VM Image Repository and Distribution Models for Federated Clouds: State of the Art, Possible Directions and Open Issues

The emerging trend of Federated Cloud models enlist virtualization as a significant concept to offer a large scale distributed Infrastructure as a Service collaborative paradigm to end users. Virtualization leverage Virtual Machines (VM) instantiated from user specific templates labelled as VM Images (VMI). To this extent, the rapid provisioning of VMs with varying user requests ensuring Quality of Service (QoS) across multiple cloud providers largely depends upon the image repository architecture and distribution policies. We discuss the possible state-of-art in VMI storage repository and distribution mechanisms for efficient VM provisioning in federated clouds. In addition, we present and compare various representative systems in this realm. Furthermore, we define a design space, identify current limitations, challenges and open trends for VMI repositories and distribution techniques within federated infrastructure

FAULT TOLERANCE IN CLOUD STORAGE

- Fault tolerance in cloud storage is to enhance data storage security during disaster. so that IaaS (Infrastructure as a Service) in NC Cloud methodology will be implemented here. NC Cloud computation power and storage capacity of cloud computing systems that allow scientists to deploy computation and data intensive applications without infrastructure investment, where big data application  sets can be stored in the cloud. In pay-as-you-go model, storage strategies and benchmarking approaches have been mainly developed for cost-effectively storing large volume of generated application data sets in the cloud. However, they are either insufficiently cost-effective for the storage or impractical to be used at runtime. In this paper, toward NC Cloud achieving the minimum cost benchmark, we say highly cost-effective and practical storage strategy that can automatically decide whether a generated data set should be stored or not at the runtime in the cloud. The main aim of this strategy is the local-optimization for the tradeoff between computation and storage, while secondarily also taking users preferences on storage into consideration. At present,the remote monitoring system is growing very high due to the growth of supporting technologies and also in NC Cloud.  The problem that may occur in remote monitoring such as the objects to be monitored and how quick how much amount of data to be transmitted to the data centre to be processed properly. This study proposes using a cloud computing infrastructure as processing centre in the remote sensing data. It focuses on the situation for sensing on the environment condition and disaster early detection. Where it has two important issue, especially in big cities that have many residents. This proposes to build the conceptual and also  aprototype model in a extensive manner from the remote terminal unit until development method for data retrieval. We  propose using FTR-HTTP method to guarantee the delivery of the data from remote client to server.When the destruction occur the database architecture will transfer the database to the concern location assigned from the admin. So that data base can be saving exactly with the last fine transaction. Here data loss will not occur at any cost. This method is based on IP conflict procedure. So that roll backing process can also be possible. Using the same procedure of IP conflict method and this method will shows the data upto last minute transaction

Análisis del rendimiento de la paralelización del algoritmo Reed-Solomon

Distributed storage systems allow to solve the strong demand of data storage required by today's society, this is because new challenges arise related to data recovery based on erasure code. This article presents the parallelization of the Reed-Solomon algorithm through threads. The evaluation was made in a BLADE system, the execution of the algorithm has been done in a configuration of 1, 2, 4 and 8 threads to check the behavior of the algorithm. Regarding the results, it was observed that the times required for processing the algorithms for both encoding and decoding are considerably reduced.Los sistemas de almacenamiento distribuido permiten resolver la fuerte demanda de almacenamiento de datos que requiere la sociedad actual. Es por ello que surgen nuevos retos relacionados con la recuperación de datos basada en código de borrado. En este artículo se presenta la paralelización del algoritmo Reed-Solomon a través de hilos. La evaluación se ha realizado en un sistema BLADE, la ejecución del algoritmo se ha realizado en una configuración de 1, 2, 4 y 8 hilos para comprobar el comportamiento del algoritmo. En cuanto a los resultados, se observa que se reducen considerablemente los tiempos requeridos para el procesamiento de los algoritmos tanto para codificación como para decodificación