantic similarity value and contact the
ones with values a predefined threshold.
Using a reference ontology during the matching
process has raised the problem of the concept is not
part of the ontology; to overcome this problem we
have used a web document based matching (WDM)
technique to find the closest existing concept. Using
this technique, the system fetches context information
related to the concept from web sites like Wikipedia
2
then applies TF-IDF (Term Frequency-Inverse Doc-
uments Frequency) algorithm (Roelleke and Wang,
2008) to find the closest existing concept in the ontol-
ogy. Afterwards, the system applies the same match-
ing steps on the existing founded concept.
In this scenario, there are two types of delay time:
the first one is the time required to compute the sim-
ilarity and rank the resource providers accordingly;
this time has no effect on the network traffic since its
done locally in the node.
2
See http://en.wikipedia.org.
The other time is the one required to contact the
providers and receive the acknowledgements. Since
the requester has done the matching process locally it
does not need to send large messages to contact the
providers, it should be just small messages to insure
that the resource is still available and the provider still
happy to share it.
In terms of request satisfaction time which is the
summation of all the delay times from the beginning
of the matching process until receiving the acknowl-
edgment both times have impacts on it. As the main
argument of this research is to study the effects of the
place where the matching is done on the network per-
formance as well as the request satisfaction time; we
have developed another scenario where the requester
sends a request to its neighbours and the neighbours
themselves do the matching process individually, this
scenario is shown in the next section.
3.2 The Second Scenario: the Providers
do the Matching Process
Using this topology, there is no need for the nodes to
have the others resources information but they must
have the reference ontology to perform the semantic
matching base on it. In this case, the same matching
steps discussed in the first scenario have to be done
but in the providers nodes. The requesters node has to
send a request contains the resource description to its
neighbours and wait for reply. On the other part, the
provider receives the request(s) and does the match-
ing steps on its own resources database and return the
highest available resource semantic similarity value.
Accordingly, the requester will collect the replies and
rank the providers to be contacted based on the se-
mantic similarity values provided by the providers.
Using this scenario, the process of resource dis-
covery will affect the network traffic as more mes-
sages need to be broad-casted. Furthermore, the
requester needs to wait the providers to finish the
matching process and return the result. In addition,
one provider would receive many requests, which
leads to the request to be queued in the providers node
for the previous ones to be done. For a network point
of view the total network delay time could be calcu-
lated using Equation 4.
T = R
t
+ q
t
+ mp
t
+ Ack
t
(4)
Where: T : is the Total network delay time, R
t
:
is the time required to send the Request from the re-
quester to the provider. q
t
: is the queue time in the
providers side. mp
t
: is the matching time, Ack
t
is the
time required to send an acknowledgement back to
the requester.
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