A comprehensive review of the data replication techniques in the cloud environments: Major trends and future directions. (April 2016) - Alami Milani, Bahareh; Jafari Navimipour, Nima
Abstract: Nowadays, in various scientific domains, large data sets are becoming an important part of shared resources. Such huge mass of data is usually stored in cloud data centers. Therefore, data replication which is generally used to manage large volumes of data in a distributed manner speeds up data access, reduces access latency and increases data availability. However, despite the importance of the data replication techniques and mechanisms in cloud environments, there has not been a comprehensive study about reviewing and analyzing its important techniques systematically. Therefore, in this paper, the comprehensive and detailed study and survey of the state of art techniques and mechanisms in this field are provided. Also, we discuss the data replication mechanisms in the cloud systems and categorize them into two main groups including static and dynamic mechanisms. Static mechanisms of data replication determine the location of replication nodes during the design phase while dynamic ones select replication nodes at the run time. Furthermore, the taxonomy and comparison of the reviewed mechanisms are presented and their main features are highlighted. Finally, the related open issues and some hints to solve the challenges are mapped out. The review indicates that some dynamic approaches allow their associated replication strategies to be adjusted at run time according to changes in user behavior and network topology. Also, they are applicable for a service-oriented environment where the number and location of the users who intend to access data often have to be determined in a highly dynamic fashion. Highlights: Discussing the most important data replication mechanisms in cloud environments. Categorizing the data replication mechanisms into static and dynamic mechanisms. Presenting the comparison of the reviewed mechanisms and highlighting their features. Mapping out the related open issues and some hints to solve the challenges.