Cloud is an emerging technology where the providers provide various services to Information Technology by adopting the concept of service oriented architecture, distributed, autonomic, and utility computing. In the present competitive world, building a highly dependable cloud application and opting for the optimal fault tolerant technique for cloud components has become crucial. In this paper, ...

In many regression learning algorithms for fuzzy rule bases it is not possible to define the error measure to be optimized freely. A possible alternative is the usage of global optimization algorithms like genetic programming approaches. These approaches, however, are very slow because of the high complexity of the search space. In this paper we present a novel approach where we first create a ...

We consider a variation of the subset selection problem in ranking and selection, where motivated by recently developed global optimization approaches applied to simulation optimization, our objective is to identify the top-m out of k designs based on simulated output. Using the optimal computing budget framework, we formulate the problem as that of maximizing the probability of correctly selec...

It is a common practice to rely on background knowledge (BK) in order to assist and improve the ontology matching process. The choice of an appropriate source of background knowledge for a given matching task, however, remains a vastly unexplored question. In the current paper, we propose an automatic BK selection approach that does not depend on an initial direct matching, can handle multiling...

Organizations strive to optimize their business processes in order to satisfy customer requirements and internal goals. A basic necessity in order to meet time and quality objectives is to monitor an organization’s business processes. Process monitoring makes their execution more transparent and allows to react to observed deviations with corrective actions. This paper focuses on monitoring pro...

Routing protocols in most networks use the length of paths or the minimum-hops that can be achieved, as the routing metric. This led to the motivation to propose a new algorithm that satisfies multiple constraints for finding a feasible path and apply GA to reduce the time taken to find a feasible path. To achieve this, The Rough sets Theory (RST) is applied to reduce the Performance metrics su...

We consider a reinforcement learning setting introduced in [6] where the learner does not have explicit access to the states of the underlying Markov decision process (MDP). Instead, she has access to several models that map histories of past interactions to states. Here we improve over known regret bounds in this setting, and more importantly generalize to the case where the models given to th...