• 제목/요약/키워드: 에너지 최소화 알고리즘

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Bio-inspired Node Selection and Multi-channel Transmission Algorithm in Wireless Sensor Networks (무선 센서망에서 생체시스템 기반의 전송노드 선택 및 다중 채널 전송 알고리즘)

  • Son, Jae Hyun;Yang, Yoon-Gi;Byun, Hee-Jung
    • Journal of Internet Computing and Services
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    • v.15 no.5
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    • pp.1-7
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    • 2014
  • WireWireless sensor networks(WSNs) are generally comprised of densely deployed sensor nodes, which causes highly redundant sensor data transmission and energy waste. Many studies have focused on energy saving in WSNs. However, delay problem also should be taken into consideration for mission-critical applications. In this paper, we propose a BISA (Bio-Inspired Scheduling Algorithm) to reduce the energy consumption and delay for WSNs inspired by biological systems. BISA investigates energy-efficient routing path and minimizes the energy consumption and delay using multi-channel for data transmission. Through simulations, we observe that the BISA archives energy efficiency and delay guarantees.

A Tangential Cutting Algorithm using Simulated Annealing (시뮬레이티드 어니얼링을 이용한 경사선분 추출 알고리즘의 개발)

  • 천인국;김승우;방재철;이효진
    • Proceedings of the Korea Multimedia Society Conference
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    • 2002.05d
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    • pp.574-578
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    • 2002
  • 층 단위로 가공하는 RP(Rapid Prototype) 시스템에서 가공되는 물체의 표면에서는 계단형의 윤곽이 나타난다. 이러한 문제점을 보완하기 위해 경사절단 방법으로 3D 모델을 가공하여 기존의 가공방법에 의해 발생하는 계단형 윤곽 모습과 표면 왜곡 둥의 문제를 보완할 수 있다. 최적의 경사선분의 집합을 구하기 위해 경사절단 선분의 길이와 중간층 점의 거리를 정의하여 이를 최소화하는 에너지 함수를 구현한다. 그러나 이 방법은 경사절단 선분이 에너지가 작아지는 방향으로만 움직이기 때문에 레이어의 윤곽이 복잡한 경우 최적의 위치가 아닌 다른 위치에서 더 이상 움직이지 않는 국부적 최적해(Local Minima)가 발생할 수 있다. 본 논문에서는 국부적 최적해를 벗어나기 위해 경사절단 선분 추출 알고리즘에 시뮬레이티드 어니얼링(Simulated Annealing) 방법을 적용하였다. 제안된 방법으로 테스트한 결과 복잡한 레이어 윤곽에서 생길 수 있는 국부적 최적해가 어느 정도 해결되었다.

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Algorithm for Adjusting Cluster Size according to Location Information in WSN (무선 센서네트워크에서 센서노드의 위치 정보를 이용한 클러스터 크기 조정 알고리즘)

  • Kwak, Tae-Kil;Jin, Kyo-Hong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.06a
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    • pp.389-392
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    • 2007
  • In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering technique. The sensed information in each cluster transfers to sink node through inter-cluster communications. Cluster head (CH) that nearby located in sink node much more spend own energy than far away CHs, because nearer CH forwards more data, so network lifetime is decreased. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster site, and improve CH lifetime by distributing transmission paths. As a result of analysis, the proposed algorithm shows longer network lifetime in WSN.

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An Efficient Shortcut Path Algorithm using Depth in Zigbee Network (Zigbee 네트워크에서 Depth를 이용한 효율적인 중간 경로 감소 알고리즘)

  • Kim, Duck-Young;Jung, Woo-Sub;Cho, Sung-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.12B
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    • pp.1475-1482
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    • 2009
  • In ZigBee network, using energy efficiently is necessary because ZigBee node works by battery. To use energy efficiently, it is one of the way to reduce unnecessary network traffic. In this paper, it presents efficient shortcut routing algorithm using depth of destination node in ZigBee network. In traditional tree routing, each node transfers data only to its own parent or child node, which is inefficient way. Efficient shortcut routing algorithm is also based on tree routing. However, we suggests the algorithm with using neighbor table and depth of destination that is able to transfer data to other neighbor node, not only to parent or child node. It minimizes coordinator bottleneck state and unnecessary intermediate routing path which happens in traditional tree routing.

Feature Weighting in Projected Clustering for High Dimensional Data (고차원 데이타에 대한 투영 클러스터링에서 특성 가중치 부여)

  • Park, Jong-Soo
    • Journal of KIISE:Databases
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    • v.32 no.3
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    • pp.228-242
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    • 2005
  • The projected clustering seeks to find clusters in different subspaces within a high dimensional dataset. We propose an algorithm to discover near optimal projected clusters without user specified parameters such as the number of output clusters and the average cardinality of subspaces of projected clusters. The objective function of the algorithm computes projected energy, quality, and the number of outliers in each process of clustering. In order to minimize the projected energy and to maximize the quality in clustering, we start to find best subspace of each cluster on the density of input points by comparing standard deviations of the full dimension. The weighting factor for each dimension of the subspace is used to get id of probable error in measuring projected distances. Our extensive experiments show that our algorithm discovers projected clusters accurately and it is scalable to large volume of data sets.

Cluster-Based Multi-Channel Algorithm in SAN Environments (SAN 환경에서 클러스터 기반의 멀티채널 알고리즘)

  • Kong, Joon-Ik;Lee, Seong Ro
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.5
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    • pp.964-973
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    • 2015
  • Ship Area Network(SAN) can monitor the status of ship in real time and minimize the maintenance costs by connecting various devices to the network. In particular, among researches on SAN, Wireless Sensor Network using sensor nodes that is low-cost, low-power, and multifunctional has a number of advantages. In this paper, we propose cluster-based multi-channel algorithm considering the energy efficiency in wireless sensor network in a ship. The proposed algorithm shows the result of improvement of throughput and energy efficiency, because it reduces interference between clusters by using channel allocation algorithm that is distributed and dynamic.

Adjusting Cluster Size for Alleviating Network Lifetime in Wireless Sensor Network (무선 센서네트워크에서 네트워크 수명 연장을 위한 클러스터 크기 조정 알고리즘)

  • Kwak, Tae-Kil;Jin, Kyo-Hong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.6
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    • pp.1201-1206
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    • 2007
  • In this paper, we propose an algorithm that improve network lifetime by adjusting cluster size according to location information of sensor node in wireless sensor network (WSN) using clustering algorithm. The collected sensing information by sensor nodes in each cluster are transferred to sink node using inter-cluster communications method. Cluster head (CH) that located nearby sink node spend much more energy than those of far from sink node, because nearer CH forwards more data, so network lifetime has a tendency to decrease. Proposed algorithm minimizes energy consumption in adjacent cluster to sink node by decreasing cluster size, and improve CH lifetime by distributing transmission paths. As a result of mathematical analysis, the proposed algorithm shows longer network lifetime in WSN.

Application of Tabu Search for Service Restoration of Distribution System with Dispersed Generators (분산전원을 고려한 배전계통 고장 복구문제에 타부탐색법 적용)

  • Bae, Byung-Hyun;Mun, Kyeong-Jun;Kim, Hyung-Su;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.369-371
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    • 2003
  • 본 논문에서는 차세대 대체 에너지원으로서 주목받고 있으며, 상용화되고 있는 분산전원이 도입된 배전계통에서 고장이 발생한 경우, 경험적 최적화 알고리즘인 타부 탐색법을 적용한 고장 복구 알고리즘을 제안하고자 한다. 배전계통 고장복구 문제는 배전 선로상에 고장 발생시 최적의 부하절체를 함으로써 건전 정전구간을 최소화하는 것을 목적으로 한다. 배전 자동화시스템에서 분산전원 계통을 자동화하여 분산전원의 동작 상태를 감시하고 고장검출, 계통분리 또는 원격스위치를 제어함으로써 고장복구 방법을 제시한다. 제안한 알고리즘의 유용성을 입증하기 위해 참고문헌의 예제 계통에 제안한 방법을 적용해 본 결과, 제안한 알고리즘이 해의 탐색속도 및 해의 성능면에서 우수함을 확인하였다.

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A Robust Propagation Algorithm for Function Approximation (함수근사를 위한 로버스트 역전파 알고리즘)

  • Kim, Sang-Min;Hwang, Chang-Ha
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.3
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    • pp.747-753
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    • 1997
  • Function approximation from a set of input-output parirs has numerous applications in scientiffc and engineer-ing areas.Multiayer feedforward neural networks have been proposed as a good approximator of noninear function.The back propagation (BP) algorithm allows muktiayer feedforward neural networks oro learn input-output mappongs from training samples.However, the mapping acquired through the BP algorithm nay be cor-rupt when errorneous trauning data are employed.In this paper we propose a robust BP learning algorithm that is resistant to the errormeous data and is capable of rejecting gross errors during the approximation process.

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Improved Snakes Algorithm for Tongue Image Segmentation in Oriental Tongue Diagnosis (한방 설진에서 혀 영상 분할을 위한 개선된 스네이크 알고리즘)

  • Jang, Myeong-Soo;Lee, Woo-Beom
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.16 no.4
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    • pp.125-131
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    • 2016
  • Tongue image segmentation is critical for automation of the tongue diagnosis system. However, most image segmentation methods for tongue diagnosis systems in oriental medicine have been proposed as user-based manual types or semi-automatic types. This study proposed a new method for tongue image segmentation, which is the most important image processing stage for complete automation of the tongue diagnosis system in oriental medicine. The proposed method improved the conventional snake algorithm, by making improvement on the internal energy function so that, as the points move outward reversely, the snake energy function is minimized, by using the image characteristics of tongue images. To calculate external energy, hierarchical spatial filtering is applied to ensure resistance against noise. Also, The proposed method was tested by using sample images and actual images, and showed more robustness against the background noise than the conventional snake algorithm. And, when one selected point was moved by the improved snake algorithm, energy values at the starting, middle, and end points were analyzed, and showed robustness that does not fall in the local minima.