Multi-user Searching of Top-k Objects with Data on Remote Servers.
Erik Horničák, Matúš Ondreička, Jaroslav Pokorný, Peter Vojtáš · 2011
Abstract. This paper focuses on searching the best k objects with more attributes according to user preferences in the Web environment. Attributes of an object type are distributed on servers in a disjunctive way, i.e. values of one attribute are stored in only one remote server on the Internet. In our work, every user can express his/her preferences for each attribute by a fuzzy function and mutual relations between the attributes by an aggregation function. We use client/server architecture and communication via Web Services. We deal with the usage of Fagin’s NRA algorithm, which can find the best k objects without accessing all the objects. Because of support of sorting objects according to a fuzzy function, an indexing method based on B+-tree is used in each remote server. Moreover, each server is stateless, i.e. independent from any previous request. Our solution is based on cache memory, which loads objects from remote servers in batches and thus reduces the amount of network communication. In this paper we present a system TOPKNET, which can efficiently find the best k objects for various users with data on remote servers. 1