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Data aggregator

About: Data aggregator is a research topic. Over the lifetime, 2615 publications have been published within this topic receiving 40265 citations.


Papers
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Journal ArticleDOI
TL;DR: This paper identifies the threats regarding user and data privacy in AMI applications and comprehensively surveys the existing solutions to address these threats and investigates and compares the performance of homomorphic encryption in terms of data size and end-to-end delay with that of hop-by-hop secure data aggregation and data concatenation within a network of SMs via extensive simulations.
Abstract: Advanced metering infrastructure AMI enables real-time collection of power consumption data through the Smart Grid communication network. With the current deployment of smart meters SMs, one of the concerns that started to be raised by the customers is on the privacy of their power consumption data. The exposure of these data can lead to several privacy problems that need to be addressed before the customers can be convinced for the use of SMs. This paper has two contributions. First, it identifies the threats regarding user and data privacy in AMI applications and comprehensively surveys the existing solutions to address these threats. We categorize the existing approaches on privacy and discuss pros and cons of these approaches with respect to some criteria. Second, we pick one of the existing solutions on privacy, namely the homomorphic encryption, and evaluate its feasibility and impact on performance when used in data aggregation for real-time AMI applications. We investigate and compare the performance of homomorphic encryption in terms of data size and end-to-end delay with that of hop-by-hop secure data aggregation and data concatenation within a network of SMs via extensive simulations. We finally conclude the paper with some future privacy issues that are subject to further research. Copyright © 2013 John Wiley & Sons, Ltd.

52 citations

Journal ArticleDOI
TL;DR: New security mechanisms for semantic data aggregation that are suitable for use in vehicular ad hoc networks are presented and Resilience against both malicious users of the system and wrong information due to faulty sensors are taken into consideration.
Abstract: Innovative ways to use ad hoc networking between vehicles are an active research topic and numerous proposals have been made for applications that make use of it. Due to the bandwidth-limited wireless communication medium, scalability is one crucial factor for the success of these future protocols. Data aggregation is one solution to accomplish such scalability. The goal of aggregation is to semantically combine information and only disseminate this combined information in larger regions. However, the integrity of aggregated information cannot be easily verified anymore. Thus, attacks are possible resulting in lower user acceptance of applications using aggregation or, even worse, in accidents due to false information crafted by a malicious user. Therefore, it is necessary to design novel mechanisms to protect aggregation techniques. However, high vehicle mobility, as well as tight bandwidth constraints, pose strong requirements on the efficiency of such mechanisms. We present new security mechanisms for semantic data aggregation that are suitable for use in vehicular ad hoc networks. Resilience against both malicious users of the system and wrong information due to faulty sensors are taken into consideration. The presented mechanisms are evaluated with respect to their bandwidth overhead and their effectiveness against possible attacks.

51 citations

Journal ArticleDOI
02 Oct 2012
TL;DR: A novel optimisation algorithm called intelligent water drops (IWDs) is adopted to construct the optimal data aggregation trees for the WSNs and shows that the IWD algorithm is able to obtain a better data aggregation tree with a smaller number of edges representing direct communication between two nodes when compared with the well-known optimisation method such as ant colony optimisation.
Abstract: Energy conservation is an important aspect in wireless sensor networks (WSNs) to extend the network lifetime. In order to obtain energy-efficient data transmission within the network, sensor nodes can be organised into an optimal data aggregation tree with optimally selected aggregation nodes to transfer data. Various nature-inspired optimisation methods have been shown to outperform conventional methods when solving this problem in a distributed manner, that is, each sensor node makes its own decision on routing the data. In this study, a novel optimisation algorithm called intelligent water drops (IWDs) is adopted to construct the optimal data aggregation trees for the WSNs. Further enhancement of the basic IWD algorithm is proposed to improve the construction of the tree by attempting to increase the probability of selecting optimum aggregation nodes. The computational experiment results show that the IWD algorithm is able to obtain a better data aggregation tree with a smaller number of edges representing direct communication between two nodes when compared with the well-known optimisation method such as ant colony optimisation. In addition, the proposed improved version of the IWD algorithm provides better performance in comparison with the basic IWD algorithm for saving the energy of WSNs.

51 citations

Proceedings ArticleDOI
03 Jan 2005
TL;DR: This paper analyzes the conditions for effective aggregation of data traffic that is subject to end-to-end delay constraints and presents an algorithm for achieving maximal possible energy saving through data aggregation while meeting the desired level of timeliness.
Abstract: Recent years have witnessed a growing interest in the application of wireless sensor networks in unattended environments. Nodes in such applications are equipped with limited energy supply and need careful management in order to extend their lifetime. In order to conserve energy, many of the routing protocols proposed for wireless sensor networks reduce the number of transmitted packets by pursuing in-network data aggregation. Almost all of the aggregation schemes presented in the literature strive to save sensor’s energy while considering unconstrained data traffic. However, aggregation extends the queuing delay at the relay nodes and can thus complicate the handling of latency-constrained data. In this paper, we analyze the conditions for effective aggregation of data traffic that is subject to end-to-end delay constraints. We present an algorithm for achieving maximal possible energy saving through data aggregation while meeting the desired level of timeliness. A Weighted Fair Queuing based mechanism for packet scheduling is employed at each node in order to perform service differentiation and ensure bounded delay for constrained traffic. The performance of the proposed approach is qualified via simulation. The simulation results have demonstrated that the proposed approach provides a balance between energy consumption and timeliness level.

51 citations

Journal ArticleDOI
TL;DR: The scenario of distributed data aggregation in wireless sensor networks is considered, where sensors can obtain and estimate the information of the whole sensing field through local data exchange and aggregation and a sequential decision process model is proposed.
Abstract: The scenario of distributed data aggregation in wireless sensor networks is considered, where sensors can obtain and estimate the information of the whole sensing field through local data exchange and aggregation. An intrinsic tradeoff between energy and aggregation delay is identified, where nodes must decide optimal instants for forwarding samples. The samples could be from a node's own sensor readings or an aggregation with samples forwarded from neighboring nodes. By considering the randomness of the sample arrival instants and the uncertainty of the availability of the multiaccess communication channel, a sequential decision process model is proposed to analyze this problem and determine optimal decision policies with local information. It is shown that, once the statistics of the sample arrival and the availability of the channel satisfy certain conditions, there exist optimal control-limit-type policies that are easy to implement in practice. In the case that the required conditions are not satisfied, the performance loss of using the proposed control-limit-type policies is characterized. In general cases, a finite-state approximation is proposed and two on-line algorithms are provided to solve it. Practical distributed data aggregation simulations demonstrate the effectiveness of the developed policies, which also achieve a desired energy-delay tradeoff.

51 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023104
2022277
2021189
2020207
2019179
2018188