• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2769-2792
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• 2013

In this paper, we propose an authenticated key agreement scheme, TinyIBAK, based on the identity-based cryptography and bilinear paring, for large scale sensor networks. We prove the security of our proposal in the random oracle model. According to the formal security validation using AVISPA, the proposed scheme is strongly secure against the passive and active attacks, such as replay, man-in-the middle and node compromise attacks, etc. We implemented our proposal for TinyOS-2.1, analyzed the memory occupation, and evaluated the time and energy performance on the MICAz motes using the Avrora toolkits. Moreover, we deployed our proposal within the TOSSIM simulation framework, and investigated the effect of node density on the performance of our scheme. Experimental results indicate that our proposal consumes an acceptable amount of resources, and is feasible for infrequent key distribution and rekeying in large scale sensor networks. Compared with other ID-based key agreement approaches, TinyIBAK is much more efficient or comparable in performance but provides rekeying. Compared with the traditional key pre-distribution schemes, TinyIBAK achieves significant improvements in terms of security strength, key connectivity, scalability, communication and storage overhead, and enables efficient secure rekeying.

• Structural Engineering and Mechanics
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• v.38 no.2
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• pp.141-156
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• 2011

A cable stayed bridge under construction has low structural damping and is not as stable as the completed bridge. Control countermeasures, such as the installation of energy dissipating devices, are thus required. In this study, the general procedure and key issues on adopting an active control device, the active mass damper (AMD), for vibration control of cable stayed bridges under construction were studied. Taking a typical cable stayed bridge as the prototype structure; a lab-scale test structure was designed and fabricated firstly. A baseline FEM model was then setup and updated according to the modal parameters measured from vibration test on the structure. A numerical study to simulate the bridge-AMD control system was conducted and an efficient LQG-based controller was designed. Based on that, an experimental implementation of AMD control of the transverse vibration of the bridge model was performed. The results from numerical simulation and experimental study verified that the AMD-based active control was feasible and efficient for reducing dynamic responses of a complex structural system. Moreover, the discussion made in this study clarified some critical problems which should be addressed for the practical implementation of AMD control on real cable-stayed bridges.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4781-4803
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• 2017

Environmental monitoring systems using Wireless Sensor Networks (WSNs) face the challenge of high power consumption, due to the high levels of multi-hop data communication involved. In order to overcome the issue of fast energy depletion, a proof-of-concept implementation proves that adopting a clustering algorithm in environmental monitoring applications will significantly reduce the total power consumption for environment sensor nodes. In this paper, an energy-efficient WSN-based environmental monitoring system is proposed and implemented, using eight sensor nodes deployed over an area of $1km^2$, which took place in the city of Tabuk in Saudi Arabia. The effectiveness of the proposed environmental monitoring system has been demonstrated through adopting a number of real experimental studies.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.692-694
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• 1996

Recently, rapid increase in electricity demand, tremendous financial need for new power plant construction, and environmental problem have led to search for more efficient energy production and energy conservation technologies. Due to the potential energy and cost savings to electric utilities, DSM plays an important role in the electric resource planning. However, implementation of cost-effective DSM program requires appropriate analysis methodologies and procedures. In this study, we present the cost-effectiveness analysis model for DSM program evaluation. We also present a case study to analyze DSM program.

• ETRI Journal
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• v.38 no.4
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• pp.735-745
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• 2016

The Paris agreement at the 21st Conference of the Parties (COP21) emphasizes the reduction of greenhouse gas emissions and increase in energy consumption in all areas. Thus, an important aspect is energy saving in buildings where the lighting is a major component of the electrical energy consumption. This paper proposes a building energy management system employing visible light communication (VLC) based on LED lighting. The proposed management system has key characteristics including personalization and localization by utilizing such VLC advantages as secure communication through light and location-information transmission. Considering the efficient implementation of an energy-consumption adjustment using LED luminaires, this paper adopts variable pulse position modulation (VPPM) as a VLC modulation scheme with simple controllability of the dimming level that is capable of providing a full dimming range. This paper analyzes the VPPM performances according to variable dimming for several schemes, and proposes a VPPM demodulation architecture based on dimming-factor acquisition, which can obtain an improved performance compared to a 2PPM-based scheme. In addition, the effect of a dimming-factor acquisition error is analyzed, and a frame format for minimizing this error effect is proposed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.9-13
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• 2014

The performance of large scale software applications has been automatically increasing for last few decades under the influence of Moore's law - the number of transistors on a microprocessor roughly doubled every eighteen months. However, on-chip transistors limitations and heating issues led to the emergence of multicore processors. The energy efficient ARM based System-on-Chip (SoC) processors are being considered for future high performance computing systems. In this paper, we present a case study of two widely used parallel programming models i.e. MPI and MapReduce on distributed memory cluster of ARM SoC development boards. The case study application, Black-Scholes option pricing equation, was parallelized and evaluated in terms of power consumption and throughput. The results show that the Hadoop implementation has low instantaneous power consumption that of MPI, but MPI outperforms Hadoop implementation by a factor of 1.46 in terms of total power consumption to execution time ratio.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.160-164
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• 2017

Public key cryptography (PKC) is the basic building block for the cryptography applications such as encryption, key distribution, and digital signature scheme. Among many PKC, elliptic curve cryptography (ECC) is the most widely used in IT systems. Recently, very efficient Montgomery-Twisted-Edward (MoTE)-ECC was suggested, which supports low complexity for the finite field arithmetic, group operation, and scalar multiplication. However, we cannot directly adopt the MoTE-ECC to new PKC systems since the cryptography is not fully evaluated in terms of performance on the Internet of Things (IoT) platforms, which only supports very limited computation power, energy, and storage. In this paper, we fully evaluate the MoTE-ECC implementations on the representative IoT devices (16-bit MSP processors). The implementation is highly optimized for the target platform and compared in three different factors (ROM, RAM, and execution time). The work provides good reference results for a gradual transition from legacy ECC to MoTE-ECC on emerging IoT platforms.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• The KIPS Transactions:PartC
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• v.17C no.6
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• pp.459-464
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• 2010

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we implement and evaluate a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC), in wireless sensor networks. The TPC is implemented on sensor Mote hardwares. With the help of TPC implemented, sensors selectively use direct links for control and forwarding time critical sensed data and relay links for data forwarding based on the user delay constraints given. Implementation study shows that TPC helps the sensors to increase a significant amount of energy while collecting sensed data from sensors in a real environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.597-611
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• 2009

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.