Abstract
The Simple Object Access Protocol (SOAP) is a basic communication protocol in Web services, which is based on eXtensible Markup Language (XML). SOAP could suffer from high latency and bottlenecks that might occur due to the high network traffic caused by the large number of client requests and the large size of XML Web messages. Previous works have proposed static and dynamic clustering models for SOAP messages to support compression based aggregation tool that could potentially reduce the overall size of SOAP messages in order to reduce the required bandwidth between the clients and their server and increase the performance of Web services. In this paper, dynamic clustering based aggregation model has been implemented based on Term Frequency-Inverse Document Frequency (TF-IDF) and Euclidean Distance methods for estimating the high degree of similarity among SOAP messages and then grouping them into a dynamic number of clusters based on lower distance to support Huffman compression based aggregation tool in combining several compressed XML Web messages in one compact message. Our proposed model has achieved better results especially in medium and large subsets of used dataset in comparison with dynamic fractal clustering and in medium, large and very large subsets with vector space model that used the same dataset. Moreover, the experiment results show a significant improvement in reducing the required processing time for clustering XML Web messages in each group of dataset.
| Original language | English |
|---|---|
| Pages (from-to) | 80-88 |
| Number of pages | 9 |
| Journal | Journal of Network and Computer Applications |
| Volume | 41 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2014 |
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Keywords
- Aggregation
- Compression
- Dynamic clustering
- Keywords
- Web services
- XML messages
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture
Cite this
Fast dynamic clustering SOAP messages based compression and aggregation model for enhanced performance of Web services. / Abbas, Ahmed Mohammed; Abu Bakar, Azuraliza; Ahmad Nazri, Mohd Zakree.
In: Journal of Network and Computer Applications, Vol. 41, No. 1, 2014, p. 80-88.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Fast dynamic clustering SOAP messages based compression and aggregation model for enhanced performance of Web services
AU - Abbas, Ahmed Mohammed
AU - Abu Bakar, Azuraliza
AU - Ahmad Nazri, Mohd Zakree
PY - 2014
Y1 - 2014
N2 - The Simple Object Access Protocol (SOAP) is a basic communication protocol in Web services, which is based on eXtensible Markup Language (XML). SOAP could suffer from high latency and bottlenecks that might occur due to the high network traffic caused by the large number of client requests and the large size of XML Web messages. Previous works have proposed static and dynamic clustering models for SOAP messages to support compression based aggregation tool that could potentially reduce the overall size of SOAP messages in order to reduce the required bandwidth between the clients and their server and increase the performance of Web services. In this paper, dynamic clustering based aggregation model has been implemented based on Term Frequency-Inverse Document Frequency (TF-IDF) and Euclidean Distance methods for estimating the high degree of similarity among SOAP messages and then grouping them into a dynamic number of clusters based on lower distance to support Huffman compression based aggregation tool in combining several compressed XML Web messages in one compact message. Our proposed model has achieved better results especially in medium and large subsets of used dataset in comparison with dynamic fractal clustering and in medium, large and very large subsets with vector space model that used the same dataset. Moreover, the experiment results show a significant improvement in reducing the required processing time for clustering XML Web messages in each group of dataset.
AB - The Simple Object Access Protocol (SOAP) is a basic communication protocol in Web services, which is based on eXtensible Markup Language (XML). SOAP could suffer from high latency and bottlenecks that might occur due to the high network traffic caused by the large number of client requests and the large size of XML Web messages. Previous works have proposed static and dynamic clustering models for SOAP messages to support compression based aggregation tool that could potentially reduce the overall size of SOAP messages in order to reduce the required bandwidth between the clients and their server and increase the performance of Web services. In this paper, dynamic clustering based aggregation model has been implemented based on Term Frequency-Inverse Document Frequency (TF-IDF) and Euclidean Distance methods for estimating the high degree of similarity among SOAP messages and then grouping them into a dynamic number of clusters based on lower distance to support Huffman compression based aggregation tool in combining several compressed XML Web messages in one compact message. Our proposed model has achieved better results especially in medium and large subsets of used dataset in comparison with dynamic fractal clustering and in medium, large and very large subsets with vector space model that used the same dataset. Moreover, the experiment results show a significant improvement in reducing the required processing time for clustering XML Web messages in each group of dataset.
KW - Aggregation
KW - Compression
KW - Dynamic clustering
KW - Keywords
KW - Web services
KW - XML messages
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U2 - 10.1016/j.jnca.2013.10.010
DO - 10.1016/j.jnca.2013.10.010
M3 - Article
VL - 41
SP - 80
EP - 88
JO - Journal of Network and Computer Applications
JF - Journal of Network and Computer Applications
SN - 1084-8045
IS - 1
ER -