Abstract

In the pervasive computing environment using smart devices equipped with various sensors, a wireless data broadcasting system for spatial data items is a natural way to efficiently provide a location dependent information service, regardless of the number of clients. A non-flat wireless broadcast system can support the clients in accessing quickly their preferred data items by disseminating the preferred data items more frequently than regular data on the wireless channel. To efficiently support the processing of spatial window queries in a non-flat wireless data broadcasting system, we propose a distributed air index based on a maximum boundary rectangle (MaxBR) over grid-cells (abbreviated DAIM), which uses MaxBRs for filtering out hot data items on the wireless channel. Unlike the existing index that repeats regular data items in close proximity to hot items at same frequency as hot data items in a broadcast cycle, DAIM makes it possible to repeat only hot data items in a cycle and reduces the length of the broadcast cycle. Consequently, DAIM helps the clients access the desired items quickly, improves the access time, and reduces energy consumption. In addition, a MaxBR helps the clients decide whether they have to access regular data items or not. Simulation studies show the proposed DAIM outperforms existing schemes with respect to the access time and energy consumption.

Highlights

  • With the advent of smart mobile devices such as smart phones and tablets, which have processing capabilities almost as powerful as computers, and advances in wireless networks, the vision of pervasive computing has become real [1,2]

  • We evaluate the performance through simulations of the proposed DAIM with respect to the access time and tuning time, and evaluate energy consumption during the processing of given window queries for practical implications

  • To show the effectiveness of the proposed DAIM, we compare it to grid-based distributed index (GDIN) for non-flat broadcast and to Hilbert Curve Index (HCI), Distributed Spatial Index (DSI), and Cell-based Distributed Index (CEDI) for flat broadcast with respect to the access time

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Summary

Introduction

With the advent of smart mobile devices such as smart phones and tablets, which have processing capabilities almost as powerful as computers, and advances in wireless networks (e.g., the 4th generation mobile communication technology), the vision of pervasive computing has become real [1,2]. To help the clients efficiently access spatial data items of interest in an LDIS via wireless data broadcasts, air indexing schemes have been proposed for both flat and non-flat wireless data broadcasts. A grid-based distributed index (GDIN) in a non-flat spatial data broadcast was proposed to help the clients access desired data items when clients’ data access patterns are skewed to hot data items [10]. Over grid-cells (abbreviated DAIM) for non-flat spatial data broadcasting to efficiently support processing window queries when clients’ data access patterns are skewed. For the non-flat broadcast, DAIM broadcasts hot data items within MaxBRs in grid-cells more frequently in a broadcast cycle and broadcasts regular data items only once in the cycle. DAIM enables the clients to access their desired hot data items quickly by providing links to cells on the wireless channel.

Air Index Allocation Schemes
Data Search
Flat Broadcasting
Nonflat Broadcasting
Proposed Indexing Scheme
Index Structure
Channel Structure
Window Query Processing
Performance Evaluation
Simulation Environment
Comparison of the Access Time
Comparison of the Tuning Time
Comparison of the Consumed Energy
Findings
Conclusions

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