Indexing and querying technique for dynamic location updates using R k-d trajectory trie tree

The area of spatiotemporal applications which engage moving objects is a treasure trove of new types of queries. Essentially querying the trajectories of moving objects (MOVObjs) has long been an attractive and demanding area which buds as various fascinating applications in Spatio-Temporal Databases (STDb). Robust index structure is required to achieve better search performance of their trajectories. In this paper, a novel data structure R k-d trajectory trie tree to index the trajectories of MOVObjs and three new algorithms to support trajectory pattern matching queries have been proposed. The performance analysis shows that the time complexity of the proposed R k-d trajectory trie tree is reduced to O (TL), in which TL represents the average trajectory length, whereas other data structures like TMN, MON and FNR tree have time complexities of O (n
²
), O (n
²
log
²
n) respectively. Through a novel index maintenance technique which is associated with dynamic location updates, tree can support three new advanced types of queries such as full, partly and recurrent trajectory pattern matching queries.