Optimizing in-network aggregate queries in wireless sensor networks for energy saving

Hung, Chih‐Chieh; Peng, Wen-Chih

doi:10.1016/j.datak.2011.03.008

Cited by 11 publications

(10 citation statements)

References 31 publications

(41 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Also in terms of query processing time, BPA showed 56% higher performance than IWQE and 26% higher than TAG. Q TNODE qn = QT Build(sni, nodelist) (5) I R O U T Ei r= QT CNode Itinerary(qn, nodelist) (6) if(QNodeIs() || DNodeIs()) (7)…”

Section: Results Of Performance Evaluationmentioning

confidence: 99%

“…As in Figure 6, query region QR is divided into CR 1 , CR 2 , CR 3 and CR 4 , and CR 4 is again subdivided into CR 5 , CR 6 , CR 7, and CR 8 , and again CR 8 into CR 9 , CR 10 , CR 11, and CR 12 . Each cell is subdivided until the number of sensor nodes in the cell becomes smaller than the threshold maximum number of sensor nodes in each cell.…”

Section: Bpa (Bucket-based Parallel Aggregation)mentioning

confidence: 99%

“…Accordingly, root node g has a range value of (1,8), and its child nodes e and f have range values of (1, 4) and (5,8), respectively. In addition, child nodes a, b, c, and d have range values of (1, 2), (3,4) and (5,6) and (7,8), respectively. Moreover, each node stores the number of sensed data that belong to its range.…”

Section: Q-digest (Quantile-digest)mentioning

confidence: 99%

“…Thus, in order to reduce the energy consumption of sensor nodes, aggregate query processing in network is being studied actively, which processes aggregate queries on sensed data in the sensor nodes and then sends the results to the server [5][6][7]. Representative techniques of aggregate query processing in network include TAG (Tiny AGgregation) and IWQE (Itinerary-based Window Query Execution) that focus on routing algorithm, and q-digest (quantile digest) and SMC (Secure Median Computation) that focus on data structure [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Aggregate Queries in Wireless Sensor Networks

Kim

Shin

Zhang

et al. 2012

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Recently as efficient processing of aggregate queries for fetching desired data from sensors has been recognized as a crucial part, in-network aggregate query processing techniques are studied intensively in wireless sensor networks. Existing representative innetwork aggregate query processing techniques propose routing algorithms and data structures for processing aggregate queries. However, these aggregate query processing techniques have problems such as high energy consumption in sensor nodes, low accuracy of query processing results, and long query processing time. In order to solve these problems and to enhance the efficiency of aggregate query processing in wireless sensor networks, this paper proposes Bucket-based Parallel Aggregation (BPA). BPA divides a query region into several cells according to the distribution of sensor nodes and builds a quadtree, and then processes aggregate queries in parallel for each cell region according to routing. It sends data in duplicate by removing redundant data, which, in turn, enhances the accuracy of query processing results. Also, BPA uses a bucket-based data structure in aggregate query processing, and divides and conquers the bucket data structure adaptively according to the number of data in the bucket. In addition, BPA compresses data in order to reduce the size of data in the bucket and performs data transmission filtering when each sensor node sends data. Finally, in this paper, we prove its superiority through various experiments using sensor data.

show abstract

Section: Results Of Performance Evaluationmentioning

confidence: 99%

Section: Bpa (Bucket-based Parallel Aggregation)mentioning

confidence: 99%

Section: Q-digest (Quantile-digest)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Aggregate Queries in Wireless Sensor Networks

Kim

Shin

Zhang

et al. 2012

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

show abstract

“…Many deal with techniques for efficient processing of aggregate queries [1][2][3]. Other proposals deal with energy-efficient methods to reduce energy consumption during query processing [4][5][6].…”

Section: Related Workmentioning

confidence: 99%

An Efficient Processing of Join Queries for Sensor Networks Using Column-Oriented Databases

Kim

2013

International Journal of Distributed Sensor Networks

View full text Add to dashboard Cite

Recently, the sensor network area is gaining attention both in the industry and academia. Many applications of sensor network such as vehicle tracking and environmental monitoring require joining sensor data scattered over the network. The main performance criterion for queries in a sensor network is to minimize the battery power consumption in each sensor node. Hence, reducing the communication cost of shipping data among sensor nodes is important since it is the main consumer of battery power. In this paper, we propose a technique for join queries in a sensor network that minimizes communication cost. For storage of sensor data, we use a column-oriented database that stores data on disk (or in memory) column-by-column unlike traditional database that store data in rows. The justification for using a column-oriented database technique is not to ship those data columns that do not participate in the actual join. We compare our algorithm with existing join algorithms for sensor networks that are based on traditional roworiented databases. The performance analysis show that our proposed algorithm based on column-oriented databases outperforms existing algorithms in processing binary equi-join (BEJ) queries for sensor networks.

show abstract

Energy Saving Model for Sensor Network Using Ant Colony Optimization Algorithm

Doreswamy

Narasegouda

2014

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Optimizing in-network aggregate queries in wireless sensor networks for energy saving

Cited by 11 publications

References 31 publications

Aggregate Queries in Wireless Sensor Networks

Aggregate Queries in Wireless Sensor Networks

An Efficient Processing of Join Queries for Sensor Networks Using Column-Oriented Databases

Energy Saving Model for Sensor Network Using Ant Colony Optimization Algorithm

Contact Info

Product

Resources

About