Disaster recovery in cloud computing: a survey <s> Resource Management <s> Requirements for restoring telecommunication services to businesses following a disaster such as the central office fire in the Chicago suburb of Hinsdale in 1988 or the recent California earthquake are delineated, and roadblocks to marketing contingency planning and disaster recovery solution are identified. US West's disaster recovery strategies and disaster recovery marketing programme are described. An illustrative case study is presented. > <s> BIB001 </s> Disaster recovery in cloud computing: a survey <s> Resource Management <s> With the dramatic evolution of various greener disk and memory technologies, helped in rapid establishment of Hybrid storage environment comprising of heterogeneous storage units. In order to provide an efficient and optimised storage solution there exists a necessity of adapting smarter changes in the management stack that enables compact sensing, processing, decision making capability based on the importance of data and disk life span predicted on operational workloads. This paper reviews system architecture for two faces of RAS cloud features namely disaster recovery planning, disk breakage prediction independent of disk technology and host aware data tier based on disk life span. <s> BIB002
Heterogeneous clouds consist many different hardware and software such as hybrid storage and diverse disks. In cloud-based enterprises, entire business data are stored in the cloud storage. So, data protection, safety and recovery are critical in these environments. Data in danger is the data which has been processed at the primary host but has not taken place in the backup host yet. So, in the case of disaster, It is necessary to use enhanced www.ccsenet.org/cis Computer and Information Science Vol. 7, No. 3; technology for data recovery in storage clouds. There are three solutions for data recovery proposed in BIB002 :  Using fastest disk technology in the event of a disaster for replication of data in danger.  Changing dirty page threshold: The percentage of dirty pages in RAM which have to be waited for flushing to disk might be reduced BIB001 .  Prediction and replacement of risky devices: Some important factors such as power consumption, heat dissipation, carbon credit utilization and importance of data (stored on each disk) can be calculated in a specific period of time. By these factors, a mathematical equation will be formed to make a replace priority list.