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aggregate query processing sensor networks

Aggregate query processing in the presence of duplicates

Mar 10, 2015· In addition, when the sensing areas of sensor nodes are disjoint, the coordinator of each sensor becomes itself and we perform traditional aggregate query processing. Thus, the problem we are considering is a generalization of the traditional in-network aggregation problem.

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Processing Multiple Aggregation Queries in Geo-Sensor Networks

This observation points out the fact that the in-network query processing is more energy efficient. Fig. 7(c) shows the response time. This time all proposed approaches performs the same and BS remains the best. 5 Conclusion and Future Work Aggregation queries are very important for sensor-network

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Aggregate Threshold Queries in Sensor Networks IEEE

Mar 30, 2007· Abstract: An important class of queries over sensor networks are network-wide aggregation queries. In this work we study a class of aggregation queries which we refer to as aggregate threshold queries. The goal of an aggregate threshold query is to continuously monitor the network and give a notification every time an aggregated value crosses a predetermined threshold

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Robust and Efficient Aggregate Query Processing in

Wireless sensor networks have been widely used in many applications, such as soil temperature monitoring for plant growth and abnormal event detection of industrial parameters. Among these applications, aggregate queries, such as SUM, COUNT, AVERAGE, MIN and MAX are often used to collect statistical data.

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Processing Multiple Aggregation Queries in Geo-Sensor Networks

Aggregate query processing in sensor networks is an orthogonal topic to our discussion. Quite a few papers from the database community have been addressing techniques and solutions for this topic

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Robust and Efficient Aggregate Query Processing in

Wireless sensor networks have been widely used in many applications, such as soil temperature monitoring for plant growth and abnormal event detection of industrial parameters. Among these applications, aggregate queries, such as SUM, COUNT, AVERAGE, MIN and MAX are often used to collect statistical data.

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(PDF) Routing and processing multiple aggregate queries in

Poster Abstract: Routing and Processing Multiple Aggregate Queries in Sensor Networks Niki Trigoni Alexandre Guitton Antonios Skordylis Birkbeck College, University of London, London WC1E 7HX, United Kingdom {niki,alexandre,adonis}@dcs.bbk.ac.uk Abstract We present a novel approach to processing continuous aggregate queries in sensor networks, which lifts the as- sumption of tree

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Interplay of processing and routing in aggregate query

Interplay of processing and routing in aggregate query optimization for sensor networks Niki Trigoni Alexandre Guitton Antonios Skordylis Computing Laboratory, University of Oxford, Oxford OX1 3QD, UK Abstract. This paper presents a novel approach to processing continuous aggre-gate queries in sensor networks, which lifts the assumption of tree

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Query Processing for Sensor Networks

to ensure that the query processing layer is tightly in-tegrated with the networking layer. Second, the notion of the cost of a query plan has changed, as the critical resource in a sensor network is power, and query opti-mization and query processing have to

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IJA: An Efficient Algorithm for Query Processing in Sensor

Sensor nodes are generally highly constrained, in particular regarding their energy and memory resources. While simple queries such as SELECT and AGGREGATE queries in wireless sensor networks have been addressed in the literature, the processing of join queries in sensor networks remain to be investigated.

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Optimized Query Processing for Wireless Sensor Networks

sensor networks is similar to saving and query processing in conventional database. Although infrastructure property and data properties of sensor networks is different with a central database system complementally [1]. We use declarative query in interaction networking. Declarative query playas an interface role. User able

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Optimizing Multiple In-Network Aggregate Queries in

in-network query processing for power saving in wireless sensor networks [3][5][6]. Prior works [2][6] explore the feature of in-network aggregation in which sensor nodes in a routing tree are able to perform aggregate operators. The authors in [1] proposed in-network materialized view that

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Processing approximate aggregate queries in wireless

Dec 01, 2006· Consider a node Root, which initiates a continuous query over the values observed by a set of data sources, and requests that the results of this query be reported to it at regular time periods.The time interval between two such consecutive time periods is referred to as the epoch of the query. The continuous query is disseminated through the network in search of the sensor nodes

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aggregate query processing in peer to peer networks with

aggregate quarry processing sensor networks aggregate query processing in peer to peer networks with, requirements including quarry, . On the Use of Histograms for Processing Exact, On the Use of Histograms for Processing Exact Aggregate Queries in Wireless Sensor Networks Khaled Ammar Mario A Nascimento Department of,

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Processing Approximate Aggregate Queries In Wireless

Processing approximate aggregate queries in wireless. Dec 01, 2006· In-network data aggregation has been recently proposed as an effective means to reduce the number of messages exchanged in wireless sensor networks Nodes of the network form an aggregation tree, in which parent nodes aggregate the values received from their children and propagate the result to their own parents

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Processing Multiple Aggregation Queries in Geo-Sensor Networks

Aggregate query processing in sensor networks is an orthogonal topic to our discussion. Quite a few papers from the database community have been addressing techniques and solutions for this topic

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Energy-Efficient Data Organization and Query Processing in

Recent sensor networks research has produced a class of data stor-age and query processing techniques called Data-Centric Storage that leverages locality-preserving distributed indexes to efficiently answer multi-dimensional range and range-aggregate queries. These distributed indexes offer a rich design space of a) logical decompo-

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