Journal of Networks, Vol 5, No 10 (2010), 1135-1142, Oct 2010
doi:10.4304/jnw.5.10.1135-1142
The Estimation of Trustworthy of Grid Services Based on Neural Network
Abstract
Though research on the Grid Services has
progressed at a steady pace, its promise has yet to be
realized. One major difficulty is that, by its very nature, the
Grid Service is a large, uncensored system to which anyone
may contribute. This raises the question of how much
credence to give each source. The concept and definition of
trustworthy of Grid Service is given. Estimating
trustworthy of Grid Services with the method of Neural
Network from the aspect of trustworthy history sequence is
proposed. The principle of the method, applicable Neural
Network structure, Neural Network constructing, input
standardization, training sample constructing, and the
procedure of estimating trustworthy of Grid Services with
trained Neural Network are presented. Experiments
confirm that the methods with Neural Network are feasible
and effective to estimate trustworthy of Grid Service, and
do not put unreasonable expectations on users. We hope
that these methods will help to move the Grid Service closer
to fulfilling its promise.
progressed at a steady pace, its promise has yet to be
realized. One major difficulty is that, by its very nature, the
Grid Service is a large, uncensored system to which anyone
may contribute. This raises the question of how much
credence to give each source. The concept and definition of
trustworthy of Grid Service is given. Estimating
trustworthy of Grid Services with the method of Neural
Network from the aspect of trustworthy history sequence is
proposed. The principle of the method, applicable Neural
Network structure, Neural Network constructing, input
standardization, training sample constructing, and the
procedure of estimating trustworthy of Grid Services with
trained Neural Network are presented. Experiments
confirm that the methods with Neural Network are feasible
and effective to estimate trustworthy of Grid Service, and
do not put unreasonable expectations on users. We hope
that these methods will help to move the Grid Service closer
to fulfilling its promise.
Keywords
grid services; trustworthy; estimation; trustworthy history sequence, neural network
References
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