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    200871&ensp·&ensp The Research of High Efficient and Real Time Data Aggregation Method Applied in WSNs DOI: 10.12677/JSTA.2015.33005, PP

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  • Research Article A Secure and Efficient Data Aggregation

    2016125&ensp·&enspthe aggregation e ciency by exploiting cryptographic tools such as onion signature [ ]andaggregatesignature[ ]. Note that, in this study, we consider a more general data aggregation scenario: collecting data within a certain area and, at the same time, providing security guarantee for the aggregation functionality. 3. System Model and Design Goal

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  • An Efficient Data Aggregation Scheme for

    201859&ensp·&enspIn this paper, we propose a privacyfriendly and efficient data aggregation scheme (EDAS) for dynamic pricing based billing and demandresponse management in smart

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  • ESPDA_ Energyefficient and Secure Pattern

    2011327&ensp·&enspESPDA: ENERGYEFFICIENT AND SECURE PATTERNBASED DATA AGGREGATION FOR WIRELESS SENSOR NETWORKS H. ?am, S. ?zdemir, P. Nair

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  • Efficient and PrivacyAware Data Aggregation in Mobile

    20141125&ensp·&enspAlthough aggregation statistics computed from timeseries data are very useful, in many scenarios, the data from individual user may be privacysensitive, and users do not trust any single thirdparty aggregator to see their data in cleartext. For instance, to monitor the propagation of a new flu, the

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  • Energy efficient data aggregation techniques in wireless

    2013929&ensp·&enspAbstract: The data in wireless sensor networks is organized in an efficient manner using data aggregation and data dissemination protocols. Due to the energy constraints in sensor nodes, energyefficient data aggregation protocols are used to save

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  • A Review on Energy Efficient Data Aggregation Routing

    2017512&ensp·&enspof data aggregation prior to transforming it into useful information. Designing different network management tools such for routing, localization, and data aggregation are, therefore, required in large scale WSNs. Only a few of the existing data aggregation

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  • Data aggregation techniques in sensor networks: A survey

    20181010&ensp·&enspThe design of efficient data aggregation algorithms is an inherently challenging task. There has been intense research in the recent past on data aggregation in WSNs. In this survey paper, we present an extensive overview of several data aggregation algorithms. We first present the basic

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  • Efficient Data Aggregation in MultihopWireless Sensor

    20091114&ensp·&enspcollection or data aggregation. Different from data collection, data aggregation allows innetwork processing. This means that data can be compressed within the network. This feature introduces a possibility of a new energy or time efficient method to collect data, comparing to data collection. For data aggregation, different objectives will be

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  • Compressed Data Aggregation: EnergyEfficient and High

    20121220&ensp·&enspIn this case, energyefficient data collection requires the use of data aggregation. Whereas many data aggregation schemes have been investigated, they either compromise the fidelity of the recovered data or require complied innetwork compressions.

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  • PERFORMANCEANALYSIS OF AN OPTIMIZED ENERGY

    2010419&ensp·&enspData aggregation in wireless sensor networks is widely accepted as an essential paradigm for energy efficient routing but with low reliability under node and link failures. Also, malicious sensor nodes send false data reports to distort aggregation

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  • Data Aggregation Protocol for Efficient Congestion Control

    PowerEfficient Data Aggregation Protocols which provides better data aggregation. The proposed scheme uses the advantages of the powerful LMST structure and provides simple solutions to the known problems in route setup and maintenance because of its distributed nature.

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  • Energy efficient structurefree data aggregation and

    The data aggregation is one of the techniques to conserve energy by eliminating the redundant data transmission in dense WSNs. In this paper, we propose an energy efficient structurefree data aggregation and delivery (ESDAD) protocol, which aggregates the redundant data in

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  • An Efficient Data Aggregation Method for EventDriven

    2017827&ensp·&enspnode, then the sink node sends data aggregation scheduling for sensor nodes while considering the number of downstream nodes of each sensor node. In [11], the sink node performs data aggregation scheduling, after receiving the report of each event. In this method, the sink node performs data aggregation scheduling for the next event report while

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  • Efficient clusteringbased data aggregation techniques for

    Authors: WooSung Jung: Ajou University, Suwon, South Korea: KeunWoo Lim: Ajou University, Suwon, South Korea: YoungBae Ko: Ajou University, Suwon, South Korea

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  • Isolines: efficient spatiotemporal data aggregation in

    This paper introduces an energyefficient data collection technique that takes advantage of spatial and temporal data correlation for monitoring continuously changing conditions such as temperature, humidity, rain fall, radiation, substance concentrations,

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  • ENERGY EFFICIENT SECURE DATA AGGREGATION IN

    2014122&ensp·&ensphierarchical data aggregation algorithm which uses an efficient public key cryptosystem (elliptic curve cryptography) to achieve end to end security. Unlike many other secure data aggregation algorithms which require separate phases for secure aggregation and integrity verifiion, the secure

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  • Power Efficient Data Gathering and Aggregation in

    2008415&ensp·&ensp(Power Efficient Data gathering and Aggregation Protocol), which are near optimal minimum spanning tree based routing schemes, where one of them is the poweraware version of the other. Our simulation results show that our algorithms perform well both in systems where base station is far away from and where it is in the center of the field.

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  • An Efficient Data Aggregation Approach for Underwater

    2013711&ensp·&ensplifetime. In UWSN data aggregation, the aggregator node aggregates the sensed data from surrounding nodes, process, and transmit the data to the sink or . So, the BS major challenge of data aggregation in UWSNs is to minimize data redundancy while ensure high data accuracy. A approach to compare between two set of promising

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  • Efficient Cluster Head Selection Scheme for Data

    201756&ensp·&enspThe aim of data aggregation is that eliminates redundant data transmission and enhances the life time of energy in wireless sensor network. Data aggregation process has to be done with the help of effective clustering scheme this paper we gives new scheme related to clustering for data aggregation called "Efficient cluster head selection

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  • An EnergyEfficient and Data Aggregation

    In wireless sensor network, monitoring data possesses fairly good similarity of nodes' readings. According to this applying background, we propose Local EnergyEfficient and

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  • Efficient aggregation (and more) using data.table

    20151127&ensp·&enspThis post repeats the same examples using data.table instead, the most efficient implementation of the aggregation logic in R, plus some additional use cases showing the power of the data.table package. This post focuses on the aggregation aspect of the data.table and only touches upon all other uses of this versatile tool.

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  • An Efficient Data Aggregation and Query Optimization for

    2017824&ensp·&enspdata aggregation and Grid based or innetwork based data aggregation. Fig 1.2 represents the classifiion types of data aggregation. Fig 1.2.Types Data aggregation In tree based data aggregation, sensor nodes are classified in the form of tree where aggregated data are executed at intermediate nodes and data are transmitted to the root node.

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  • A PrivacyPreserving Data Aggregation Scheme

    A PrivacyPreserving Data Aggregation Scheme in Wireless Sensor Networks Fu Shuai 1,2, Jiang Qi 2, Ma Jianfeng 2 1 (School of Electronic and Information Engineering

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  • Data Aggregation Scheduling with Guaranteed

    Data Aggregation Scheduling with Guaranteed Lifetime and Efficient Latency in Wireless Sensor Ne,: An Efficient File System for LargeCapacity

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  • Secure and Efficient Hierarchical Data Aggregation in

    2014710&ensp·&enspdata aggregation protocol is an inherently challenging task because the protocol designer must trade off between energy efficiency, data accuracy, faulttolerance, latency, and security. In order to achieve this trade off, data aggregation techniques are tightly coupled with how packets are routed

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  • An EnergyEfficient and Scalable Secure Data Aggregation

    Data aggregation is an essential technique to reduce the communiion overhead and energy consumption. Since many appliions require data privacy, we need to take security into consideration. In this paper, we propose an energyefficient, secure, highly accurate, and scalable scheme for data aggregation (EESSDA).

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  • An Efficient Data Aggregation Approach for Large Scale

    An Efficient Data Aggregation Approach for Large Scale Wireless Sensor Networks Lutful Karim *, Nidal Nasser, Hanady Abdulsalam** and Imad Moukadem*** *Dept. of Computing and Info Science

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  • Energy Efficient Data Aggregation Scheduling in Wireless

    Abstract—Data aggregation is a critical functionality in wireless sensor networks. This paper focuses on enhancing energy and delay efficiency for the data aggregation scheduling problem. In the existing data aggregation scheduling algorithms, a sensor node has to start its radio numerous times to receive all data

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  • Delay Efficient Distributed Data Aggregation Algorithm in

    2013516&ensp·&enspnetwork. In data aggregation algorithms the main important metrics are network lifetime, data accuracy, and latency. The definitions of these measures are highly dependent on the desired appliion. The design of efficient data aggregation algorithms is

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  • CiteSeerX — Efficient data aggregation and transport in

    201011&ensp·&enspAbstract. Abstract—In wireless sensor networks, innetwork aggregation is the process of compressing locally the data gathered by the sensor nodes, so that only the compressed data travel across several hops to their destination.

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  • Energy Efficient Data Aggregation in Wireless Sensor

    2014325&ensp·&enspDesigning energy efficient data aggregation technique in clustering environment for Wireless Sensor Networks (WSNs) is a challenging task when nodes in the network are resource constrained. Data aggregation is necessary

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  • AEESPAN: Automata Based Energy Efficient Spanning Tree

    2009710&ensp·&enspA solution, which is suggested, is aggregation. In aggregation mechanisms, the nodes aggregate received data and send aggregated result instead of raw data to sink, so, the volume of the transmitted data is decreased. Aggregation algorithms should construct aggregation tree and transmit data to sink based on this tree.

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  • Data aggregation for wireless sensor networks: an energy

    Data aggregation can be egorized as functionbased and correlationbased. This thesis aims to develop both functionbased and correlationbased data aggregation algorithms for conventional WSNs powered by nonrechargeable battery to achieve energy efficiency and prolong network lifetime.

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  • — MongoDB Manual 3.4

    201757&ensp·&enspThe pipeline provides efficient data aggregation using native operations within MongoDB, and is the preferred method for data aggregation in MongoDB. The aggregation.

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  • EnergyEfficient Secure Pattern Based Data

    2011629&ensp·&enspEnergyEfficient Secure Pattern Based Data Aggregation for Wireless Sensor Networks_ 00 EnergyEfficient Secure

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  • Data aggregation framework for energyefficient

    Data aggregation is defined as the process of aggregating the data from multiple sensors to eliminate number of transmissions and provide fused information to the base station. Data aggregation usually involves the fusion of data from multiple sensors at intermediate nodes and transmission of the aggregated data to the base station (sink).

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  • Energyefficient clusterbased privacy data

    20181115&ensp·&enspAbstract Current privacypreserving data aggregation methods in wireless sensor networks often have large computational and communiion costs. This paper presents an

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