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Some of them have attempted to provide full spatio temporal support but have poor performance for complex spatio temporal aggregate queries In addition while the volume of sensor data is rapidly growing the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved In this article we introduce EAGLE a spatio temporal query engine
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Aggregate Query Processing in Cache Aware Wireless Sensor Networks Khaled Ammar University of Alberta Agenda Introduction Previous Work Contribution Selection Process Hot Area Conclusion Future Work References Introduction Slideshow 5468044 by vinson
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Wireless Sensor Networks WSNs are increasingly involved in many applications However communication overhead and energy efficiency of sensor nodes are the major concerns in WSNs In addition the broadcast communication mode of WSNs makes the network vulnerable to privacy disclosure when the sensor nodes are subject to malicious behaviours Based on the abovementioned issues we present a
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Processing approximate aggregate queries in wireless sensor networks 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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The in network aggregation paradigm in sensor networks provides a versatile approach for evaluating aggregate queries Traditional approaches need a separate aggregate to be computed and communicated for each query and hence do not scale well with the
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ports the map representation of the sensor network data Assuming a confidence function C s l which is dependent of the sensor network setting but is query independent we denote the query by STDMap qID sr tr ct with the follow ing characteristics • It is identified in the sensor network using a unique query identifier qID
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tention paid to efficient query processing for aggregate queries [15 20 23] In the TAG system [15] users connect to the sen sor network using a workstation or base station directly connected to a sensor designated as the sink Aggregate queries over the sensor data are formulated using a sim ple SQL like language then distributed across
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In network aggregation can be optimized to decrease the en ergy consumption of such types of aggregate queries in a WSN [17] Essentially such optimizations avoid sending all values to the sink root node However in order to solve more complex aggregate queries such as nding the median or quantiles of the node values it is still necessary
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energy efficient aggregate query evaluation in sensor networks this paper considers the evaluation in a database with the objective to prolong the lifetime we first propose an algorithm by introducing a node capability concept that balances the residual energy and the energy consumption at each node so that the lifetime is prolonged
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Thus we use the base station as a filter to re SELECT FROM WHERE clause supporting selection pro duce duplicate data access to the sensor network and as a jection and aggregation in addition to EPOCH DURA screen to hide the query dynamics from the sensor network TION clause to define the frequency that the sensor data as much as possible
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The vast majority of advances in sensor network research over the last five years have focused on the development of a series of small scale 100s of nodes testbeds and specialized applications environmental monitoring etc that are built on low powered sensor devices that self organize to form application specific multihop wireless networks
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Q uery dissemination phase The home node dissemi nates the query message to all sensor nodes inside the KNN boundary Dissemination follows parallel itinerary struc tures and query responses are aggregated along with each itinerary traversal At the end of dissemination the aggre gatedqueryresponsesaredirectly routedbacktothesinkin a bundle
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sensor networks as distributed databases with users tasking the network with declarative queries which are then converted by a front end query processor into an efficient query plan for in net work processing Similarly Govindan et al also argue in [9] that sensor networks ought to be viewed primarily as virtual databases with query
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Once the WSN is active and nodes are collecting data a number of queries can be issued spatio temporal range queries join queries and aggregate queries for which a large number of algorithms have been proposed [1 3 11 14 20 19 25]
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Title Query Processing in Sensor Networks 1 Query Processing in Sensor Networks 11/09/2024 Se Ho Park Hyun Ik Jang Frolin Rusu W Hong S Madden Implementation and Research Issues in Query Processing for Wireless Sensor Networks ICDE 2024 2 Outline 3 Outline 4 Query Processor 5 No Transcript 6 TinyDB Root gateway node Distributed in Network Query processor Wireless Sensor networks 7
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3 4 5 1] In this paper we study how we can process aggregate queries efficiently on a sensor network with minimum communica tion among the sensors As our next example illustrates aggregate queries are one of the most expensive queries to support because we potentially have to retrieve the current value from every sensor
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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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A note on efficient aggregate queries in sensor networks message may consume as much power as a thousand processing cycles Therefore it is highly desirable to reduce the amount of data transmitted possibly by doing more local processing This basic motivation underlies sensor network systems like TAG [9] Cougar [15] and others see [16] Intuitively the idea is to view
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Motivation Sensor Nets and In Network Query Processing Many Sensor Network Applications are Data Oriented Queries Natural and Efficient Data Processing Mechanism Easy unlike embedded C code Enable optimizations through abstraction Aggregates Common Case Which rooms are in use In network processing a must Sensor networks power and
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For cooperative processing in a sensor network the information of interest is not the data at an individual sensor node but the aggregate statistics aggregates amid a group of sensor nodes [19] [15] Possible applications using aggregates are the average temperature the average gas concentration of a hazardous gas in an area the average
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Proposed algorithms [96 148 151] process such aggregate queries in two phases In the rst phase called Broadcast the query oods the network and a spanning tree is built on the sensors Figure b In the second phase called Convergecast sub treecountsare propagated upfrom theleavesto theroot Figure c
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We now briefly describe the data aggregation process in sensor networks when 100% accuracy ignoring network delays or lost messages is desired in the querying node and when utilizing the TAG [2] model to synchronize the transmission of data values by the sensor nodes
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Query Processing for Sensor Networks Yong Yao Johannes Gehrke Department of Computer Science Cornell University Ithaca NY 14850 {yao johannes} Abstract Hardware for sensor nodes that combine phys ical sensors actuators embedded processors and communication components has advanced significantly over the last decade and made the large scale deployment of such sensors a
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gate queries over sensor networks in an energy efficient manner From the databases perspective in network aggregation provides a mechanism for evaluating aggregate queries over sensor networks The common approach to aggre gate query processing in sensor networks has two phases the dissemination phase and the aggregation phase For
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Wireless sensor networks WSNs have received increasing attention in the past decade In existing studies for query processing of WSNs each sensor n…
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In Proceedings of the ACM Data Management for Sensor Networks DMSN in conjuction with VLDB August 2024 A Demers J Gehrke R Rajaraman N Trigoni and Y Yao Directions in Multi Query Optimization for Sensor Networks In Advances in Pervasive Computing and Networking Ed by Szymanski and B Yener Springer pages 179 197 2024
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In this paper we propose a novel framework for secure informa tion aggregation in large sensor networks In our framework certain nodes in the sensor network called aggregators help aggregating information requested by a query which substantially reduces the communication overhead
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The publications are broken down on topics Sketch based Approximate Query Processing Florin Rusu and Alin Dobra Sketching Sampled Data Streams Proceedings of IEEE ICDE 2024 Shanghai China April 2024 392 [Talk slides pdf ] Florin Rusu and Alin Dobra Sketches for Size of Join Estimation ACM Transactions on Database Systems Vol 33 No 3 September 2024
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In this paper we design and evaluate an energy efficient data retrieval architecture for continuous aggregate queries in wireless sensor networks We show how the modification of precision in one sensor affects the sample reporting frequency of other sensors and how the precisions of a group of sensors may be collectively modified to achieve the target Quality of Information QoI with
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