• Title/Summary/Keyword: Random Resource Selection

Search Result 16, Processing Time 0.031 seconds

Enhanced Random Resource Selection Scheme for V2X (V2X를 위한 향상된 랜덤 자원 선택 기술)

  • Yoon, Sung-jun;Choi, Sang Won;Kwon, Ki-bum;Park, Dong-hyun;Li, Jianjun
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.42 no.5
    • /
    • pp.1058-1068
    • /
    • 2017
  • In V2X communication, a random based resource selection scheme is needed with considerations of cases that support devices without sidelink reception capabilities and require reduction of UE's power consumption. In this paper, as improvement of D2D's resource section scheme that one TRP is repeated to data subframe pool within a PSCCH period, it is proposed that different TRPs is applied for enhanced random resource selection based on pseudo-random sequence having UE-specific seed value. By results of proposed scheme's performance by numerical analysis, it is confirmed that collision probability among resources allocated to each UE for data TB is reduced, and a number of UEs which can avoid resource collision as much as possible and have simultaneous resource allocation is increased.

A Real-time Resource Allocation Algorithm for Minimizing the Completion Time of Workflow (워크플로우 완료시간 최소화를 위한 실시간 자원할당 알고리즘)

  • Yoon, Sang-Hum;Shin, Yong-Seung
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.29 no.1
    • /
    • pp.1-8
    • /
    • 2006
  • This paper proposes a real-time resource allocation algorithm for minimizing the completion time of overall workflow process. The jobs in a workflow process are interrelated through the precedence graph including Sequence, AND, OR and Loop control structure. A resource should be allocated for the processing of each job, and the required processing time of the job can be varied by the resource allocation decision. Each resource has several inherent restrictions such as the functional, geographical, positional and other operational characteristics. The algorithm suggested in this paper selects an effective resource for each job by considering the precedence constraint and the resource characteristics such as processing time and the inherent restrictions. To investigate the performance of the proposed algorithm, several numerical tests are performed for four different workflow graphs including standard, parallel and two series-parallel structures. In the tests, the solutions by the proposed algorithm are compared with random and optimal solutions which are obtained by a random selection rule and a full enumeration method respectively.

A Study on the prediction of BMI(Benthic Macroinvertebrate Index) using Machine Learning Based CFS(Correlation-based Feature Selection) and Random Forest Model (머신러닝 기반 CFS(Correlation-based Feature Selection)기법과 Random Forest모델을 활용한 BMI(Benthic Macroinvertebrate Index) 예측에 관한 연구)

  • Go, Woo-Seok;Yoon, Chun Gyeong;Rhee, Han-Pil;Hwang, Soon-Jin;Lee, Sang-Woo
    • Journal of Korean Society on Water Environment
    • /
    • v.35 no.5
    • /
    • pp.425-431
    • /
    • 2019
  • Recently, people have been attracting attention to the good quality of water resources as well as water welfare. to improve the quality of life. This study is a papers on the prediction of benthic macroinvertebrate index (BMI), which is a aquatic ecological health, using the machine learning based CFS (Correlation-based Feature Selection) method and the random forest model to compare the measured and predicted values of the BMI. The data collected from the Han River's branch for 10 years are extracted and utilized in 1312 data. Through the utilized data, Pearson correlation analysis showed a lack of correlation between single factor and BMI. The CFS method for multiple regression analysis was introduced. This study calculated 10 factors(water temperature, DO, electrical conductivity, turbidity, BOD, $NH_3-N$, T-N, $PO_4-P$, T-P, Average flow rate) that are considered to be related to the BMI. The random forest model was used based on the ten factors. In order to prove the validity of the model, $R^2$, %Difference, NSE (Nash-Sutcliffe Efficiency) and RMSE (Root Mean Square Error) were used. Each factor was 0.9438, -0.997, and 0,992, and accuracy rate was 71.6% level. As a result, These results can suggest the future direction of water resource management and Pre-review function for water ecological prediction.

Performance Analysis of Random Resource Selection in LTE D2D Discovery (LTE D2D 디스커버리에서 무작위 자원 선택 방법에 대한 성능 분석)

  • Park, Kyungwon;Kim, Joonyoung;Jeong, Byeong Kook;Lee, Kwang Bok;Choi, Sunghyun
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.42 no.3
    • /
    • pp.577-584
    • /
    • 2017
  • Long Term Evolution device-to-device (LTE D2D) is a key technology to mitigate data traffic load in a cellular system. It facilitates direct data exchange between neighboring users, which is preceded by D2D discovery. Each device advertises its presence to neighboring devices by broadcasting its discovery message. In this paper, we develop a mathematical analysis to assess the probability that discovery messages are successfully transmitted at the D2D discovery stage. We make use of stochastic geometry for modeling spatial statistics of nodes in a two dimensional space. It reflects signal to noise plus interference ratio (SINR) degradation due to resource collision and in-band emission, which leads to the discovery message reception probability being modeled as a function of the distance between the transmitter and the receiver. Numerical results verify that the newly developed analysis accurately estimates discovery message reception probabilities of nodes at the D2D discovery stage.

An Efficient Stochastic Channel Selection Algorithm for Cognitive Radio Networks (무선인지시스템을 위한 효율적인 채널 선택 알고리즘)

  • Pham, Thi Hong Chau;Koo, In-Soo
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.9 no.6
    • /
    • pp.29-35
    • /
    • 2009
  • An efficient stochastic channel selection algorithm for cognitive radio networks is proposed and analyzed in this paper. With the new algorithm utilizing quality of channels, the stationary level of the channels in idle state and history performance, we can find the best channel for secondary users to transmit data. Moreover, this method not only restricts channel switching of secondary users but also adapts to random resource environment of cognitive radio network. The advantages of the proposed algorithm are demonstrated clearly through computer simulation.

  • PDF

A study on helper node selection mechanisms in cooperative communications (협력통신에서 도움노드 선정방법에 대한 비교연구)

  • Jang, Jae-Shin
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.16 no.7
    • /
    • pp.1397-1405
    • /
    • 2012
  • Cooperative communications play a important role in increasing frame transmission rate at wireless communication networks where frequency resource is strictly limited. In this paper, we did a research on how to select the helper nodes that are very import in cooperative communications. As a prelude study in this research field, we carried out performance comparison of three helper node selection schemes using computer simulation. The system throughput was used as the performance measure and the random way point mobility model, where every communicating nodes move around within the designated communication range, was used.

A Meta-Analysis of the Effects of Multi-Cultural Education Program in Korea (다문화가정과 일반가정 유아와 아동을 대상으로 한 다문화교육 프로그램의 효과에 관한 메타분석)

  • Choi, Hea Young
    • Journal of Family Resource Management and Policy Review
    • /
    • v.19 no.3
    • /
    • pp.1-16
    • /
    • 2015
  • The purpose of this study was to synthesize the results of studies on the effects of multi-cultural education program for Korean children. Using the author's own selection criteria, 17 studies were finally selected and 31 effect sizes were calculated from these studies and used for meta analysis. The overall effect size for all studies on the random effect model was .802, and it was positive and high. Given the heterogeneity among the effect size, subgroup analysis was conducted. According to the analysis, effect sizes significantly differed depending on program goal, concerned multi-cultural higher than others. Result also showed that the high scored effect sizes were the general family, pre-school age children group, and the program were 11-20 children group in size, and 11~20 times in frequency of education.

Performance and Energy Oriented Resource Provisioning in Cloud Systems Based on Dynamic Thresholds and Host Reputation (클라우드 시스템에서 동적 임계치와 호스트 평판도를 기반으로 한 성능 및 에너지 중심 자원 프로비저닝)

  • Elijorde, Frank I.;Lee, Jaewan
    • Journal of Internet Computing and Services
    • /
    • v.14 no.5
    • /
    • pp.39-48
    • /
    • 2013
  • A cloud system has to deal with highly variable workloads resulting from dynamic usage patterns in order to keep the QoS within the predefined SLA. Aside from the aspects regarding services, another emerging concern is to keep the energy consumption at a minimum. This requires the cloud providers to consider energy and performance trade-off when allocating virtualized resources in cloud data centers. In this paper, we propose a resource provisioning approach based on dynamic thresholds to detect the workload level of the host machines. The VM selection policy uses utilization data to choose a VM for migration, while the VM allocation policy designates VMs to a host based on its service reputation. We evaluated our work through simulations and results show that our work outperforms non-power aware methods that don't support migration as well as those based on static thresholds and random selection policy.

An Adaptive Peer-to-Peer Search Algorithm for Reformed Node Distribution Rate (개선된 노드 분산율을 위한 적응적 P2P 검색 알고리즘)

  • Kim, Boon-Hee;Lee, Jun-Yeon
    • Journal of the Korea Society of Computer and Information
    • /
    • v.10 no.4 s.36
    • /
    • pp.93-102
    • /
    • 2005
  • Excessive traffic of P2P applications in the limited communication environment is considered as a network bandwidth problem. Moreover, Though P2P systems search a resource in the phase of search using weakly connected systems(peers' connection to P2P overlay network is very weakly connected), it is not guaranteed to download the very peer's resource in the phase of download. In previous P2P search algorithm (1), we had adopted the heuristic peer selection method based on Random Walks to resolve this problems. In this paper, we suggested an adaptive P2P search algorithm based on the previous algorithm(1) to reform the node distribution rate which is affected in unit peer ability. Also, we have adapted the discriminative replication method based on a query ratio to reduce traffic amount additionally. In the performance estimation result of this suggested system, our system works on a appropriate point of compromise in due consideration of the direction of searching and distribution of traffic occurrence.

  • PDF

Adjusting sampling bias in case-control genetic association studies

  • Seo, Geum Chu;Park, Taesung
    • Journal of the Korean Data and Information Science Society
    • /
    • v.25 no.5
    • /
    • pp.1127-1135
    • /
    • 2014
  • Genome-wide association studies (GWAS) are designed to discover genetic variants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.