Modeling Disaster Recovery By Estimating Rpo And Rto

1127 WordsMay 1, 20175 Pages
Modelling Disaster Recovery by Estimating RPO and RTO Thaila Annamalai (CSU ID: 830860017), thaila@colostate.edu Abstract— Disaster Recovery (DR) proposes strategies for choosing the pattern of DR for every business Unit. The importance of the business and the DR readiness is assessed by the recovery time objective (RTO) and recovery point objective (RPO). This assessing method make sure business continuity even under a drastic failure and a long disrupted period. The data backup and protection has become a basic requirement in networks because of the generation of data in huge volume from each business unit. The disasters that can occur has to be identified and should be evaluated…show more content…
Traditionally, the DRP was to back-up the data in a remote place and then access them during disaster. The storing of data remotely can take place in two ways either periodically or from time to time. These methods were costly and inefficient since large amount of storage was needed. The development in cloud computing paved a way for this problem. In cloud computing large amount of data can be generated and stored. Also, this gives real-time backup of data. Though only large scale business units use real-time backup other advantages of cloud computing are utilized by other business units. The primary working site and the backup site is separated. The probability of failure occurring in both sites at the same time is rare. The RTO is defined as the time during which the business unit is unavailable due to the failure. This includes the time of the disaster occurrence and the time needed to restore the functionalities. The RPO is the time period between two successive backups. This metric will let the user aware of the maximum amount of data that can be lost when the restoration is completed. The RPO should be close to 0 in an optimized DR system. MOTIVATION Disaster recovery has become the topic of interest in today’s research due to two main reasons: (1) The size of the computer data handled by the organizations are huge and are growing with time. (2) if the data loss is not handled within the

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