As grow as the data-intensive applications in cloud computing day after day, data popularity in this environment becomes critical and important. Hence to improve data availability and efficient accesses to popular data, replication algorithms are now widely used in distributed systems. However, most of them only replicate the static number of replicas on some requested chosen sites and it is ob...

Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. There are a number of different approaches to prediction. Markov models and their variations, collaborative filtering models, or models based on pattern recognition techniques such as sequence mining, association rule mining, clustering user sessions or user, have been found well...

This paper presents a Page Rank based prefetching technique for accesses to web page clusters. The approach uses the link structure of a requested page to determine the “most important” linked pages and to identify the page(s) to be prefetched. The underlying premise of our approach is that in the case of cluster accesses, the next pages requested by users of the web server are typically based ...

Almost all applications containing indirect array addressing (irregular accesses) have a substantial number of direct array accesses (regular accesses) too. A conspicuous percentage of these direct array accesses usually require inter-processor communication for the applications to run on a distributed memory multicomputer. This study highlights how lack of a uniform representation and lack of ...

Cache misses due to coherence and directory maintenance is a major reason for poor performance in shared memory multiprocessors. We show that the relationship between a particular access pattern and cache miss ratios for a class of directory-based, write-invalidate cache coherence protocols can be characterised in a small set of parameters. In order to do this, a reference generator has been de...

My research interests span the areas of big data, cloud computing, high-performance computing, and machine intelligence. A common thread in my research is the orchestration of both theories and systems: An in-depth theoretical analysis is conducted to guide the design and implementation of the real system; On the other hand, from building real systems I abstract their commonality to achieve gen...

Neural networks are applied to the system identification problems using adaptive algorithms for either parameter or functional estimation of dynamic systems. In this paper the neural networks' sensitivity to input values and connections' weights, is studied. The Reduction-Sigmoid-Amplification (RSA) neurons are introduced and four different models of neural network architecture are proposed and...