• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.5189-5208
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• 2015

To address the contradiction between data aggregation and data security in wireless sensor networks, a Recoverable Privacy-preserving Integrity-assured Data Aggregation (RPIDA) scheme is proposed based on privacy homomorphism and aggregate message authentication code. The proposed scheme provides both end-to-end privacy and data integrity for data aggregation in WSNs. In our scheme, the base station can recover each sensing data collected by all sensors even if these data have been aggregated by aggregators, thus can verify the integrity of all sensing data. Besides, with these individual sensing data, base station is able to perform any further operations on them, which means RPIDA is not limited in types of aggregation functions. The security analysis indicates that our proposal is resilient against typical security attacks; besides, it can detect and locate the malicious nodes in a certain range. The performance analysis shows that the proposed scheme has remarkable advantage over other asymmetric schemes in terms of computation and communication overhead. In order to evaluate the performance and the feasibility of our proposal, the prototype implementation is presented based on the TinyOS platform. The experiment results demonstrate that RPIDA is feasible and efficient for resource-constrained sensor nodes.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.428-439
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• 2015

In this study, we present an approach for reducing the information inaccuracy of existing star aggregation based on bypass links when there are multi-constraint QoS parameters in asymmetric networks. In our approach, bypass links with low similarity are selected. Links that are not chosen as bypass links are included in each group depending on the star's link characteristics. Moreover, each link group is aggregated differently according to the similarity of the links that make up the group. The selection of a bypass link by using link similarity reduces the existing time complexity of O($N^3$) to O(N) by virtue of the simplification of the selection process. In addition, the adaptive integration according to the characteristics of the links in each group is designed to reduce the information inaccuracy caused by static aggregation. Simulation results show that the proposed method maintains low information distortion; specifically, it is 3.8 times lower than that of the existing method, even when the number of nodes in a network increases.

• Journal of KIISE:Databases
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• v.32 no.4
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• pp.372-382
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• 2005

Aggregation such as computing an average value of data measured in each sensor commonly occurs in many applications of sensor networks. Since sensor networks consist of low-cost nodes with limited battery power, reducing energy consumption must be considered in order to achieve a long network lifetime. Reducing the amount of messages exchanged is the most important for saving energy. Earlier work has demonstrated the effectiveness of in-network data aggregation and data filtering for minimizing the amount of messages in sensor networks. In this paper, we propose an adaptive error adjustment scheme that is simpler, more effective and efficient than previous work. The proposed scheme is based on self-adjustment in each sensor node. We show through various experiments that our scheme reduces the network traffic significantly, and performs better than existing methods.

• Journal of KIISE:Software and Applications
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• v.29 no.5
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• pp.289-294
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• 2002

It is known that restructuring feed-forward neural network affects generalization capability and efficiency of the network. In this paper, we introduce a new approach to restructure a neural network using abstraction of the hidden knowledge that the network has teamed. This method involves extracting local rules from non-input nodes and aggregation of the rules into global rule base. The extracted local rules are used for pruning unnecessary connections of local nodes and the aggregation eliminates any possible redundancies arid inconsistencies among local rule-based structures. Final network is generated by the global rule-based structure. Complexity of the final network is much reduced, compared to a fully-connected neural network and generalization capability is improved. Empirical results are also shown.

• Convergence Security Journal
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• v.8 no.2
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• pp.95-102
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• 2008

In this paper, we proposed topology aggregation method that efficiently aggregating topology information in simple node topology. And, it improved QoS of networks by improving call success rate and call access time. Proposed method can improving performance of network by decreasing aggregation information and aggregating multi-links information between boundary nodes using the line segment scheme within bandwidth and delay parameter. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme in respect to call success rate, access time.

• Journal of Multimedia Information System
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• v.3 no.2
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• pp.21-26
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• 2016

Our networked world has been growing exponentially fast. The explosion in volume of machine-to-machine (M2M) transactions threatens to exceed the transport capacity of the networks that link them. Therefore, it is quite essential to reconsider the tradeoff between using many data sets versus using good data sets. We focus on this tradeoff in the context of the quality of information aggregated from many sensors in a noisy environment. We start with a basic theoretical model considered in the famous "CEO problem'' in the field of information theory. From a point of view of large deviations, we successfully find a simple statement for the optimal strategies under the limited network capacity condition. Moreover, we propose an open problem for a sensor network scenario and report a numerical result.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.10-17
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• 2010

Sensor nodes used in Geosensor network are resource limited and power constrained. So it is necessary to research on routing protocols to gather data by using energy efficiently. Wireless sensor networks collect data gathered from sensor nodes by transfering it to the sink using multihop. However, it has two problems. First, the existing works require unnecessary data transmission for choosing a proper parent node to transfer data. Secondly, they have a large number of data transmission because each sensor node has a different path. To solves the problems, we, in this paper, propose a designated path based data aggregation scheme for efficient energy management in WSNs. The proposed scheme can reduce unnecessary data transmission by pre-determining a set of paths and can enable all the sensor nodes to participate in gathering data by running them in round-robin fashion. We show from performance analysis that the proposed scheme is more energy efficient than the existing directed diffusion(DD) and the hierarchical data aggregation(HDA).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.653-669
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• 2024

Dynamic scene deblurring is a complex computer vision problem owing to its difficulty to model mathematically. In this paper, we present a novel approach for image deblurring with the help of the sharp reference image, which utilizes the reference image for high-quality and high-frequency detail results. To better utilize the clear reference image, we develop an encoder-decoder network and two novel modules are designed to guide the network for better image restoration. The proposed Reference Extraction and Aggregation Module can effectively establish the correspondence between blurry image and reference image and explore the most relevant features for better blur removal and the proposed Spatial Feature Fusion Module enables the encoder to perceive blur information at different spatial scales. In the final, the multi-scale feature maps from the encoder and cascaded Reference Extraction and Aggregation Modules are integrated into the decoder for a global fusion and representation. Extensive quantitative and qualitative experimental results from the different benchmarks show the effectiveness of our proposed method.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.933-937
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• 2009

This paper proposes a dynamic timeout scheduling for energy efficient and accurate aggregation by analyzing the single hop delay in wireless sensor networks based on IEEE 802.15.4. The proposed scheme dynamically configures the timeout value depending on both the number of nodes sharing a channel and the type of wireless media, with considering the results of delay analysis of the single hop delay. The timeout of proposed scheme is much smaller than the maximum single hop delay which is used as the timeout of traditional data aggregation schemes. Therefore the proposed scheme considerably reduces the energy consumption of idle monitoring for waiting messages. Also, the proposed scheme maintains the data accuracy by guaranteeing the reception ratio required by the sensor network applications. Extensive simulation has revealed that proposed scheme enhances energy consumption by 30% with maintaining data accuracy, as compared with the TAG data aggregation.