Critique & Summary of Scalable Network Distance Browsing in Spatial Databases

Introduction In today's world, the mapping services like Google Maps, Microsoft MapPoint etc have gained significant popularity for finding the shortest route while travelling from place to place. These services are available online and hence the responses of it must be real time i.e. very quick. Study has revealed that people do not change the parent query however may change the sub queries within it. This means people may search for objects within the vicinity of the destination like (restaurants, gas stations, ATMs etc.). Sometimes even these objects may remain constant however their attributes change drastically like (price of gas/gallon, type of food etc). The common algorithms like INE and IER are incorporated by these mapping services to achieve these quick responses. The INE, IER and similar methods do incorporate Dijkstra's Algorithm at some stage for the extraction of shortest path from source to destination. Hence the Dijkstra's Algorithm forms the very back bone of these methods. Dijkstra's Algorithm works in way that it visits every vertex near the source to calculate the shortest path that is nearest to the destination. The drawback of this is that it visits far too many vertices and has to store the shortest path from each vertex between source and the destination. Also even if the sub query is changed it calculates the entire shortest route again.