An Efficient Communication Topology using Societal Computing

Abstract

In the era of mobile development, Social computing technology has reached the next form of getting collaborated. We study a new type of K-Cover Group (KCG) queries that, given a set of query points and giving boundary towards the exploration of view from various users. The idea of collaborative social computing has been widely used in various domains, including location-based social networks (LBSNs), Geo-crowdsourcing, activity planning, group decision making, and disaster rescue. One of the most important applications of collaborative social computing in the database field is social queries, which are attracting increasing interest from both industrial and academic communities. The proposed social queries which take as inputs a set of query location point and certain social acquaintance constraint and return a set of users with minimum location distance while satisfying the social constraint. We formally define a KCG query to capture natural requirements driven by the real-life applications. For the social factor, instead of finding a group whose associated regions jointly cover a set of query points? Here we quantify the desire social relationship within a user group in terms of k-core. And also we propose a novel index structure, known as the Enhanced SaR-tree. It is easy to extend our algorithm to support the case where each user has multiple associated regions. The following branch and bounding process remains the same as the case where each user has exactly one associated region.