Shortest Average-Distance Query on Heterogeneous Neighboring Objects

Abstract

In recent years many researchers focus on how to effectively manage objects on the server side and then provide the user to query the objects over the wireless network Such a system allows user to query information of objects around him at anytime and anywhere This type of query associated with the location of static or moving objects is called the location-based query Most of processing techniques for the conventional location-based queries focus on single type of objects (i e single data source) such as finding a nearest restaurant to the user (nearest neighbor queries) or finding the theaters closer to the user (range queries) However in real life there are many different types of objects We term the different types of objects (i e multiple data source) the heterogeneous objects (HOs for short) If the distance between any two objects in HOs is less than or equal to the user-defined distance d then the HOs is a heterogeneous neighboring objects (HNOs for short) In this thesis we propose a novel and useful location-based query on the HNOs so as to provide the useful HNOs information Such a location-based query is named the shortest average-distance query (SADQ for short) Consider the n types of data sources HO1 HO2 HOn Assume that there exist m sets of HNOs SADQ finds a set of HNOs with the shortest average-distance among these m sets of HNOs To efficiently process the shortest average-distance query we develop an efficient algorithm the SADQ algorithm It can reduce the computation cost for answering the SADQ Comprehensive experiments are performed on both synthetic and real datasets to demonstrate the effectiveness and the efficiency of the SADQ algorithm

Date of Award	2014 Jul 18
Original language	English
Supervisor	Chiang Lee (Supervisor)