• Title/Summary/Keyword: Test Resource Allocation

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Solving the test resource allocation using variable group genetic algorithm (가변 그룹 유전자알고리즘 기반의 시험자원할당 문제 해결)

  • Mun, Chang-min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.8
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    • pp.1415-1421
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    • 2016
  • There are considerable concern on the methods for the efficient utilization of the test-resources as increasing of the number of the tests for functionality and performance verification of weapon systems. Furthermore, with an increase in the complexity of the resource assignment the decision support is required. Test resource allocation is basically the same problems as conventional NP-hard FJSP(Flexible Job Shop Problem), therefore empirical test resource allocation method that has been used in many decades is limited in the time performance. Although research has been conducted applying the genetic algorithm to the FJSP, it is limited in the test resource allocation domain in which more than one machine is necessary for a single operation. In this paper, a variable group genetic algorithm is proposed. The algorithm is expected to improve the test plan efficiency by automating and optimizing the existing manual based allocation. The simulation result shows that the algorithm could be applicable to the test plan.

Differences in Time Use Satisfaction by Time Allocation Types of the Elderly (노인의 시간배분 유형에 따른 시간사용만족도의 차이)

  • Kim, Oi-Sook
    • Journal of Family Resource Management and Policy Review
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    • v.19 no.1
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    • pp.163-180
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    • 2015
  • The purpose of this study was to explore a typology of time allocation, investigate determinants of time allocation types, and analyze differences in time use satisfaction by the types of time use of the elderly. The data source for this research was the 2009 Time Use Survey conducted by the Korea National Statistical office (KNSO). The 4,699 time diaries (3,552 for weekday, 1,147 for Sunday) completed by the elderly over the age of 60 were analyzed using mean, standard deviation, chi-square, cluster analysis, ANOVA analysis, Duncan test, and multinomial logistic regression analysis. Time allocation of the elderly was classified into four types: personal care oriented, work oriented, leisure oriented, and balanced type. Gender, age, education, employment status, income, and the presence of spouse were identified as determinants for each type. According to the types of time allocation, time use satisfaction was different on week days.

Optimized Module Design for Berth Planning of Logistics Information System Using Tabu Search Algorithm (타부탐색을 이용한 물류정보시스템의 선석계획 최적화 모듈 설계)

  • Hong, Dong-Hee;Kim, Chang-Gon
    • The KIPS Transactions:PartB
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    • v.11B no.1
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    • pp.63-70
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    • 2004
  • Port operation is largely divided into gate operation, yard operation and berth operation. Operation strategy and optimal resource allocation for three parts are important in the productivity of the port operation.. Especially the resource allocation planning in berth operation needs optimization, because it is directly connected with the processing time in shipping. Berth planning is not independent on recourse allocation but interrelated with yard stacking area allocation. Therefore, we design the optimized module of berth planning and give priority to interrelationship with yard space allocation, while existing studies design independent resource allocation in berth planning. We suggest constraints by mathematical method, and they are related to yard stacking area allocation with existing constraints. Then we look for solutions, use tabu search to optimize them, and design optimized the berth planning module. In the performance test of optimized module design of berth planning, we find that the berth planning with yard stacking area allocation takes less processing time than without yard stacking area allocation.

Energy and Service Level Agreement Aware Resource Allocation Heuristics for Cloud Data Centers

  • Sutha, K.;Nawaz, G.M.Kadhar
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.11
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    • pp.5357-5381
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    • 2018
  • Cloud computing offers a wide range of on-demand resources over the internet. Utility-based resource allocation in cloud data centers significantly increases the number of cloud users. Heavy usage of cloud data center encounters many problems such as sacrificing system performance, increasing operational cost and high-energy consumption. Therefore, the result of the system damages the environment extremely due to heavy carbon (CO2) emission. However, dynamic allocation of energy-efficient resources in cloud data centers overcomes these problems. In this paper, we have proposed Energy and Service Level Agreement (SLA) Aware Resource Allocation Heuristic Algorithms. These algorithms are essential for reducing power consumption and SLA violation without diminishing the performance and Quality-of-Service (QoS) in cloud data centers. Our proposed model is organized as follows: a) SLA violation detection model is used to prevent Virtual Machines (VMs) from overloaded and underloaded host usage; b) for reducing power consumption of VMs, we have introduced Enhanced minPower and maxUtilization (EMPMU) VM migration policy; and c) efficient utilization of cloud resources and VM placement are achieved using SLA-aware Modified Best Fit Decreasing (MBFD) algorithm. We have validated our test results using CloudSim toolkit 3.0.3. Finally, experimental results have shown better resource utilization, reduced energy consumption and SLA violation in heterogeneous dynamic cloud environment.

Time allocation of a dual-earner working group with preschool children on working and nonworking days (미취학자녀를 둔 맞벌이 집단의 근무일과 비근무일 생활시간배분)

  • Kim, Oisook;Song, Hyerim;Cho, Heekeum;Kim, Joohee
    • Journal of Family Resource Management and Policy Review
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    • v.20 no.3
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    • pp.25-43
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    • 2016
  • This study focused on the time use of a dual-earner working group with preschool children on working and nonworking days using 2014 time-use survey data provided by Statistics Korea(KOSTAT). We collected the time-use data recorded in a 2,158 time diary. We divided the time use into 4 parts ; paid work, household labor work (including caring work), leisure and living essentials. For the statistical analysis, we used SPSS 18.0 packages, i.e., descriptive statistics, T-test, Anova with Duncan test and regression for the impact off the independent factors. The results verified gender differences in time use and recognized the usefulness of the time-allocation analysis for the diagnosis of Work and Life Balance(WLB). In the conclusion, we suggest increasing men's time allocation for household labor as a crucial solution to the WLB of dual-earner working groups. And the follow-up study should include the various factors that affect the time allocation of dual-earner groups, such as type of labor and job and children's ages.

Adaptive Resource Allocation for Traffic Flow Control in Hybrid Networks

  • Son, Sangwoo;Rhee, Byungho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.7 no.1
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    • pp.38-55
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    • 2013
  • Wireless network systems provide fast data transmission rates and various services to users of mobile devices such as smartphones and smart pads. Because many people use high-performance mobile devices, the use of real-time multimedia services is increasing rapidly. However, the preoccupation of resources by real-time traffic users is causing harm to other services-for example, frequent call interference, lowered service quality, and poor network performance. This paper suggests a resource allocation algorithm for effective traffic service support in a hybrid network. The main objective is to obtain an optimum value of data rates by comparing user requirements with the amount of resources that can be allocated. A new mechanism based on Adaptive-Quality of Service (QoS) and a monitoring system based on Queue-Aware are proposed. Adaptive-QoS supports effective resource control according to the type of traffic service, and the monitoring system based on Queue-Aware measures the amount of resources in order to calculate the maximum that can be allocated. We apply our algorithm to a test system and use Qualnet 4.5.1 to evaluate its performance.

Time allocation of men who work long hours and their wives (남성 장시간 근로집단 및 그 배우자집단의 생활시간배분)

  • Song, Hyerim;Kim, Yookyung;Kim, Joohee
    • Journal of Family Resource Management and Policy Review
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    • v.21 no.3
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    • pp.43-59
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    • 2017
  • This study aimed to analyze time allocation for men who work long hours and their wives. Using 2014 time-use survey data (provided by Statistics Korea), we analyzed the amount of time spent in four areas-paid work, housework, leisure, and life essentials-of male workers who work more than 52 hours a week and of their wives. Descriptive statistics and a paired t-test were conducted using SPSS version 18.0. The results were as follows: First, the time allocation of men who worked long hours differed from their wives with the exception of personal maintenance time. Second, the working time of wives who work long hours was longer than their husbands who work long. Third, men who worked long hours did less housework when their wives were employed than when they were not employed. All the results showed gender differences in terms of time allocation. Equal role-sharing between spouses is needed for the work-life balance of both husbands and wives.

Optimal Allocation Strategy Based on Stackelberg Game for Inspecting Drunk Driving on Traffic Network

  • Jie, Yingmo;Li, Mingchu;Tang, Tingting;Guo, Cheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.12
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    • pp.5759-5779
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    • 2017
  • As the main means to cope with the stubborn problem of drunk driving, the inspection of drunk driving has already been paid more attention and thus reinforced. In this paper, we model this scenario as a Stackelberg game, where the police department (called defender) allocates resources dynamically in terms of the traffic situation on the traffic network to arrest drink drivers and drivers who drink (called attacker), whether choosing drunk driving or designated driving service, expect to minimize their cost for given travel routes. However, with the number of resources are limited, our goal is to calculate the optimal resource allocation strategy for the defender. Therefore, first, we provide an effective approach (named OISDD) to fulfill our goal, i.e., generate the optimal strategy to inspect drunk driving. Second, we apply OISDD to directed graphs (which are abstracted from Dalian traffic network) to analyze and test its correctness and rationality. The experimental results show that OISDD is feasible and efficient.

Review of Wind Energy Publications in Korea Citation Index using Latent Dirichlet Allocation (잠재디리클레할당을 이용한 한국학술지인용색인의 풍력에너지 문헌검토)

  • Kim, Hyun-Goo;Lee, Jehyun;Oh, Myeongchan
    • New & Renewable Energy
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    • v.16 no.4
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    • pp.33-40
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    • 2020
  • The research topics of more than 1,900 wind energy papers registered in the Korean Journal Citation Index (KCI) were modeled into 25 topics using latent directory allocation (LDA), and their consistency was cross-validated through principal component analysis (PCA) of the document word matrix. Key research topics in the wind energy field were identified as "offshore, wind farm," "blade, design," "generator, voltage, control," 'dynamic, load, noise," and "performance test." As a new method to determine the similarity between research topics in journals, a systematic evaluation method was proposed to analyze the correlation between topics by constructing a journal-topic matrix (JTM) and clustering them based on topic similarity between journals. By evaluating 24 journals that published more than 20 wind energy papers, it was confirmed that they were classified into meaningful clusters of mechanical engineering, electrical engineering, marine engineering, and renewable energy. It is expected that the proposed systematic method can be applied to the evaluation of the specificity of subsequent journals.

Hierarchical IoT Edge Resource Allocation and Management Techniques based on Synthetic Neural Networks in Distributed AIoT Environments (분산 AIoT 환경에서 합성곱신경망 기반 계층적 IoT Edge 자원 할당 및 관리 기법)

  • Yoon-Su Jeong
    • Advanced Industrial SCIence
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    • v.2 no.3
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    • pp.8-14
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    • 2023
  • The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.