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Omid Khatibi

Publications and source records attributed to Omid Khatibi.

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Criteria for the CloudSim Environment

CPU is undoubtedly the most important resource of the computer system. Recent advances in software and system architecture have increased processing complexity, as computing is now distributed and parallel. CloudSim represents the complexity of an application in terms of its computational requirements. CloudSim [9] is a complete solution for simulating Cloud Computing environments and building test beds for provisioning algorithms. This paper analyzes and evaluates the performance of cloud environment modeling using CloudSim. We describe the CloudSim architecture and then investigate the new models and techniques in CloudSim.

cs.DC

Efficient Multichannel in XML Wireless Broadcast Stream

In this paper we recommend the use of multi-channel for XML data in wireless broadcasting. First we divide XML data into information units as bucket, then extract path information (XPath) for any unit and build an index tree from the data path. Finally, make wireless data stream with merging parts of index tree and parts of XML data in multichannel XML. Then, create a protocol that allows mobile users access to the wireless XML stream generated with our method. We study 11 channels in server side and 3 orthogonal channels in client side.

cs.DC

An Improved Energy-Aware Clustering Method for the Regional Queries in the Internet of Things

We will offer a method to improve energy efficient consumption for processing queries on the Internet of Things. We focused on an energy efficient hierarchical clustering index tree such that we can facilitate time-correlated region queries in the I.O.T (Internet of Things). We try to improve clustering and make a change on its proposed index tree. We try to do this by optimizing the query processing. We improve clustering to increase the accuracy of the Internet of Things and prevent the network from disconnecting. In the article that we have chosen, there is a heterogeneous cluster which means there exists a large data difference in the two ends of a cluster. Also, it often happens that the same information is sent to the base station by two overlapping clusters; therefore, we save energy by eliminating duplicated data.

cs.DC

Criteria for the Application of Double Exponential Transformation

The double exponential formula was introduced for calculating definite integrals with singular point oscillation functions and Fourier-integrals. The double exponential transformation is not only useful for numerical computations but it is also used in different methods of Sinc theory. In this paper we use double exponential transformation for calculating particular improper integrals. By improving integral estimates having singular final points. By comparison between double exponential transformations and single exponential transformations it is proved that the error margin of double exponential transformations is smaller. Finally Fourier-integral and double exponential transformations are discussed.

math.GM

An Upper Bound Estimate and Stability for the Global Error of Numerical Integration Using Double Exponential Transformation

The double exponential formula was introduced for calculating definite integrals with singular point oscillation functions and Fourier integral. The double exponential transformation is not only useful for numerical computations but it is also used in different methods of Sinc theory. In this paper we give an upper bound estimate for the error of double exponential transformation. By improving integral estimates having singular final points, in theorem 1 we prove that the method is convergent and the rate of convergence is $\mathcal{O}(h^2)$ where h is a step size. Our main tool in the proof is DE formula in Sinc theory. The advantage of our method is that the time and space complexity is drastically reduced. Furthermore, we discovered upper bound error in DE formula independent of N truncated number, as a matter of fact we proved stability. Numerical tests are presented to verify the theoretical predictions and confirm the convergence of the numerical solution.

math.GM