In this paper, we propose a concurrency control algorithm based on link-technique for high-dimensional index structures. In high dimensional index structures, search operations are generally more frequent than insert or delete operations and need to access more nodes than those in other index structures, such as B+-tree, B-tree, hashing techniques, and so on, due to the properties of queries. In the proposed algorithm, we focus on minimizing the delay of search operations in all cases. It also supports concurrency control on reinsert operations for the high-dimensional index structures employing reinsert operations to improve their performance. We apply the algorithm to one of the exiting multi-dimensional index structures and implement it on a storage system. It is shown through various experiments that the proposed algorithm is more suitable for high dimensional index structures than existing ones.
This chapter introduces a concurrency control algorithm based on link-technique for high-dimensional index structures. In high-dimensional index structures, search operations are generally more frequent than insert or delete operations and need to access many more nodes than those in other index structures, such as B+-tree, B-tree, hashing techniques, and so on, due to the properties of queries. This chapter proposed an algorithm that minimizes the delay of search operations in all cases. The proposed algorithm also supports concurrency control on reinsert operations for the high-dimensional index structures employing reinsert operations to improve their performance. The authors hope that this chapter will give helpful information for studying multidimensional index structures and their concurrency control problems to researchers.
Existing methods to process continuous range queries are not scalable. In particular, as the number of continuous range queries on a large number of moving objects becomes larger, their performance degrades significantly. We propose a novel query indexing method called the projected attribute bit (PAB)‐based query index. We project a two‐dimensional continuous range query on each axis to get two one‐dimensional bit lists. Since the queries are transformed to bit lists and query evaluation is performed by bit operations, the storage cost of indexing and query evaluation time are reduced significantly. Through various experiments, we show that our method outperforms the containment‐encoded squares‐based indexing method, which is one of the most recently proposed methods.
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