Linear discriminant analysis-based service discovery algorithm in MANET. (2016) - Buvana, M.; Suganthi, M.; Muthumayil, K.
With the increase in the number of available services, the use of the service has been increased rapidly and finding the exact services also the challenging task in large-scale mobile ad hoc network. We propose a method named as SD-LDA (linear discriminant analysis-based service discovery) algorithm to find the web services. Our method exploits the clustering structure, where the cluster head node (CHN) is selected to form a distributed directory. This CHN handles the discovery agent in which LDA is used for service discovery by reducing the dimension of service data and ignores the inequality of local data points of the similar class using matrix representation and calculating the overall score of QoS for each service, then ranks the services based on their overall QoS and selects services with highest QoS values. Finally, the performance of our algorithm is evaluated by experiments. The results show that the clustering method has low communication overhead and success of service discovery is increased. In addition, we show that less energy consumption during service discovery, minimise the discovery overhead, and rank identification.