ACM Computing Surveys (CSUR)
Fractal Image Compression and Recurrent Iterated Function Systems
IEEE Computer Graphics and Applications
Enhancing the Beauty of Fractals
ICCIMA '99 Proceedings of the 3rd International Conference on Computational Intelligence and Multimedia Applications
Latency Performance of SOAP Implementations
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Compressing SOAP Messages by using Differential Encoding
ICWS '04 Proceedings of the IEEE International Conference on Web Services
LYE: A High-Performance Caching SOAP Implementation
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
Journal of Parallel and Distributed Computing - Special issue on middleware
A middleware architecture for distributed systems management
Journal of Parallel and Distributed Computing - Special issue on middleware
XML Clustering by Principal Component Analysis
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Fast Detection of XML Structural Similarity
IEEE Transactions on Knowledge and Data Engineering
Differential Deserialization for Optimized SOAP Performance
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Journal of Parallel and Distributed Computing
Clustering XML Documents Based on the Weight of Frequent Structures
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Similarity-Based SOAP Multicast Protocol to Reduce Bandwith and Latency in Web Services
IEEE Transactions on Services Computing
Dynamic Fractal Clustering Technique for SOAP Web Messages
SCC '11 Proceedings of the 2011 IEEE International Conference on Services Computing
Redundancy-aware SOAP messages compression and aggregation for enhanced performance
Journal of Network and Computer Applications
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The significant increase in the usage of Web services has resulted in bottlenecks and congestion on bandwidth-constrained network links. Aggregating SOAP messages can be an effective solution that could potentially reduce the large amount of generated traffic. Although pairwise SOAP aggregation, that is grouping only two similar messages, has demonstrated significant performance improvement, additional improvements can be done by including similarity mechanisms. Such mechanisms cluster several SOAP messages that have high degree of similarity. This paper proposes a fractal self-similarity model that provides a novel way of computing the similarity of SOAP messages. Fractal is proposed as an unsupervised clustering technique that dynamically groups SOAP messages. Various experimentations have shown good performance results for the proposed fractal self-similarity model in comparison with some well-known clustering models by only consuming 31% of the clustering time required by the K-Means and 23% when using principle component analysis (PCA) combined with K-Means. Furthermore, the proposed technique has shown ''better'' quality clustering, as the aggregated SOAP messages have much smaller size than their counterparts.