Spatial query processing in road networks for wireless data broadcast

  • Authors:

  • Yanqiu Wang;Chuanfei Xu;Yu Gu;Mo Chen;Ge Yu

  • Affiliations:

  • College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819;College of Information Science and Engineering, Northeastern University, Shenyang, China 110819

  • Venue:
  • Wireless Networks
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recently, wireless broadcast environments have attracted significant attention due to its high scalability to broadcast information to a large number of mobile subscribers. It is especially a promising and desirable dissemination method for the heavily loaded environment where a great number of the same type of requests are sent from the users. There have been many studies on processing spatial queries via broadcast model recently. However, not much attention is paid to the spatial queries in road networks on wireless broadcast environments. In this paper, we focus on three common types of spatial queries, namely, k nearest neighbor (kNN) queries, range queries and reverse nearest neighbor (RNN) queries in spatial networks for wireless data broadcast. Specially, we propose a novel index for spatial queries in wireless broadcast environments (ISW). With the reasonable organization and the effectively pre-computed bounds, ISW provides a powerful framework for spatial queries. Furthermore, efficient algorithms are designed to cope with kNN, range and RNN queries separately based on ISW. The search space can be obviously reduced and subsequently the client can download as less as possible data for query processing, which can conserve the energy while not significantly influence the efficiency. The detailed theory analysis of cost model and the experimental results are presented for verifying the efficiency and effectiveness of ISW and our methods.