An efficient hybridized index technique for moving object database

Abstract

Indexes are needed in order to index a number of moving object’s positions to provide answers to different types of queries as fast as possible. The most popular types of querying techniques in moving object databases are K-Nearest Neighbor and Rang queries. In KNN, a set of k points of interest that can be reached in a minimum response time are retrieved. For Range Query, all objects whose positions fall within a predefined rectangular or circular range are retrieved. Creating an efficient index for objects’ locations is looked upon as the most critical problem in connection with spatial–temporal data management. Indexes are different based on their structures, query processing, and update performance. In this context, this paper aims to hybridize both tree and grid based structures to enhance update, search, and insert in the index. To achieve this goal, the current paper will discuss the design of the proposed index.