Topic
Data aggregator
About: Data aggregator is a research topic. Over the lifetime, 2615 publications have been published within this topic receiving 40265 citations.
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15 May 2006TL;DR: A context adaptive clustering mechanism is proposed, which tries to form clusters of sensors with similar output data within the bound of a given tolerance parameter, which can reduce energy consumption and prolong the sensor lifetime.
Abstract: Wireless sensor networks are characterized by the widely distributed sensor nodes which transmit sensed data to the base station cooperatively. However, due to the spatial correlation between sensor observations, it is not necessary for every node to transmit its data. There are already some papers on how to do clustering and data aggregation in-network, however, no one considers about the data distribution with respect to the environment. In this paper a context adaptive clustering mechanism is proposed, which tries to form clusters of sensors with similar output data within the bound of a given tolerance parameter. With similar data inside a cluster, it is possible for the cluster header to use a simple technique for data aggregation without introducing large errors, thus can reduce energy consumption and prolong the sensor lifetime. The algorithm proposed is very simple, transparent, localized and does not need any central authority to monitor or supervise it.
14 citations
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TL;DR: The security issues in data aggregation for the WSN will be discussed, and the |state-of-the-art| in secure data aggregation schemes will be surveyed and then classified into two categories based on the number of aggregator nodes and the existence of the verification phase.
Abstract: Recent advances in wireless sensor networks (WSNs) have led to several new promising applications including habitat monitoring and target tracking. However, data communication between nodes consumes a large portion of the entire energy consumption of the WSNs. Consequently, data aggregation techniques can significantly help to reduce the energy consumption by eliminating redundant data travelling back to the base station. The security issues such as data integrity, confidentiality, and freshness in data aggregation become crucial when the WSN is deployed in a remote or hostile environment where sensors are prone to node failures and compromises. There is currently research potential in securing data aggregation in WSNs. With this in mind, the security issues in data aggregation for the WSN will be discussed in this article. After that, the |state-of-the-art| in secure data aggregation schemes will be surveyed and then classified into two categories based on the number of aggregator nodes and the existence of the verification phase.
14 citations
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01 Jan 2021TL;DR: The purpose of the proposed model is to exempt the sensor nodes (SN) from sending huge volumes of data for a specific duration during which the BS will predict the future data values and thus minimize the energy utilization of WSN.
Abstract: Environmental monitoring is among the most significant applications of wireless sensor networks (WSNs), which results in sensing, communicating, aggregating and transmitting large volumes of data over a very short period. Thus, a lot of energy is consumed in transmitting this redundant and correlated data to the basestation (BS) making it enormously challenging to achieve an acceptable network lifetime, which has become a bottleneck in scaling such applications. In order to proficiently deal with the energy utilization in successive data aggregation cycles, we propose a data prediction-based aggregation model, which will reduce data transmission by establishing relationship between sensor readings. The purpose of the proposed model is to exempt the sensor nodes (SN) from sending huge volumes of data for a specific duration during which the BS will predict the future data values and thus minimize the energy utilization of WSN. The study suggested an extended linear regression model, which determines resemblance in shape of data curve of contiguous data periods. We have used real sensor dataset of 54 SN that was deployed in the Intel Berkeley Research laboratory. We tested and compared our work with the recent prediction-based data reduction method. Results reveal that the proposed ELR model works better when compared with the other techniques in many assessment indicators.
14 citations
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01 Jan 2011TL;DR: The main idea is to define a multi-metrics protocol that takes into account the residual energy within sensor nodes, data aggregation and data accuracy, and the trade-off between data quality and energy consumption to increase the lifetime of WSN.
Abstract: This paper presents wireless sensor network (WSN) for environmental monitoring with optimized lifetime. The node is equipped with multimode sensors for sensing different environmental parameters. An efficient utilization of power is essential in order to use networks for long duration, hence it is needed to reduce data traffic inside sensor networks, reduce amount of data that need to send to sink. This paper aims at studying different strategies to maximize the WSN lifetime, including routing, data aggregation, data accuracy and energy consumption. The main idea is to define a multi-metrics protocol that takes into account the residual energy within sensor nodes, data aggregation and data accuracy.This paper considers three optimization metrics. First of all, it considers the construction of routing tree with energy and distance parameters.The objective is to maximize the number of data gathering queues answered until the first node m the network fails. Secondly, data aggregation is done by gathering data in an energy efficient manner The aim of the proposed work is to compare the performance in terms of energy efficiency in comparison with and without data aggregation in WSN. Thirdly, the trade-off between data quality and energy consumption to increase the lifetime of WSN is considered.
14 citations
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28 Aug 2011TL;DR: A novel structure-free Real-time Data Aggregation protocol, RDAG, is designed using a Real- time Data-aware Routing policy and a Judiciously Waiting policy for spatial and temporal convergence of packets to make aggregation more efficient.
Abstract: Data aggregation is an effective technique which is introduced to save energy by reducing packet transmissions in WSNs. However, it extends the delay at the intermediate nodes, so it can complicate the handling of delay-constrained data in event-critical applications. Besides, the structure-based aggregation as the dominant data gathering approach in WSNs suffers from high maintenance overhead in dynamic scenarios for event-based applications. In this paper, to make aggregation more efficient, we design a novel structure-free Real-time Data Aggregation protocol, RDAG, using a Real-time Data-aware Routing policy and a Judiciously Waiting policy for spatial and temporal convergence of packets. Extensive simulations in NS-2 verify the superiority of RDAG in WSNs.
14 citations