RPMSP: A Novel Replica Placement Method Inspired by Self-Similarity Propagation of Plants

Replica placement method determines replica layout directly and affects resource management of cloud storage indirectly. Since the imbalance of performance indicators in the issue of replica placement, this paper proposes a novel replica placement method inspired by self-similarity propagation of plants (RPMSP). Firstly, the issue of replica placement affected by multiple performance indicators is modeled as the objective space. Then, the method simulates the self-similarity propagation of plants to find the most profitable area and selects the optimal individual from it as the most suitable replica layout. Finally, it conducted several simulation experiments to evaluate the proposed method. The experimental results show that RPMSP can effectively find a suitable replica layout and balance the relationship among multiple performance indicators.