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Scaling of resources in cloud computing is essential for the better utilization of resources. Dynamic allocation of the resources / VMs in the multi-tenant environment is the need of the cloud computing. Virtualization technologies evolved to help IT organizations and to improve the efficiency of their hardware resources by partitioning hardware to provide simultaneous support to multiple applications and their corresponding software stacks. If the resource utilization is not properly allocated to applications, it will lead to the faulty services to the customers. The Cloud is the hub of resources, and can be used by any client on rental bases and on no demand resources can left with no usage. Clients/ Brokers may request for the multiple VMs/ other resources like, applications, database, operating system etc, but the resources are limited. So, there is the need of such a system to handle this allocation and deallocation of resources or VMs. By this PDRA model, authors have presented an idea to handle the resources/ VMs allocation and deallocation system.

In an automatic fingerprint identification system (AFIS), the fingerprint enhancement algorithm is mainly used to improve the visual quality of the input fingerprint image. The factors affecting the quality of an input fingerprint image may be the presence of scars, cuts, pressure variation between the finger and sensor, worn artifacts, and humidity during acquisition process. An enhancement algorithm is applied on the input fingerprint image to improve image quality and to repair broken ridges. This paper proposes a new method of enhancing fingerprint image. The method uses a hybrid approach of a new orientation scheme and a Circular Gabor filter to improve the visual quality of the fingerprint image. The proposed approach is compared to other enhancement algorithms using structural similarity index (SSIM). Experimental results and comparative analysis show that the new method performs better than the previous methods .

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