• Title/Summary/Keyword: Heuristics for $A^*$ algorithm

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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.

Multi Colony Ant Model using Positive.Negative Interaction between Colonies (집단간 긍정적.부정적 상호작용을 이용한 다중 집단 개미 모델)

  • Lee, Seung-Gwan;Chung, Tae-Choong
    • The KIPS Transactions:PartB
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    • v.10B no.7
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    • pp.751-756
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    • 2003
  • Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP) . In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance and we wish to certify that qualitative level of problem solution is excellent.

An Optimal Path Search Method based on Traffic Information for Telematics Terminals (텔레매틱스 단말기를 위한 교통 정보를 활용한 최적 경로 탐색 기법)

  • Kim, Jin-Deog
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.12
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    • pp.2221-2229
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    • 2006
  • Optimal path search algorithm which is a killer application of mobile device to utilize location information should consider traffic flows of the roads as well as the distance between a departure and destination. The existing path search algorithms, however, are net able to cope efficiently with the change of the traffic flows. In this paper, we propose a new optimal path search algorithm. The algorithm takes the current flows into consideration in order to reduce the cost to get destination. It decomposes the road network into Fixed Grid to get variable heuristics. We also carry out the experiments with Dijkstra and Ar algorithm in terms of the execution time, the number of node accesses and the accuracy of path. The results obtained from the experimental tests show the proposed algorithm outperforms the others. The algorithm is highly expected to be useful in a advanced telematics systems.

Analysis and Classfication of Heuristic Algorithms for Node Coloring Problem (노드채색문제에 대한 기존 해법의 분석 및 분류)

  • 최택진;명영수;차동완
    • Journal of the Korean Operations Research and Management Science Society
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    • v.18 no.3
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    • pp.35-49
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    • 1993
  • The node coloring problem is a problem to color the nodes of a graph using the minimum number of colors possible so that any two adjacent nodes are colored differently. This problem, along with the edge coloring problem, has a variety of practical applications particularly in item loading, resource allocation, exam timetabling, and channel assignment. The node coloring problem is an NP-hard problem, and thus many researchers develop a number of heuristic algorithms. In this paper, we survey and classify those heuristics with the emphasis on how an algorithm orders the nodes and colors the nodes using a determined ordering.

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IDDQ Test Pattern Generation in CMOS Circuits (CMOS 조합회로의 IDDQ 테스트패턴 생성)

  • 김강철;송근호;한석붕
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.1
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    • pp.235-244
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    • 1999
  • This Paper proposes a new compaction algorithm for IDDQ testing in CMOS Circuits. A primary test pattern is generated by the primitive fault pattern which is able to detect GOS(gate-oxide short) and the bridging faults in an internal primitive gate. The new algorithm can reduce the number of the test vectors by decreasing the don't care(X) in the primary test pattern. The controllability of random number is used on processing of the backtrace together four ones of heuristics. The simulation results for the ISCAS-85 benchmark circuits show that the test vector reduction is more than 45% for the large circuits on the average compared to static compaction algorithms.

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Heuristic Backtrack Search Algorithm for Energy-efficient Clustering in Wireless Sensor Networks (무선 센서 네트웍에서 에너지 효율적인 집단화를 위한 경험적 백트랙 탐색 알고리즘)

  • Sohn, Surg-Won
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.5
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    • pp.219-227
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    • 2008
  • As found in research on constraint satisfaction problems, the choice of variable ordering heuristics is crucial for effective solving of constraint optimization problems. For the special problems such as energy-efficient clustering in heterogeneous wireless sensor networks, in which cluster heads have an inclination to be near a base station, we propose a new approach based on the static preferences variable orderings and provide a pnode heuristic algorithm for a specific application. The pnode algorithm selects the next variable with the highest Preference. In our problem, the preference becomes higher when the cluster heads are closer to the optimal region, which can be obtained a Priori due to the characteristic of the problem. Since cluster heads are the most dominant sources of Power consumption in the cluster-based sensor networks, we seek to minimize energy consumption by minimizing the maximum energy dissipation at each cluster heads as well as sensor nodes. Simulation results indicate that the proposed approach is more efficient than other methods for solving constraint optimization problems with static preferences.

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Region Segmentation from MR Brain Image Using an Ant Colony Optimization Algorithm (개미 군집 최적화 알고리즘을 이용한 뇌 자기공명 영상의 영역분할)

  • Lee, Myung-Eun;Kim, Soo-Hyung;Lim, Jun-Sik
    • The KIPS Transactions:PartB
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    • v.16B no.3
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    • pp.195-202
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    • 2009
  • In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.

Boundary Extraction of Moving Objects using Moving Edge and Heuristic Search (이동에지와 휴리스틱 탐색을 이용한 움직이는 물체의 경계추출)

  • 김종대;김성대;김재균
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.14 no.3
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    • pp.249-262
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    • 1989
  • We present a method of boundary extraction of moving objects. We propose four methods for detecting moving edge pixels which can be located on the boundaries of moving objects. We select the best one after we test the above four methods to real image sequences. The portion of the boundaries of moving objects which is marked as moving edge pixels is searched along the moving edge pixels with simple heuristics. And the end points of the resultant line segments are utilized as the start points of the secon stage heuristic search. This second stage search is performed for the boundaries of moving objects which is not marked as moving edge pixels due to various reasons. We test our algorithm for two real sequences and we find that this simple algorithm has good performance.

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An Addition-Chain Heuristics and Two Modular Multiplication Algorithms for Fast Modular Exponentiation (모듈라 멱승 연산의 빠른 수행을 위한 덧셈사슬 휴리스틱과 모듈라 곱셈 알고리즘들)

  • 홍성민;오상엽;윤현수
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.7 no.2
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    • pp.73-92
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    • 1997
  • A modular exponentiation( E$M^{$=varepsilon$}$mod N) is one of the most important operations in Public-key cryptography. However, it takes much time because the modular exponentiation deals with very large operands as 512-bit integers. Modular exponentiation is composed of repetition of modular multiplications, and the number of repetition is the same as the length of the addition-chain of the exponent(E). Therefore, we can reduce the execution time of modular exponentiation by finding shorter addition-chain(i.e. reducing the number of repetitions) or by reducing the execution time of each modular multiplication. In this paper, we propose an addition-chain heuristics and two fast modular multiplication algorithms. Of two modular multiplication algorithms, one is for modular multiplication between different integers, and the other is for modular squaring. The proposed addition-chain heuristics finds the shortest addition-chain among exisiting algorithms. Two proposed modular multiplication algorithms require single-precision multiplications fewer than 1/2 times of those required for previous algorithms. Implementing on PC, proposed algorithms reduce execution times by 30-50% compared with the Montgomery algorithm, which is the best among previous algorithms.

Automatic Extraction of Component Inspection Regions from Printed Circuit Board by Image Clustering (영상 클러스터링에 의한 인쇄회로기판의 부품검사영역 자동추출)

  • Kim, Jun-Oh;Park, Tae-Hyoung
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.3
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    • pp.472-478
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    • 2012
  • The inspection machine in PCB (printed circuit board) assembly line checks assembly errors by inspecting the images inside of the component inspection region. The component inspection region consists of region of component package and region of soldering. It is necessary to extract the regions automatically for auto-teaching system of the inspection machine. We propose an image segmentation method to extract the component inspection regions automatically from images of PCB. The acquired image is transformed to HSI color model, and then segmented by several regions by clustering method. We develop a modified K-means algorithm to increase the accuracy of extraction. The heuristics generating the initial clusters and merging the final clusters are newly proposed. The vertical and horizontal projection is also developed to distinguish the region of component package and region of soldering. The experimental results are presented to verify the usefulness of the proposed method.