Practically Realizable Efficient Data Allocation and Replication Strategies for Distributed Databases with Buffer Constraints

In this paper, we address the performance of distributed database systems with buffer constraints. Specifically, our objective is to design and analyze efficient data allocation and replication strategies to minimize the total servicing cost for an arbitrary read/write request sequence, under finite buffer constraints of the nodes in the system. When the available buffer space in a node is not enough to store a copy of an object, the decision has to be made on whether or not we should evict one or more objects in use to give room for the new object copy. In this paper, we design and analyze the data replication strategies with the model of dynamic window mechanism (DWM) algorithm jointly implemented with different types of object replacement strategies (no replacement, LRU, and LFU) commonly found in practice. We consider situations wherein the object sizes are identical as well as heterogeneous. We will show the impact on the performance of the allocation and replication strategies due to the limited local database buffer capacities. We analyze and quantify theoretically (using competitive analysis) the performances of all the proposed algorithms. Further, we perform rigorous simulation experiments to validate the findings with respect to several influencing parameters. Several useful conclusions are drawn based on the experimental results and we highlight the usefulness of the algorithms under different situations

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