Progressive Processing of Continuous Range Queries in Hierarchical Wireless Sensor Networks

In this paper, we study the problem of processing continuous range queries in a hierarchical wireless sensor network. Contrasted with the traditional approach of building networks in a "flat" structure using sensor devices of the same capability, the hierarchical approach deploys devices of higher capability in a higher tier, i.e., a tier closer to the server. While query processing in flat sensor networks has been widely studied, the study on query processing in hierarchical sensor networks has been inadequate. In wireless sensor networks, the main costs that should be considered are the energy for sending data and the storage for storing queries. There is a trade-off between these two costs. Based on this, we first propose a progressive processing method that effectively processes a large number of continuous range queries in hierarchical sensor networks. The proposed method uses the query merging technique proposed by Xiang et al. as the basis and additionally considers the trade-off between the two costs. More specifically, it works toward reducing the storage cost at lower-tier nodes by merging more queries, and toward reducing the energy cost at higher-tier nodes by merging fewer queries (thereby reducing "false alarms"). We then present how to build a hierarchical sensor network that is optimal with respect to the weighted sum of the two costs. It allows for a cost-based systematic control of the trade-off based on the relative importance between the storage and energy in a given network environment and application. Experimental results show that the proposed method achieves a near-optimal control between the storage and energy and reduces the cost by 0.989~84.995 times compared with the cost achieved using the flat (i.e., non-hierarchical) setup as in the work by Xiang et al.Comment: 41 pages, 20 figure

A Query Result Merging Scheme for Providing Energy Efficiency in Underwater Sensor Networks

Underwater sensor networks are emerging as a promising distributed data management system for various applications in underwater environments, despite their limited accessibility and restricted energy capacity. With the aid of recent developments in ubiquitous data computing, an increasing number of users are expected to overcome low accessibility by applying queries to underwater sensor networks. However, when multiple users send queries to an underwater sensor network in a disorganized manner, it may incur lethal energy waste and problematic network traffic. The current query management mechanisms cannot effectively deal with this matter due to their limited applicability and unrealistic assumptions. In this paper, a novel query management scheme involving query result merging is proposed for underwater sensor networks. The mechanism is based on a relational database model and is adjusted to the practical restrictions affecting underwater communication environments. Network simulations will prove that the scheme becomes more efficient with a greater number of queries and a smaller period range

2004 IEEE International Conference on Mobile Ad-hoc and Sensor Systems Query Aggregation for Providing Efficient Data Services in Sensor Networks

Abstract--P)oviding efficient &tu senices is one of the fundamental requirements for sensor networks The doto senice paradigm requires that the application submit its requests as quen'es and the sensor network transmits the requested dala to the applieotior While most &ting work in this area focus6 on data aggregation, no1 much attention has been paid lo query aggregation. For many opplic~~oons, especially ones with high query rales, query eggregation is very important. In this paper, we sludy a query aggregation-based opproach for providing efficient dola services. In particular: I) we propose a multi-layered overlqbased framework consisting of a query manager and access points (nodes), where the former provides the query aggregation plan and the latter exefates the plan; 2) we design an eflective query aggregation algorithm to reduce the number of duplicatdwerlnpping queries and sme overall energy consumplion in the sensor network. Our performance evaluations show tho / by applying our query aggregction dgorilhm, the overall energy consumption con be significantly reduced and the sensor network li/time can be prolonged correspondingly. Keyword.Mcnsor Network, Query Aggregation 1