Clustering web services based on multi-criteria service dominance relationship using Peano Space filling curve

As the use of the web is greatly increased so as the need for effective web service selection and retrieval techniques. So many good algorithms have been developed for web service selection problem. The need for effective web service clustering technique is also came forward, which will help the users to search within their needed clusters, that will reflect different tradeoffs such as price , quality etc. Recent works on web service selection and retrieval techniques has found out that for getting greater accuracy and stability, all the algorithms for web service selection and clustering must satisfy the following two criteria. First, it should consider all the parameter matches. Second, multiple criteria should be taken into consideration while performing the parameter matching. In this paper we are proposing an efficient web service clustering technique based on multi criteria service dominance relationship, which satisfies the above criteria. Recent work on the same area proposed the use of Hilbert space filling curve, and then applying a simple algorithm for forming the clusters. Space filling curve is a way of mapping multi-dimensional space into the one dimensional space. So the effectiveness of the formed clusters are having a direct relationship with how effective the used space filling curve is. In this paper we propose the use of Peano Space filling curve for the multidimensional reduction, which tends to show less irregularity, more fairness and more scalability than Hilbert space filling curve.