This paper presents a survey of data replication strategies in cloud systems. Based on the survey and reviews of existing classifications, we propose another classification of replication strategies based on the following five dimensions: (i) static vs. dynamic, (ii) reactive vs. proactive workload balancing, (iii) provider vs. customer centric, (iv) optimal number vs. dynamic adjustment of the replica factor and (v) objective function. Ideally, a good replication strategy must simultaneously consider multiple criteria: (i) the reduction of access time, (ii) the reduction of the bandwidth consumption, (iii) the storage resource availability, (iv) a balanced workload between replicas and (v) a strategic placement algorithm including an adjusted number of replicas. Therefore, selecting a data replication strategy is a classic example of multiple criteria decision making problems. The taxonomy we present can be a useful guideline for IT managers to select the data replication strategy for their organization.
Cloud providers aim to maximise their profits while satisfying tenant requirements, e.g., performance. The relational database management systems face many obstacles in achieving this goal. Therefore, the use of NoSQL databases becomes necessary when dealing with heterogeneous workloads and voluminous data. In this context, we propose a new data replication strategy that balances the workload of nodes and dynamically adjusts the number of replicas while the provider profit is taken into account. Result analysis shows that the proposed strategy reduces the resource consumption, which improves the provider profit while satisfying the tenant performance requirement.
Cloud providers aim to maximise their profits while satisfying tenant requirements, e.g., performance. The relational database management systems face many obstacles in achieving this goal. Therefore, the use of NoSQL databases becomes necessary when dealing with heterogeneous workloads and voluminous data. In this context, we propose a new data replication strategy that balances the workload of nodes and dynamically adjusts the number of replicas while the provider profit is taken into account. Result analysis shows that the proposed strategy reduces the resource consumption, which improves the provider profit while satisfying the tenant performance requirement.
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