In this chapter we described the concept of multicloud architecture in which locally distributed clouds are combined to provide combined services of locally distributed clouds to the users. We started with basic of cloud computing and reached to multicloud through single cloud. In this chapter have described four architectural models for multicloud. Architecture models are Repetition of applications, Partition of System architecture into layers, Partition of Security features into segments and Distributing of data into fragments with these models security of the data resides in the datacenters of the cloud computing must be increased which leads to reliability in data storing of data.

In this chapter we described the concept of multicloud architecture in which locally distributed clouds are combined to provide combined services of locally distributed clouds to the users. We started with basic of cloud computing and reached to multicloud through single cloud. In this chapter have described four architectural models for multicloud. Architecture models are Repetition of applications, Partition of System architecture into layers, Partition of Security features into segments and Distributing of data into fragments with these models security of the data resides in the datacenters of the cloud computing must be increased which leads to reliability in data storing of data.

Abstract

Automatic identification of anomalies for performance diagnosis in the cloud computing is a fundamental and challenging issue. TPA is interested to identifies these anomalies and remove them so that the performance of the cloud systems increased. In this paper we are proposing an Automatic Black Box Anomaly Detector which can find anomalies automatically with minimum human intervention. Using this detector we can find old and even new anomalies created in the cloud computing systems even if we don't have knowledge of source code (i.e. black box testing). Automatic black box anomaly detection is a two step process in which first of all data from different sources is collected and transform it into a common form that is act as input for black box anomaly detector and secondly anomaly detection is performed. General TermsAnomaly detection in cloud computing. KeywordsBlack box anomaly detector, cloud service provider, performance diagnosis, cloud systems.

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