AWSQ: an approximated web server queuing algorithm for heterogeneous web server cluster

With the rising popularity of web-based applications, the primary and consistent resource in the infrastructure of World Wide Web are cluster-based web servers. Overtly in dynamic contents and database driven applications, especially at heavy load circumstances, the performance handling of clusters is a solemn task. Without using efficient mechanisms, an overloaded web server cannot provide great performance. In clusters, this overloaded condition can be avoided using load balancing mechanisms by sharing the load among available web servers. The existing load balancing mechanisms which were intended to handle static contents will grieve from substantial performance deprivation under database-driven and dynamic contents. The most serviceable load balancing approaches are Web Server Queuing (WSQ), Server Content based Queue (QSC) and Remaining Capacity (RC) under specific conditions to provide better results. By Considering this, we have proposed an approximated web server Queuing mechanism for web server clusters and also proposed an analytical model for calculating the load of a web server. The requests are classified based on the service time and keep tracking the number of outstanding requests at each webserver to achieve better performance. The approximated load of each web server is used for load balancing. The investigational results illustrate the effectiveness of the proposed mechanism by improving the mean response time, throughput and drop rate of the server cluster

Utility Independent Privacy Preserving Data Mining - Horizontally Partitioned Data

Micro data is a valuable source of information for research. However, publishing data about individuals for research purposes, without revealing sensitive information, is an important problem. The main objective of privacy preserving data mining algorithms is to obtain accurate results/rules by analyzing the maximum possible amount of data without unintended information disclosure. Data sets for analysis may be in a centralized server or in a distributed environment. In a distributed environment, the data may be horizontally or vertically partitioned. We have developed a simple technique by which horizontally partitioned data can be used for any type of mining task without information loss. The partitioned sensitive data at 'm' different sites are transformed using a mapping table or graded grouping technique, depending on the data type. This transformed data set is given to a third party for analysis. This may not be a trusted party, but it is still allowed to perform mining operations on the data set and to release the results to all the 'm' parties. The results are interpreted among the 'm' parties involved in the data sharing. The experiments conducted on real data sets prove that our proposed simple transformation procedure preserves one hundred percent of the performance of any data mining algorithm as compared to the original data set while preserving privacy

Stabilization of 2D NSHP Recursive Digital Filters with Guaranteed Stability Using PLSI Polynomials

Two-dimensional digital filters have gained wide acceptance in recent years. For recursive filters, nonsymmetric half-plane versions (also known as semicausal) are more general than quarter-plane versions (also known as causal) in approximating arbitrary magnitude characteristics. The major problem in designing two-dimensional recursive filters is to guarantee their stability with the expected magnitude response. In general, it is very difficult to take stability constraints into account during the stage of approximation. This is the reason why it is useful to develop techniques, by which stability problem can be separated from the approximation problem. In this way, at the end of approximation process, if the filter becomes unstable, there is a need for stabilization procedures that produce a stable filter with similar magnitude response as that of the unstable filter. This paper, demonstrates a stabilization procedure for a two-dimensional nonsymmetric half-plane recursive filters based on planar least squares inverse (PLSI) polynomials. The paper's findings prove that, a new way of form-preserving transformation can be used to obtain stable PLSI polynomials. Therefore obtaining PLSI polynomial is computationally less involved with the proposed form-preserving transformation as compared to existing methods, and the stability of the resulting filters is guaranteed