• Journal of Information Processing Systems
• /
• v.18 no.3
• /
• pp.389-401
• /
• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.355-357
• /
• 2020

최근 에너지 효율의 중요성이 높아지고 에너지 공급 형태가 다변화하면서 다양한 에너지원을 효율적으로 관리할 수 있는 마이크로그리드 개념이 중요해지고 있다. 본 연구의 산업단지 마이크로그리드 열거래 플랫폼은 실증사이트의 전기 및 열에너지 모니터링 기능과 열에너지 거래 정산 기능을 가지며, 이를 위해 정확하고 안정적인 실증사이트 데이터가 필요하다. 하지만 실증사이트 데이터는 에너지 단위의 불일치, 센서 및 현장 운영상태에 따른 불안정성 등의 문제가 있어 수집 직후 열거래 플랫폼에서 활용할 수 없다. 따라서 수집된 데이터를 활용하기 위해 엔진 최대 출력량, 최대 전력 사용량 등의 변수별 특성을 고려하여 데이터 전처리 프로세스를 설계 및 적용하였다.

• Journal of Information Processing Systems
• /
• v.19 no.4
• /
• pp.450-464
• /
• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.7
• /
• pp.2377-2398
• /
• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Proceedings of the Korean Radioactive Waste Society Conference
• /
• 2005.06a
• /
• pp.311-318
• /
• 2005

Transparency on the Total System Performance Assessment (TSPA) is the key issue to enhance the public acceptance for a permanent high level radioactive repository. To approve it, all performances on TSPA through Quality Assurance is necessary. The integrated Cyber R&D Platform is developed by KAERI using the T2R3 principles applicable for five major steps in R&D's. The proposed system is implemented in the web-based system so that all participants in TSPA are able to access the system. It is composed of FEAS (FEp to Assessment through Scenario development) showing systematic approach from the FEPs to Assessment methods flow chart, PAID (Performance Assessment Input Databases) showing PA(Performance Assessment) input data set in web based system and QA system receding those data. All information is integrated into Cyber R&D Platform so that every data in the system can be checked whenever necessary. For more user-friendly system, system upgrade included input data & documentation package is under development. Throughout the next phase R&D, Cyber R&D Platform will be connected with the assessment tool for TSPA so that it will be expected to search the whole information in one unified system.

• Journal of Advanced Navigation Technology
• /
• v.19 no.1
• /
• pp.66-73
• /
• 2015

In this paper, an architecture of a perpetual smart video device and its energy control model for the internet of things (IoT) are proposed. The smart video device consists of a processor, an image sensor, a video codec, and a network controller. In the proposed energy control model, energy consumed by image sensing, video encoding, and transmission and energy harvested by solar panels are defined as an input and an output of a battery, an energy buffer. Frame rate, quantization parameter, and operating frequency of processor are defined as the energy control parameters, and these parameters control the input and the output energy of the energy buffer, finally control the energy left in the battery. The proposed energy control model is validated by the energy consumption measurement of the smart phone based platform for various combinations of energy control parameters, and can be used for the design of perpetual smart video device.

• Transactions of the Korean hydrogen and new energy society
• /
• v.31 no.4
• /
• pp.337-344
• /
• 2020

Worldwide, there is a significant surge in the efforts for addressing the issue of global warming; the use of renewable energy is one of the solutions proposed to mitigate global warming. However, severe volatility is a critical disadvantage, and thus, power-to-gas technology is considered one of best solutions for energy storage. Hydrogen is a popular candidate from the perspective of both environment and economics. Accordingly, a hydrogen production system based on renewable energy sources is developed, and the economics of the system are assessed. The result of the base case shows that the unit cost of hydrogen production would be 6,415 won/kg H₂, with a hydrogen production plant based on a 100 MW akaline electrolyzer and 25% operation rate, considering renewable energy sources with no electricity cost payment. Sensitivity study results show that the range of hydrogen unit cost efficiency can be 2,293 to 6,984 Won/kg H₂, depending on the efficiency and unit cost of the electrolyzer. In case of electrolyzer operation rate and electricity unit cost, sensitivity study results show that hydrogen unit cost is in the range 934-26,180 won/kg H₂.

• 한국신재생에너지학회:학술대회논문집
• /
• 2010.11a
• /
• pp.170-170
• /
• 2010

The energy conversion from the temperature difference between hot and cold source like ocean thermal energy conversion (OTEC), requires a long and large-diameter pipe (about 1000 to 10,000 meters long) to reach the deep water. The pipe diameter ranges from 2.8 meter for proposed early test systems, to 5 meter for large, commercial power generation systems. The pipe must be designed to resist collapsing pressures produced by water temperature and density differences, and the reduced pressure required to induce flow up the pipe. Other design considerations include the external-drag effect on the pipe due to ocean currents, and the wave-induced motions of the platform to which the pipe is attached. Various approaches to the pipe construction have been proposed, including aluminum, steel, concrete, and fiberglass. More recently, a flexible pipe construction involving the use of fiberglass reinforced plastic has been proposed. This report presents the results of a scaled fixed cold water pipe (CWP) model test program performed by EES(Engineering Equation Solver) to demonstrate the feasibility of this pipe approach.

• Journal of the Korea Society of Computer and Information
• /
• v.16 no.6
• /
• pp.11-20
• /
• 2011

In this paper, we propose an optimal scheduling scheme that minimizes the energy consumption of a real-time video task on the multi-core platform supporting dynamic voltage and frequency scaling. Exploiting parallel execution on multiple cores for less energy consumption, the propose scheme allocates an appropriate number of cores to the task execution, turns off the power of unused cores, and assigns the lowest clock frequency meeting the deadline. Our experiments show that the proposed scheme saves a significant amount of energy, up to 67% and 89% of energy consumed by two previous methods that execute the task on a single core and on all cores respectively.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.04a
• /
• pp.580-581
• /
• 2016

국제적으로 지속적인 이슈가 되고 있는 에너지 절감에 대한 대책으로 다양한 에너지 절감 기술들이 연구 개발되고 있다. 특히 전체 에너지 사용량의 약 20%이상을 차지하는 건물(가정/상업/공공)부문에서는 에너지 진단 및 분석을 수행하기 위해 건물 에너지 관리 시스템(BEMS: Building Energy Management System)과 건물 자동화 시스템(BAS: Building Automation System) 그리고 다양한 환경정보들을 수집하여 활용한다. 하지만 기존 분석 방식은 결과의 신뢰성에 최소한의 영향을 주면서 데이터 관리 효율을 높이는 방법에 초점을 맞춰 연구가 진행되었으며, 이를 위해 기존에 수집된 데이터를 압축하거나 샘플링하는 사전 정제 과정을 거치게 되었다. 하지만 빅데이터 플랫폼을 활용하면 더 이상 신뢰성을 낮추면서까지 데이터를 정제할 필요가 없어지고, 수집되는 모든 데이터에 대한 다차원 분석을 빠르게 수행할 수 있게 된다. 따라서 본 논문에서는 하드웨어의 한계로 기존 건물에너지 진단 및 분석 시스템에서 제공하지 못했던 다양한 분석 및 진단 서비스들을 빠르고 정확하게 제공하도록 하는 빅데이터 플랫폼 기반 건물 에너지 통합 관리 시스템 설계에 대해 서술한다.