• Title/Summary/Keyword: Resource consumption rate

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Energy-aware Virtual Resource Mapping Algorithm in Wireless Data Center

  • Luo, Juan;Fu, Shan;Wu, Di
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.819-837
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    • 2014
  • Data centers, which implement cloud service, have been faced up with quick growth of energy consumption and low efficiency of energy. 60GHz wireless communication technology, as a new option to data centers, can provide feasible approach to alleviate the problems. Aiming at energy optimization in 60GHz wireless data centers (WDCs), we investigate virtualization technology to assign virtual resources to minimum number of servers, and turn off other servers or adjust them to the state of low power. By comprehensive analysis of wireless data centers, we model virtual network and physical network in WDCs firstly, and propose Virtual Resource Mapping Packing Algorithm (VRMPA) to solve energy management problems. According to VRMPA, we adopt packing algorithm and sort physical resource only once, which improves efficiency of virtual resource allocation. Simulation results show that, under the condition of guaranteeing network load, VPMPA algorithm can achieve better virtual request acceptance rate and higher utilization rate of energy consumption.

Petroleum Imports and Exchange Rate Volatility (원유수입과 환율변동성)

  • Mo, Soo-Won;Kim, Chang-Beom
    • Environmental and Resource Economics Review
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    • v.11 no.3
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    • pp.397-414
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    • 2002
  • This paper presents an empirical analysis of exchange rate volatility, petroleum's import price and industrial production on petroleum imports. The GARCH framework is used to measure the exchange rate volatility. One of the most appealing features of the GARCH model is that it captures the volatility clustering phenomenon. We found one long-run relationship between petroleum imports, import price, industrial production, and exchange rate volatility using Johansen's multivariate cointegration methodology. Since there exists a cointegrating vector, therefore, we employ an error correction model to examine the short-run dynamic linkage, finding that the exchange rate volatility performs a key role in the short-run. This paper also apply impulse-response functions to provide the dynamic responses of energy consumption to the exchange rate volatility. The results show that the response of energy consumption to exchange rate volatility declines at the first month and dies out very quickly.

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Dynamic Service Assignment based on Proportional Ordering for the Adaptive Resource Management of Cloud Systems

  • Mateo, Romeo Mark A.;Lee, Jae-Wan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.12
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    • pp.2294-2314
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    • 2011
  • The key issue in providing fast and reliable access on cloud services is the effective management of resources in a cloud system. However, the high variation in cloud service access rates affects the system performance considerably when there are no default routines to handle this type of occurrence. Adaptive techniques are used in resource management to support robust systems and maintain well-balanced loads within the servers. This paper presents an adaptive resource management for cloud systems which supports the integration of intelligent methods to promote quality of service (QoS) in provisioning of cloud services. A technique of dynamically assigning cloud services to a group of cloud servers is proposed for the adaptive resource management. Initially, cloud services are collected based on the excess cloud services load and then these are deployed to the assigned cloud servers. The assignment function uses the proposed proportional ordering which efficiently assigns cloud services based on its resource consumption. The difference in resource consumption rate in all nodes is analyzed periodically which decides the execution of service assignment. Performance evaluation showed that the proposed dynamic service assignment (DSA) performed best in throughput performance compared to other resource allocation algorithms.

Evaluation for Sustainable Resource Management In Korea using Material Flow Indicators (물질흐름지표를 이용한 한국(韓國)의 지속가능한 자원관리(資源管理) 평가 연구(硏究))

  • Kim, Yu-Jeong
    • Resources Recycling
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    • v.20 no.6
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    • pp.43-49
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    • 2011
  • This study calculated the three indices of Korea's resource productivity (and raw material productivity), material circulation rate and decoupling factor to evaluate the sustainability of domestic economic activities and resource consumption and examine the extent of dematerialization. Korea's resource productivity improved 22% from 1.32 million KRW/ton in 2000 to 1.61 million KRW/ton in 2007, with the annual average growth of resource productivity during the period standing at 2.88%. Raw material inputs accounted for 73-76% of domestic material consumption (DMC); raw material productivity for the year 2007 was 2.11 million KRW/ton, growing 3% on annual average from 2000 through 2007. The wastes released are circulated into the economic system through recycling and energization. Korea's material circulation went up from 10.9% in 2000 to 15.6% in 2007, growing by an annual average of 5.3% during the period. The rate of change in year-on-year growth, however, was found to be on the gradual decrease. This study also showed that Korea's economic activities were decoupled with its resource consumption as the country heads toward dematerialization through sustainable resource management.

Personalized Battery Lifetime Prediction for Mobile Devices based on Usage Patterns

  • Kang, Joon-Myung;Seo, Sin-Seok;Hong, James Won-Ki
    • Journal of Computing Science and Engineering
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    • v.5 no.4
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    • pp.338-345
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    • 2011
  • Nowadays mobile devices are used for various applications such as making voice/video calls, browsing the Internet, listening to music etc. The average battery consumption of each of these activities and the length of time a user spends on each one determines the battery lifetime of a mobile device. Previous methods have provided predictions of battery lifetime using a static battery consumption rate that does not consider user characteristics. This paper proposes an approach to predict a mobile device's available battery lifetime based on usage patterns. Because every user has a different pattern of voice calls, data communication, and video call usage, we can use such usage patterns for personalized prediction of battery lifetime. Firstly, we define one or more states that affect battery consumption. Then, we record time-series log data related to battery consumption and the use time of each state. We calculate the average battery consumption rate for each state and determine the usage pattern based on the time-series data. Finally, we predict the available battery time based on the average battery consumption rate for each state and the usage pattern. We also present the experimental trials used to validate our approach in the real world.

A Joint Allocation Algorithm of Computing and Communication Resources Based on Reinforcement Learning in MEC System

  • Liu, Qinghua;Li, Qingping
    • Journal of Information Processing Systems
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    • v.17 no.4
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    • pp.721-736
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    • 2021
  • For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

Socioeconomic Analysis of Public Forestry Investment(I) - On the Estimation of Social Discount Rate - (공공임업투자(公共林業投資)에 대한 사회경제적(社會經濟的) 분석(分析)(I) - 사회적(社會的) 할인율(割引率)의 추정에 대하여 -)

  • Chang, Cheol Su
    • Journal of Korean Society of Forest Science
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    • v.81 no.3
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    • pp.280-286
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    • 1992
  • When the social cost-benefit analysis is applied for analyzing the public forestry investment, the choice of discount rate to be used in analysis is critical. In this paper, the social discount rate discussed in the public economics was introduced and the social time preference rate as a measure of that was estimated for Korea. The component parameters of the model used are : the elasticity of social marginal utility of consumption and the growth rate of real consumption. The results for the social time preference rate and the elasticity of social marginal utility of consumption are 6.2% and -1.38, respectively, which are plausible and thus can be used as a useful basis in establishing rational resource allocation policies.

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Investment beneficial analysis of rice alternative plants

  • Yi, Hyang-Mi;Goh, Jong-Tae;Lee, Jong-In
    • Korean Journal of Agricultural Science
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    • v.40 no.2
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    • pp.169-176
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    • 2013
  • The price and revenue of rice are expected to decrease due to increasing rice imports, decreasing consumption and the discontinuance of the government's rice procurement. This degenerating profitability is leading to a rise in the cultivation of upland-crops such as beans, fodder crops and fruits in paddy fields. However, there is a lack of research on the selection of rice substitute crops which are adaptable to the relevant region through profitability analysis. This research, therefore, analyzed investment profitability of rice substitute crops for Cheorwon-gun area in Kangwon province. The study applied net present value (NPV) and internal rate of return (IRR), which fit for mutually exclusive investments that make one selection to the exclusion of other crops. Target crops are green house plants in Cheorwon-gun area. Financial analysis showed paprika and cucumber have investment feasibility for automated vinyl greenhouses and conventional plastic greenhouses respectively.

A Comparative Study and Analysis of LoRaWAN Performance in NS3

  • Arshad Farhad;Jae-Young Pyun
    • Smart Media Journal
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    • v.13 no.1
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    • pp.45-51
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    • 2024
  • Long Range Wide Area Network (LoRaWAN) is a widely adopted Internet of Things (IoT) protocol due to its high range and lower energy consumption. LoRaWAN utilizes Adaptive Data Rate (ADR) for efficient resource (e.g., spreading factor and transmission power) management. The ADR manages these two resource parameters on the network server side and end device side. This paper focuses on analyzing the ADR and Gaussian ADR performance of LoRaWAN. We have performed NS3 simulation under a static scenario by varying the antenna height. The simulation results showed that antenna height has a significant impact on the packet delivery ratio. Higher antenna height (e.g., 50 m) has shown an improved packet success ratio when compared with lower antenna height (e.g., 10 m) in static and mobility scenarios. Based on the results, it is suggested to use the antenna at higher allevation for successful packet delivery.

Resource Allocation Algorithm for Multiple RIS-Assisted UAV Networks (다중 UAV-RIS 네트워크를 위한 자원 할당 알고리즘)

  • Heejae Park;Laihyuk Park
    • Journal of Platform Technology
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    • v.11 no.1
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    • pp.3-10
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    • 2023
  • Unmanned Aerial Vehicles (UAVs) have gained significant attention in 5G and 6G wireless networks due to their high flexibility and low hardware costs. However, UAV communication is still challenged by blockage and energy consumption issues. Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising solution to these challenges, enabling improved spectral efficiency and reduced energy consumption by transmitting signals to users who cannot receive signals because of the obstacles. Many previous studies have focused on minimizing power consumption and data transmission delay through phase shift and power optimization. This paper proposes an algorithm that maximizes the sum rate by including bandwidth optimization. Simulation results demonstrate the effectiveness of the proposed algorithm.

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