Zalinda Othman

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Keywords: Cloud computing service composition Systematic literature review Quality of service parameter QoS Research objectives Importance percentage of quality of service parameters a b s t r a c t The increasing tendency of network service users to use cloud computing encourages web service vendors to supply services that have different functional and(More)
—Service composition is among the most important challenges that cloud providers have ever faced. Optimization of QoS attributes when composing simple atomic services to obtain a complex service can be considered to be an NP-hard problem, which could be solved properly by using Hybrid optimization algorithms. In this research, the hybridization of an(More)
Aiming to provide satisfying and value-added cloud composite services, suppliers put great effort into providing a large number of service providers. This goal, achieved by providing the ''best'' solutions, will not be guaranteed unless an efficient composite service composer is employed to choose an optimal set of required unique services (with respect to(More)
Any abnormal patterns show in Statistical Process Control charts imply the presence of possible assignable causes and variances that may lead to the process performance deterioration. Therefore, timely detection and recognizer of patterns in control charts are very important in the SPC implementation. This paper presents the performance of five(More)
Enterprise Resource Planning (ERP) systems are widely used by many multinational companies throughout the world. Recently, many institutions of higher learning have replaced their legacy systems to ERP systems as a means for integration advantages. Investment with this ERP system are representing the largest investment for institutions of higher learning,(More)
Clustering is an unsupervised learning method that is used to group similar objects. One of the most popular and efficient clustering methods is K-means, as it has linear time complexity and is simple to implement. However, it suffers from gets trapped in local optima. Therefore, many methods have been produced by hybridizing K-means and other methods. In(More)
This paper proposed a dynamic tabu search (DTSAR) that incorporated a dynamic tabu list to solve an attribute reduction problem in rough set theory. The dynamic tabu list is use to skip the aspiration criteria and to promote faster running times. A number of experiments have been conducted to evalute the performance of the proposed technique with other(More)