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L. Chandra, J. Chandrasekaran, K. Perumal, B. Babu and V. Jayaramakrishnan

Abstract

NLO active 2-aminopyridinium 4-aminobenzoate (APAB) single crystals were successfully grown by the standard slow evaporation technique. The crystallinity of the grown crystals was analyzed through X-ray diffraction (XRD) measurements. Fourier transform infrared (FT-IR) spectroscopic studies were also performed for the identification of different modes present in the compound. The UV-Vis absorption and transmittance spectra were recorded for the grown crystal and the optical band gap was calculated. Birefringence and etching studies were also carried out. The dielectric study showed that the dielectric constant decreased with an increase in frequency. The photoconductivity study revealed its positive photoconducting nature. Theoretical HOMO LUMO investigations were also made for the crystal. The relative SHG efficiency of the material was investigated by the Kurtz and Perry powder technique. The phase matching property of the crystal was studied through the SHG dependence of average particle sizes.

Open access

Boominathan Perumal, M. Aramudhan and Ra K. Saravanaguru

Abstract

Cloud computing technology has transformed the information and communication technology industry by authorizing on-demand resource delivery to the cloud users. Datacenters are the major resource storage places from where the resources are disseminated to the requesters. When several requests are received by datacenters, the available resources are to be handled in an optimized way; otherwise the datacenters suffer from resource wastage. Virtualization is the technology that helps the cloud providers to handle several requests in an optimized way. In this regard, virtual machine placement, i.e., the process of mapping virtual machines to physical machines is considered to be the major research issue. In this paper, we propose to apply fuzzy hybrid bio-inspired meta-heuristic techniques for solving the virtual machine placement problem. The cuckoo search technique is hybridized with the fuzzy ant colony optimization and fuzzy firefly colony optimization technique. The experimental results obtained show competing performance of the proposed algorithms.