Energy-Efficient Query Management Scheme for a Wireless Sensor Database System

Guofang Nan,Minqiang Li

doi:10.1155/2010/978694

Abstract

Minimizing the communication overhead to reduce the energy consumption is an essential consideration in sensor network applications, and existing research has mostly concentrated on data aggregation and in-network processing. However, effective query management to optimize the query aggregation plan at the gateway side is also a significant approach to energy saving in practice. In this paper, we present a multiquery management framework to support historical and continuous queries, where the key idea is to reduce common tasks in a collection of queries through merging and aggregation, according to query region, attribute, time duration, and frequency, by executing the common subqueries only once. In this framework, we propose a query management scheme to support query partitioning, region aggregation and approximate processing, time partitioning and aggregation rules, multirate queries, and historical database. In order to validate the performance of our algorithm, a heuristic routing protocol is also described. The performance simulation results show that the overall energy consumption for forwarding and answering a collection of queries can be significantly reduced by applying our query management scheme. The advantages and disadvantages of the proposed scheme are discussed, together with open research issues.

Highlights

With the development of low-power hardware manufacturing and integration, it is possible to design tiny sensor devices combining the abilities of sensing, computation, storage, and communication [1]
Many of the WSN techniques designed to extend the network lifetime are concentrated on modified routing protocols [4,5,6], in-network processing [7, 8], node sleep scheduling
The energy reduction comes from both historical query and query aggregation; Table 3 shows an average of 6.64 queries which can be fully answered by historical database, an average of 7.84 queries which can be partially answered by historical database and an average of 7.44 aggregated queries

Summary

Introduction

With the development of low-power hardware manufacturing and integration, it is possible to design tiny sensor devices combining the abilities of sensing, computation, storage, and communication [1]. These nodes collect sensor data and communicate with each other, forming a network to monitor objects, animals, people, temperature, humidity, and so on in a given area [2]. Recent studies have shown that radio communication is significantly more expensive than computation or sensing in most existing sensor node platforms, the main consideration is to minimize the communication overhead of forwarding queries and transmitting queried data between gateway and source nodes [14].

Objectives

Results

Conclusion