• Title/Summary/Keyword: Graph algorithm

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Spatial Reuse Algorithm Using Interference Graph in Millimeter Wave Beamforming Systems

  • Jo, Ohyun;Yoon, Jungmin
    • ETRI Journal
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    • v.39 no.2
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    • pp.255-263
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    • 2017
  • This paper proposes a graph-theatrical approach to optimize spatial reuse by adopting a technique that quantizes the channel information into single bit sub-messages. First, we introduce an interference graph to model the network topology. Based on the interference graph, the computational requirements of the algorithm that computes the optimal spatial reuse factor of each user are reduced to quasilinear time complexity, ideal for practical implementation. We perform a resource allocation procedure that can maximize the efficiency of spatial reuse. The proposed spatial reuse scheme provides advantages in beamforming systems, where in the interference with neighbor nodes can be mitigated by using directional beams. Based on results of system level measurements performed to illustrate the physical interference from practical millimeter wave wireless links, we conclude that the potential of the proposed algorithm is both feasible and promising.

Task Planning Algorithm with Graph-based State Representation (그래프 기반 상태 표현을 활용한 작업 계획 알고리즘 개발)

  • Seongwan Byeon;Yoonseon Oh
    • The Journal of Korea Robotics Society
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    • v.19 no.2
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    • pp.196-202
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    • 2024
  • The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

AN EFFICIENT PRAM ALGORITHM FOR MAXIMUM-WEIGHT INDEPENDENT SET ON PERMUTATION GRAPHS

  • SAHA ANITA;PAL MADHUMANGAL;PAL TAPAN K.
    • Journal of applied mathematics & informatics
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    • v.19 no.1_2
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    • pp.77-92
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    • 2005
  • An efficient parallel algorithm is presented to find a maximum weight independent set of a permutation graph which takes O(log n) time using O($n^2$/ log n) processors on an EREW PRAM, provided the graph has at most O(n) maximal independent sets. The best known parallel algorithm takes O($log^2n$) time and O($n^3/log\;n$) processors on a CREW PRAM.

AN EFFICIENT ALGORITHM TO SOLVE CONNECTIVITY PROBLEM ON TRAPEZOID GRAPHS

  • Ghosh, Prabir K.;Pal, Madhumangal
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.141-154
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    • 2007
  • The connectivity problem is a fundamental problem in graph theory. The best known algorithm to solve the connectivity problem on general graphs with n vertices and m edges takes $O(K(G)mn^{1.5})$ time, where K(G) is the vertex connectivity of G. In this paper, an efficient algorithm is designed to solve vertex connectivity problem, which takes $O(n^2)$ time and O(n) space for a trapezoid graph.

Path Planning for Mobile Robots using Visibility Graph and Genetic Algorithms (가시도 그래프와 유전 알고리즘에 기초한 이동로봇의 경로계획)

  • 정연부;이민중;전향식;최영규
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.418-418
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    • 2000
  • This paper proposes a path planning algorithm for mobile robot. To generate an optimal path and minimum time path for a mobile robot, we use the Genetic Algorithm(GA) and Visibility Graph. After finding a minimum-distance between start and goal point, the path is revised to find the minimum time path by path-smoothing algorithm. Simulation results show that the proposed algorithms are more effective.

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ShareSafe: An Improved Version of SecGraph

  • Tang, Kaiyu;Han, Meng;Gu, Qinchen;Zhou, Anni;Beyah, Raheem;Ji, Shouling
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.11
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    • pp.5731-5754
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    • 2019
  • In this paper, we redesign, implement, and evaluate ShareSafe (Based on SecGraph), an open-source secure graph data sharing/publishing platform. Within ShareSafe, we propose De-anonymization Quantification Module and Recommendation Module. Besides, we model the attackers' background knowledge and evaluate the relation between graph data privacy and the structure of the graph. To the best of our knowledge, ShareSafe is the first platform that enables users to perform data perturbation, utility evaluation, De-A evaluation, and Privacy Quantification. Leveraging ShareSafe, we conduct a more comprehensive and advanced utility and privacy evaluation. The results demonstrate that (1) The risk of privacy leakage of anonymized graph increases with the attackers' background knowledge. (2) For a successful de-anonymization attack, the seed mapping, even relatively small, plays a much more important role than the auxiliary graph. (3) The structure of graph has a fundamental and significant effect on the utility and privacy of the graph. (4) There is no optimal anonymization/de-anonymization algorithm. For different environment, the performance of each algorithm varies from each other.

A Study on the Constructing the Function using Extension Edge Valued Graph (모서리값 확장 그래프를 사용한 함수구성에 관한연구)

  • Park, Chun-Myoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.4
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    • pp.863-868
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    • 2013
  • In recently years, many digital logic systems based on graph theory are analyzed and synthesized. This paper presented a method of constructing the function using edge valued extension graph which is based on graph theory. The graph is applied to a new data structure. from binary graph which is recently used in constructing the digital logic systems based on the graph theory. We discuss the mathematical background of literal and reed-muller expansion, and we discuss the edge valued extension graph which is the key of this paper. Also, we propose the algorithms which is the function derivation based on the proposed edge valued extension graph. That is the function minimization method of the n-variables m-valued functions and showed that the algorithm had the regularity with module by which the same blocks were made concerning about the schematic property of the proposed algorithm.

Embedding algorithm among star graph and pancake graph, bubblesort graph (스타 그래프와 팬케익, 버블정렬 그래프 사이의 임베딩 알고리즘)

  • Kim, Jong-Seok;Lee, Hyeong-Ok;Kim, Sung-Won
    • The Journal of Korean Association of Computer Education
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    • v.13 no.5
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    • pp.91-102
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    • 2010
  • Star graph is a well-known interconnection network to further improve the network cost of Hypercube and has good properties such as node symmetry, maximal fault tolerance and strongly hierarchical property. In this study, we will suggest embedding scheme among star graph and pancake graph, bubblesort graph, which are variations of star graph. We will show that bubblesort graph can be embedded into pancake and star graph with dilation 3, expansion 1, respectively and pancake graph can be embedded into bubblesort graph with dilation cost O($n^2$). Additionally, we will show that star graph can be embedded into pancake graph with dilation 4, expansion 1. Also, with dilation cost O(n) we will prove that star graph can be embedded into bubblesort graph and pancake graph can be embedded into star graph.

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A Reliability Computational Algorithm for Reliability Block Diagram Using Factoring Method (팩토링 기법을 이용한 신뢰성 구조도의 신뢰도 계산 알고리즘)

  • Lie, Chang-Hoon;Kim, Myung-Gyu;Lee, Sang-Cheon
    • Journal of Korean Institute of Industrial Engineers
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    • v.20 no.3
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    • pp.3-14
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    • 1994
  • In this study, two reliability computational algorithms which respectively utilize a factoring method are proposed for a system represented by reliability block diagram. First, vertex factoring algorithm is proposed. In this algorithm, a reliability block diagram is considered as a network graph with vertex reliabilities. Second algorithm is mainly concerned with conversion of a reliabilities block diagram into a network graph with edge reliabilities. In this algorithm, the independence of edges is preserved by eliminating replicated edges, and in computing the reliability of a converted network graph, existing edge factoring algorithm is applied. The efficiency of two algorithms are compared for example systems with respect to computing times. The results shows that the second algorithm is shown to be more efficient than the first algorithm.

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Shortest Path-Finding Algorithm using Multiple Dynamic-Range Queue(MDRQ) (다중 동적구간 대기행렬을 이용한 최단경로탐색 알고리즘)

  • Kim, Tae-Jin;Han, Min-Hong
    • The KIPS Transactions:PartA
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    • v.8A no.2
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    • pp.179-188
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    • 2001
  • We analyze the property of candidate node set in the network graph, and propose an algorithm to decrease shortest path-finding computation time by using multiple dynamic-range queue(MDRQ) structure. This MDRQ structure is newly created for effective management of the candidate node set. The MDRQ algorithm is the shortest path-finding algorithm that varies range and size of queue to be used in managing candidate node set, in considering the properties that distribution of candidate node set is constant and size of candidate node set rapidly change. This algorithm belongs to label-correcting algorithm class. Nevertheless, because re-entering of candidate node can be decreased, the shortest path-finding computation time is noticeably decreased. Through the experiment, the MDRQ algorithm is same or superior to the other label-correcting algorithms in the graph which re-entering of candidate node didn’t frequently happened. Moreover the MDRQ algorithm is superior to the other label-correcting algorithms and is about 20 percent superior to the other label-setting algorithms in the graph which re-entering of candidate node frequently happened.

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