• ETRI Journal
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• 제39권2호
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• pp.145-150
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• 2017

As wearable devices are powered by batteries, they need to consume as little energy as possible. To address this challenge, in this article, we propose a synergistic technique for energy-efficient approximate speech signal processing (ASSP) for wearable devices. More specifically, to enable the efficient trade-off between energy consumption and sound quality, we synergistically integrate an approximate multiplier and a successive approximate register analog-to-digital converter using our enhanced conversion algorithm. The proposed ASSP technique provides ~40% lower energy consumption with ~5% higher sound quality than a traditional one that optimizes only the bit width of SSP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권1호
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• pp.35-57
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• 2021

Fog computing aims to provide the solution of bandwidth, network latency and energy consumption problems of cloud computing. Likewise, management of data generated by healthcare IoT devices is one of the significant applications of fog computing. Huge amount of data is being generated by healthcare IoT devices and such types of data is required to be managed efficiently, with low latency, without failure, and with minimum energy consumption and low cost. Failures of task or node can cause more latency, maximum energy consumption and high cost. Thus, a failure free, cost efficient, and energy aware management and scheduling scheme for data generated by healthcare IoT devices not only improves the performance of the system but also saves the precious lives of patients because of due to minimum latency and provision of fault tolerance. Therefore, to address all such challenges with regard to data management and fault tolerance, we have presented a Fault Tolerant Data management (FTDM) scheme for healthcare IoT in fog computing. In FTDM, the data generated by healthcare IoT devices is efficiently organized and managed through well-defined components and steps. A two way fault-tolerant mechanism i.e., task-based fault-tolerance and node-based fault-tolerance, is provided in FTDM through which failure of tasks and nodes are managed. The paper considers energy consumption, execution cost, network usage, latency, and execution time as performance evaluation parameters. The simulation results show significantly improvements which are performed using iFogSim. Further, the simulation results show that the proposed FTDM strategy reduces energy consumption 3.97%, execution cost 5.09%, network usage 25.88%, latency 44.15% and execution time 48.89% as compared with existing Greedy Knapsack Scheduling (GKS) strategy. Moreover, it is worthwhile to mention that sometimes the patients are required to be treated remotely due to non-availability of facilities or due to some infectious diseases such as COVID-19. Thus, in such circumstances, the proposed strategy is significantly efficient.

• Journal of the Korea Society of Computer and Information
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• 제22권2호
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• pp.9-19
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• 2017

Useful continuous sensing applications are increasingly emerging as a new class of mobile applications. Meanwhile, open, multi-use sensor devices are newly adopted beyond smartphones, and provide huge opportunities to expand potential application categories. In this upcoming environment, uncoordinated use of sensor devices would cause severe imbalance in power consumption of devices, and thus result in early shutdown of some sensing applications depending on power-hungry devices. In this paper, we propose EnergyCordy, a novel inter-device energy use coordination system; with a system-wide holistic view, it coordinates the energy use of concurrent sensing applications over multiple sensor devices. As its key approach, we propose a relaxed sensor association; it decouples the energy use of an application from specific sensor devices leveraging multiple context inference alternatives, allowing flexible energy coordination at runtime. We demonstrated the effectiveness of EnergyCordy by developing multiple example applications over custom-designed wearable senor devices. We show that EnergyCordy effectively coordinates the power usage of concurrent sensing applications over multiple devices and prevent undesired early shutdown of applications.

• KIEAE Journal
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• 제16권5호
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• pp.47-55
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• 2016

Purpose: As the energy consumed by buildings increases, there is a growing need for studies and technology development to address this issue. One of the solutions to excessive energy use by buildings is the light-shelf, which is a natural lighting system enabling efficient reduction in light energy, and research in this area has been intensive. However, most of the studies about the light-shelf are limited to the light environment, and thus the application of their findings to an actual environment in the form of a design may be problematic. Therefore, the purpose of the present study is to provide fundamental data for light-shelf design by carrying out a light-shelf performance evaluation on the basis of the light environment and the heating and cooling environment. Method: In the present study, a testbed was established to conduct a light-shelf performance evaluation by measuring the electric power consumption of lighting and heating and cooling devices depending on the existence of a light-shelf and its angle. Result: The findings of the present study are as follows: 1) With respect to the uniformity of the indoor light environment amenity, the optimum angle of a light-shelf was found to be $30^{\circ}$ for the summer solstice and the winter solstice. 2) With respect to the reduction of electric power consumption by indoor lighting devices, the optimum light-shelf angle at the summer solstice is $30^{\circ}$, at which time electric power consumption may be reduced by 10.2% in comparison with when no light-shelf is applied. However, at the winter solstice, a light-shelf may increase the energy consumption for lighting in comparison with when no light-shelf is applied, and this should be taken into account in the design of a light-shelf. 3) In terms of reducing the electric power consumption of heating and cooling devices, the optimum angle of a light-shelf was found to be $30^{\circ}$ for the summer solstice, while a light-shelf is inappropriate for the winter solstice since a light-shelf creates shade and thus increases the heating energy consumption. 4) To summarize the findings above, the optimum angle of a light-shelf is $30^{\circ}$ for the summer solstice, but the installation of a light-shelf may in some circumstances increase the energy consumed by lighting devices as well as by heating and cooling devices. Therefore, more studies and technology development may need to be performed to solve the problem of increased energy consumption at the winter solstice.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권9호
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• pp.3151-3168
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• 2021

Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

• IEMEK Journal of Embedded Systems and Applications
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• 제9권6호
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• pp.315-321
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• 2014

Mobile computing devices such as smartphones, tablet computers have become the dominant personal computing platforms. Energy efficiency is a prime design requirement for smart devices. In order to reduce the energy consumption of the smart devices, analysis of performance and energy consumption has become important. However, so far, there is no framework for the analysis and systematic approach to improve the power consumption of the heterogeneous multi-core system. In this paper, we describe a new framework for the analysis of heterogeneous multi-core systems. Also, by use of an analysis tool, can be provide reliability and productivity of development results.

• Journal of Software Engineering Society
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• 제26권3호
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• pp.53-62
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• 2013

Along with increasing supplies of smart devices, a proliferation of context-aware applications is came. However, acquiring contexts through sensors requires considerable energy consumption. It has became big constraints on running many context-aware applications in mobile devices having limited battery capacity. Hence, energy-efficient methods for monitoring contexts are highly required. In this paper, we propose four context monitoring methods, analyse energy consumption in each method, and provide guidelines for applying the methods. It is effective to decrease energy consumption for monitoring contexts with applying the methods. To assess the proposed methods, we implement an application that is aware of a user's motion and show quantitative comparison between each of the methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.6152-6168
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• 2017

Recently, the biometric-based authentication systems such as FIDO (Fast Identity Online) are increased in mobile computing environments. The biometric-based authentication systems are performed on the mobile devices with the battery, the improving energy efficiency is important issue. In the case, the size of images (i.e., face, fingerprint, iris, and etc.) affects both recognition accuracy and energy consumption, and hence the tradeoff analysis between the both recognition accuracy and energy consumption is necessary. In this paper, we propose an energy-efficient way to authenticate based on biometric information with tradeoff analysis between the both recognition accuracy and energy consumption in multimedia IoT (Internet of Things) transmission environments. We select the facial information among biometric information, and especially consider the multicore-based mobile devices. Based on our experimental results, we prove that the proposed approach can enhance the energy efficiency of GABOR+LBP+GRAY VALUE, GABOR+LBP, GABOR, and LBP by factors of 6.8, 3.6, 3.6, and 2.4 over the baseline, respectively, while satisfying user's face recognition accuracy.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.7-15
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• 2024

6G network technology represents the next generation of communications, supporting high-speed connectivity, ultra-low latency, and integration with cutting-edge technologies, such as the Internet of Things (IoT), virtual reality, and autonomous vehicles. These advancements promise to drive transformative changes in digital society. However, as technology progresses, the demand for efficient data transmission and energy management between smart devices and network equipment also intensifies. A significant challenge within 6G networks is the optimization of interactions between satellites and smart devices. This study addresses this issue by introducing a new game theory-based technique aimed at minimizing system-wide energy consumption and latency. The proposed technique reduces the processing load on smart devices and optimizes the offloading decision ratio to effectively utilize the resources of Low-Earth Orbit (LEO) satellites. Simulation results demonstrate that the proposed technique achieves a 30% reduction in energy consumption and a 40% improvement in latency compared to existing methods, thereby significantly enhancing performance.

• KIPS Transactions on Computer and Communication Systems
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• 제3권5호
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• pp.151-154
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• 2014

An energy of applications had consumed through the complexed inter-action with operating systems, run-time environments, compiler, and applications on various mobile devices. In these days, challenged researches are studying to reduce of energy consumptions that uses energy-oriented high-level and low-level compiler techniques on mobile devices. In this paper, we intented to reduce an energy consumption of Java mobile applications that applied a list instruction scheduling for energy dissipation from dalvik bytecode which extracted Android dex files. Through this works, we can construct the optimized power and energy environment on mobile devices with the limited power supply.