• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4269-4292
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• 2014

Currently, increasing numbers of access points (AP) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity, but most of these access points are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to power conservation, applying energy efficient strategies in WIFI networks is strongly advocated. One feasible method is dynamically managing network resources, particularly APs, by powering devices on or off. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it; therefore, the network performance would be greatly impacted. In this paper, based on a global view of an entire WLAN, we propose an AP selection technology, known as Temporary Access Selection (TAS). The criterion of TAS is a fusion metric consisting of two evaluation indexes which are based on throughput and battery life, respectively. TAS is both service and clients' preference specific through balancing the data rate, battery life and packet size. TAS also works well independently in traditional WLANs in which no energy efficient strategy is deployed. Moreover, this paper demonstrates the feasibility and performance of TAS through experiments and simulations with Network Simulator version 3 (NS3).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.836-858
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• 2010

Web Services allow a user to integrate applications from different platforms and languages. Since mobile applications often run on heterogeneous platforms and conditions, Web Service becomes a popular solution for integrating with server applications. However, because of its verbosity, XML based SOAP messaging gives the possible overhead to the less powerful mobile devices. Based on the mobile client's behavior that it usually exchanges messages with Web Service continuously in a session, we design the Handheld Flexible Representation architecture. Our proposed architecture consists of three main components: optimizing message representation by using a data format language (Simple_DFDL), streaming communication channel to reduce latency and the Context-store to store context information of a session as well as redundant parts of the messages. In this paper, we focus on the Context-store and describe the architecture with the Context-store for improving the performance of mobile Web Service messaging. We verify our approach by conducting various evaluations and investigate the performance and scalability of the proposed architecture. The empirical results show that we save 40% of transit time between a client and a service by reducing the message size. In contrast to solutions for a single problem such as the compression or binarization, our architecture addresses the problem at a system level. Thus, by using the Context-store, we expect reliable recovery from the fault condition and enhancing interoperability as well as improving the messaging performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4658-4679
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• 2017

Android is now the most popular smartphone platform and remains rapid growth. There are huge number of sensitive privacy information stored in Android devices. Kinds of methods have been proposed to detect Android malicious applications and protect the privacy information. In this work, we focus on extracting the fine-grained features to maximize the information of Android malware detection, and selecting the least joint features to minimize the number of features. Firstly, permissions and APIs, not only from Android permissions and SDK APIs but also from the developer-defined permissions and third-party library APIs, are extracted as features from the decompiled source codes. Secondly, feature selection methods, including information gain (IG), regularization and particle swarm optimization (PSO) algorithms, are used to analyze and utilize the correlation between the features to eliminate the redundant data, reduce the feature dimension and mine the useful joint features. Furthermore, regularization and PSO are integrated to create a new joint feature mining method. Experiment results show that the joint feature mining method can utilize the advantages of regularization and PSO, and ensure good performance and efficiency for Android malware detection.

• Journal of Communications and Networks
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• v.17 no.5
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• pp.506-516
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• 2015

Wireless sensor networks (WSNs) are generally comprised of densely deployed sensor nodes, which results in highly redundant sensor data transmissions and energy waste. Since the sensor nodes depend on batteries for energy, previous studies have focused on designing energy-efficient medium access control (MAC) protocols to extend the network lifetime. However, the energy-efficient protocols induce an extra end-to-end delay, and therefore recent increase in focus on WSNs has led to timely and reliable communication protocols for mission-critical applications. In this paper, we propose an energy efficient and delay guaranteeing node scheduling scheme inspired by biological systems, which have gained considerable attention as a computing and problem solving technique.With the identification of analogies between cellular signaling systems and WSN systems, we formulate a new mathematical model that considers the networking challenges of WSNs. The proposed bio-inspired algorithm determines the state of the sensor node, as required by each application and as determined by the local environmental conditions and the states of the adjacent nodes. A control analysis shows that the proposed bio-inspired scheme guarantees the system stability by controlling the parameters of each node. Simulation results also indicate that the proposed scheme provides significant energy savings, as well as reliable delay guarantees by controlling the states of the sensor nodes.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.1
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• pp.29-34
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• 2018

The systems associated with the ESS never stop. It runs 24 hours everyday. The system must be managed to run. The ESS system should perform normally even if the power IT equipment fails or communication failure occurs. Therefore, there is a need for a system that actively addresses, manages and controls the high precision power data of the ESS, even if a variety of failures occur. I would like to propose a power management communication unit to cope with the occurrence of communication failure. This paper also includes an integrated management system that can perform micro grid site management, maintenance and monitoring for the ESS system connected with the solar power generation facility.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.119-131
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• 2011

In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. DDWT main property is a more computationally efficient approach to shift invariance. Also, the DDWT gives much better directional selectivity when filtering multidimensional signals. The dual-tree DWT of a signal is implemented using two critically-sampled DWTs in parallel on the same data. The transform is 2-times expansive because for an N-point signal it gives 2N DWT coefficients. If the filters are designed is a specific way, then the sub-band signals of the upper DWT can be interpreted as the real part of a complex wavelet transform, and sub-band signals of the lower DWT can be interpreted as the imaginary part. The quincunx lattice is a sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Quincunx lattice yields a non separable 2D-wavelet transform, which is also symmetric in both horizontal and vertical direction. And non-separable wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, non-separable image processing using DDWT services good performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.205-210
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• 2017

Wireless sensor networks are useful to various unmanned monitoring application such as monitoring environments, surveillance system, unmanned space exploration, and so on. Due to the inappropriate placement of sensor nodes, there are some problems, for example, low connectivity and high overlapped sensing area. These problems can make it difficult for the data collection and lead to a waste of energy. In this paper, we propose a node relocating method to resolve the inappropriate placement of sensor nodes. Given monitoring area, we place sensor nodes randomly and find redundant nodes and move them to uncovered area. Through the simulation, We show that the proposed method is viable and efficient compared with the existing randomly locating method.

• Bulletin of the Korean Chemical Society
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• v.30 no.2
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• pp.323-326
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• 2009

SR proteins are essential splicing regulators and also modulate alternative splicing events, which function both as redundant and substrate-specific manner. The Drosophila B52/SRp55, a member of the SR protein family, is essential for the fly development in vivo, as deletion of B52 gene results in lethality of animals at the second instar larval stage. Identification of the splicing target genes of B52 thus should be crucial for the understanding of the specific developmental role of B52 in vivo. In this study, we performed whole-genome DNA microarray experiments with a B52- knock-out animal. Analysis of the microarray data not only provided the B52-dependent gene expression signature, but also revealed a larval-stage specific, alternative splicing target gene of B52. Our result thus provides a starting point to understand the essential function of B52 at the organismal level.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.94-99
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• 2008

In the pattern classification problem, feature selection is an important technique to improve performance of the classifiers. Particularly, in the case of classifying with a large number of features or variables, the accuracy of the classifier can be improved by using the relevant feature subset to remove the irrelevant, redundant, or noisy data. In this paper we propose a feature selection method using genetic algorithm and information theory. Experimental results show that this method can achieve better performance for pattern recognition problems than conventional ones.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.310-315
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a u!;or preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or non-spam in a meaningful way. We also suggest a nor rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.