• Title/Summary/Keyword: Probability of Connectivity

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Connectivity Analysis of Cognitive Radio Ad-hoc Networks with Shadow Fading

  • Dung, Le The;An, Beongku
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.9
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    • pp.3335-3356
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    • 2015
  • In this paper, we analyze the connectivity of cognitive radio ad-hoc networks in a log-normal shadow fading environment. Considering secondary user and primary user's locations and primary user's active state are randomly distributed according to a homogeneous Poisson process and taking into account the spectrum sensing efficiency of secondary user, we derive mathematical models to investigate the connectivity of cognitive radio ad-hoc networks in three aspects and compare with the connectivity of ad-hoc networks. First, from the viewpoint of a secondary user, we study the communication probability of that secondary user. Second, we examine the possibility that two secondary users can establish a direct communication link between them. Finally, we extend to the case of finding the probability that two arbitrary secondary users can communicate via multi-hop path. We verify the correctness of our analytical approach by comparing with simulations. The numerical results show that in cognitive radio ad-hoc networks, high fading variance helps to remarkably improve connectivity behavior in the same condition of secondary user's density and primary user's average active rate. Furthermore, the impact of shadowing on wireless connection probability dominates that of primary user's average active rate. Finally, the spectrum sensing efficiency of secondary user significantly impacts the connectivity features. The analysis in this paper provides an efficient way for system designers to characterize and optimize the connectivity of cognitive radio ad-hoc networks in practical wireless environment.

Estimation of Reward Probability in the Fronto-parietal Functional Network: An fMRI Study

  • Shin, Yeonsoon;Kim, Hye-young;Min, Seokyoung;Han, Sanghoon
    • Science of Emotion and Sensibility
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    • v.20 no.4
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    • pp.101-112
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    • 2017
  • We investigated the neural representation of reward probability recognition and its neural connectivity with other regions of the brain. Using functional magnetic resonance imaging (fMRI), we used a simple guessing task with different probabilities of obtaining rewards across trials to assay local and global regions processing reward probability. The results of whole brain analysis demonstrated that lateral prefrontal cortex, inferior parietal lobe, and postcentral gyrus were activated during probability-based decision making. Specifically, the higher the expected value was, the more these regions were activated. Fronto-parietal connectivity, comprising inferior parietal regions and right lateral prefrontal cortex, conjointly engaged during high reward probability recognition compared to low reward condition, regardless of whether the reward information was extrinsically presented. Finally, the result of a regression analysis identified that cortico-subcortical connectivity was strengthened during the high reward anticipation for the subjects with higher cognitive impulsivity. Our findings demonstrate that interregional functional involvement is involved in valuation based on reward probability and that personality trait such as cognitive impulsivity plays a role in modulating the connectivity among different brain regions.

Efficient Deployment of RSUs in Smart Highway Environment

  • Ge, Mingzhu;Chung, Yeongjee
    • International journal of advanced smart convergence
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    • v.8 no.4
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    • pp.179-187
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    • 2019
  • Vehicular density is usually low in a highway environment. Consequently, connectivity of the vehicular ad hoc networks (VANETs) might be poor. We are investigating the problem of deploying the approximation optimal roadside units (RSUs) on the highway covered by VANETs, which employs VANETs to provide excellent connectivity. The goal is to estimate the minimal number of deployed RSUs to guarantee the connectivity probability of the VANET within a given threshold considering that RSUs are to be allocated equidistantly. We apply an approximation algorithm to distribute RSUs locations in the VANETs. Thereafter, performance of the proposed scheme is evaluated by calculating the connectivity probability of the VANET. The simulation results show that there is the threshold value M of implemented RSUs corresponding to each vehicular network with N vehicles. The connectivity probability increases slowly with the number of RSUs getting larger.

Architectures and Connection Probabilities forWireless Ad Hoc and Hybrid Communication Networks

  • Chen, Jeng-Hong;Lindsey, William C.
    • Journal of Communications and Networks
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    • v.4 no.3
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    • pp.161-169
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    • 2002
  • Ad hoc wireless networks involving large populations of scattered communication nodes will play a key role in the development of low power, high capacity, interactive, multimedia communication networks. Such networks must support arbitrary network connections and provide coverage anywhere and anytime. This paper partitions such arbitrarily connected network architectures into three distinct groups, identifies the associated dual network architectures and counts the number of network architectures assuming there exist N network nodes. Connectivity between network nodes is characterized as a random event. Defining the link availability P as the probability that two arbitrary network nodes in an ad hoc network are directly connected, the network connection probability $ \integral_n$(p) that any two network nodes will be directly or indirectly connected is derived. The network connection probability $ \integral_n$(p) is evaluated and graphically demonstrated as a function of p and N. It is shown that ad hoc wireless networks containing a large number of network nodes possesses the same network connectivity performance as does a fixed network, i.e., for p>0, $lim_{N\to\infty} Integral_n(p)$ = 1. Furthermore, by cooperating with fixed networks, the ad hoc network connection probability is used to derive the global network connection probability for hybrid networks. These probabilities serve to characterize network connectivity performance for users of wireless ad hoc and hybrid networks, e.g., IEEE 802.11, IEEE 802.15, IEEE 1394-95, ETSI BRAN HIPERLAN, Bluetooth, wireless ATM and the world wide web (WWW).

Secure Connectivity Probability of Multi-hop Clustered Randomize-and-Forward Networks

  • Wang, Xiaowei;Su, Zhou;Wang, Guangyi
    • ETRI Journal
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    • v.39 no.5
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    • pp.729-736
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    • 2017
  • This work investigates secure cluster-aided multi-hop randomize-and-forward networks. We present a hop-by-hop multi-hop transmission scheme with relay selection, which evaluates for each cluster the relays that can securely receive the message. We propose an analytical model to derive the secure connectivity probability (SCP) of the hop-by-hop transmission scheme. For comparison, we also analyze SCPs of traditional end-to-end transmission schemes with two relay-selection policies. We perform simulations, and our analytical results verify that the proposed hop-by-hop scheme is superior to end-to-end schemes, especially with a large number of hops or high eavesdropper channel quality. Numerical results also show that the proposed hop-by-hop scheme achieves near-optimal performance in terms of the SCP.

Measuring Connectivity in Heterogenous Landscapes: a Review and Application (이질적 경관에서의 연결성 측정: 리뷰 및 적용)

  • Song, Wonkyong;Kim, Eunyoung;Lee, Dong-Kun
    • Journal of Environmental Impact Assessment
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    • v.21 no.3
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    • pp.391-407
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    • 2012
  • The loss of connectivity and fragmentation of forest landscapes are seriously hindering dispersal of many forest-dwelling species, which may be critical for their viability and conservation by decreasing habitat area and increasing distance among habitats. For understanding their environmental impacts, numerous spatial models exist to measure landscape connectivity. However, general relationships between functional connectivity and landscape structure are lacking, there is a need to develop landscape metrics that more accurately measure landscape connectivity in whole landscape and individual patches. We reviewed functional and structural definition of landscape connectivity, explained their mathematical connotations, and applied representative 13 indices in 3 districts of Seoul having fragmented forest patches with tits, the threshold distance was applied 500m by considering the dispersal of tits. Results of correlation and principal component analysis showed that connectivity indices could be divided by measurement methods whether they contain the area attribute with distance or not. Betweenness centrality(BC), a representative index measuring distance and distribution among patches, appreciated highly stepping stone forest patches, and difference of probability of connectivity(dPC), an index measuring including area information, estimated integrated connectivity of patches. Therefore, for evaluating landscape connectivity, it is need to consider not only general information of a region and species' characteristics but also various measuring methods of landscape connectivity.

Improved Differential-Linear Cryptanalysis Using DLCT (DLCT를 활용한 향상된 차분선형 분석)

  • Kim, Hyunwoo;Kim, Seonggyeom;Hong, Deukjo;Sung, Jaechul;Hong, Seokhie
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.6
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    • pp.1379-1392
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    • 2018
  • The complexity of the differential-linear cryptanalysis is strongly influenced by the probability of the differential-linear characteristic computed under the assumption of round independence, linear approximation independence, and uniformity for the trail that does not satisfy differential trail. Therefore, computing the exact probability of the differential-linear characteristic is a very important issue related to the validity of the attack. In this paper, we propose a new concept called DLCT(Differential-Linear Connectivity Table) for the differential-linear cryptanalysis. Additionally, we propose an improved probability computation technique of differential-linear characteristic by applying DLCT. By doing so, we were able to weaken linear approximation independence assumption. We reanalyzed the previous results by applying DLCT to DES and SERPENT. The probability of 7-round differential-linear characteristic of DES is $1/2+2^{-5.81}$, the probability of 9-round differential-linear characteristic of SERPENT is computed again to $1/2+2^{-57.9}$, and data complexity required for the attack is reduced by $2^{0.2}$ and $2^{2.2}$ times, respectively.

Structural Topology Design Using Compliance Pattern Based Genetic Algorithm (컴플라이언스 패턴 기반 유전자 알고리즘을 이용한 구조물 위상설계)

  • Park, Young-Oh;Min, Seung-Jae
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.8
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    • pp.786-792
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    • 2009
  • Topology optimization is to find the optimal material distribution of the specified design domain minimizing the objective function while satisfying the design constraints. Since the genetic algorithm (GA) has its advantage of locating global optimum with high probability, it has been applied to the topology optimization. To guarantee the structural connectivity, the concept of compliance pattern is proposed and to improve the convergence rate, small number of population size and variable probability in genetic operators are incorporated into GA. The rank sum weight method is applied to formulate the fitness function consisting of compliance, volume, connectivity and checkerboard pattern. To substantiate the proposed method design examples in the previous works are compared with respect to the number of function evaluation and objective function value. The comparative study shows that the compliance pattern based GA results in the reduction of computational cost to obtain the reasonable structural topology.

A Novel Line Detection Method using Gradient Direction based Hough transform (Gradient 방향을 고려한 허프 변환을 이용한 직선 검출 방법)

  • Kim, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.1
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    • pp.197-205
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    • 2007
  • We have proposed a novel line detection method based on the estimated probability density function of gradient directions of edges. By estimating peaks of the density function, we determine groups of edges that have the same gradient direction. For edges in the same groups, we detect lines that correspond to peaks of the connectivity weighted distribution of the distances from the origin. In the experiments using the Data Matrix barcode images and LCD images, the proposed method showed better performance than conventional Methods in terms of the processing speed and accuracy.

Localized Algorithm to Improve Connectivity and Topological Resilience of Multi-hop Wireless Networks

  • Kim, Tae-Hoon;Tipper, David;Krishnamurthy, Prashant
    • Journal of information and communication convergence engineering
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    • v.11 no.2
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    • pp.69-81
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    • 2013
  • Maintaining connectivity is essential in multi-hop wireless networks since the network topology cannot be pre-determined due to mobility and environmental effects. To maintain the connectivity, a critical point in the network topology should be identified where the critical point is the link or node that partitions the network when it fails. In this paper, we propose a new critical point identification algorithm and also present numerical results that compare the critical points of the network and H-hop sub-network illustrating how effectively sub-network information can detect the network-wide critical points. Then, we propose two localized topological control resilient schemes that can be applied to both global and local H-hop sub-network critical points to improve the network connectivity and the network resilience. Numerical studies to evaluate the proposed schemes under node and link failure network conditions show that our proposed resilient schemes increase the probability of the network being connected in variety of link and node failure conditions.