• 제목/요약/키워드: Growth Algorithm

검색결과 586건 처리시간 0.023초

A Dynamic Placement Mechanism of Service Function Chaining Based on Software-defined Networking

  • Liu, Yicen;Lu, Yu;Chen, Xingkai;Li, Xi;Qiao, Wenxin;Chen, Liyun
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제12권10호
    • /
    • pp.4640-4661
    • /
    • 2018
  • To cope with the explosive growth of Internet services, Service Function Chaining (SFC) based on Software-defined Networking (SDN) is an emerging and promising technology that has been suggested to meet this challenge. Determining the placement of Virtual Network Functions (VNFs) and routing paths that optimize the network utilization and resource consumption is a challenging problem, particularly without violating service level agreements (SLAs). This problem is called the optimal SFC placement problem and an Integer Linear Programming (ILP) formulation is provided. A greedy heuristic solution is also provided based on an improved two-step mapping algorithm. The obtained experimental results show that the proposed algorithm can automatically place VNFs at the optimal locations and find the optimal routing paths for each online request. This algorithm can increase the average request acceptance rate by about 17.6% and provide more than 20-fold reduction of the computational complexity compared to the Greedy algorithm. The feasibility of this approach is demonstrated via NetFPGA-10G prototype implementation.

An Encrypted Speech Retrieval Scheme Based on Long Short-Term Memory Neural Network and Deep Hashing

  • Zhang, Qiu-yu;Li, Yu-zhou;Hu, Ying-jie
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제14권6호
    • /
    • pp.2612-2633
    • /
    • 2020
  • Due to the explosive growth of multimedia speech data, how to protect the privacy of speech data and how to efficiently retrieve speech data have become a hot spot for researchers in recent years. In this paper, we proposed an encrypted speech retrieval scheme based on long short-term memory (LSTM) neural network and deep hashing. This scheme not only achieves efficient retrieval of massive speech in cloud environment, but also effectively avoids the risk of sensitive information leakage. Firstly, a novel speech encryption algorithm based on 4D quadratic autonomous hyperchaotic system is proposed to realize the privacy and security of speech data in the cloud. Secondly, the integrated LSTM network model and deep hashing algorithm are used to extract high-level features of speech data. It is used to solve the high dimensional and temporality problems of speech data, and increase the retrieval efficiency and retrieval accuracy of the proposed scheme. Finally, the normalized Hamming distance algorithm is used to achieve matching. Compared with the existing algorithms, the proposed scheme has good discrimination and robustness and it has high recall, precision and retrieval efficiency under various content preserving operations. Meanwhile, the proposed speech encryption algorithm has high key space and can effectively resist exhaustive attacks.

Compression and Enhancement of Medical Images Using Opposition Based Harmony Search Algorithm

  • Haridoss, Rekha;Punniyakodi, Samundiswary
    • Journal of Information Processing Systems
    • /
    • 제15권2호
    • /
    • pp.288-304
    • /
    • 2019
  • The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

유역분할 알고리즘을 이용한 결정립 크기 측정 (Grain size measurement based on marked watershed algorithm)

  • 김범수;윤상두;권재성;최성웅;노정필;양정현
    • 한국표면공학회지
    • /
    • 제55권6호
    • /
    • pp.403-407
    • /
    • 2022
  • Grain size of material is important factor in evaluating mechanical properties. Methods for grain size determination are described in ASTM grain size standards. However, conventional method require pretreatment of the surface to clarify grain boundaries. In this study, the grain size from the surface image obtained from scanning electron microscope was measured using the watershed algorithm, which is a region-based method among image segmentation techniques. The shapes of the crystals are similar to each other, but the size and growth height are different. In addition, crystal grains are adjacent to each other, so it is very similar to the shape image of the topography. Therefore, grain boundaries can be efficiently detected using the Watershed algorithm.

A cache placement algorithm based on comprehensive utility in big data multi-access edge computing

  • Liu, Yanpei;Huang, Wei;Han, Li;Wang, Liping
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제15권11호
    • /
    • pp.3892-3912
    • /
    • 2021
  • The recent rapid growth of mobile network traffic places multi-access edge computing in an important position to reduce network load and improve network capacity and service quality. Contrasting with traditional mobile cloud computing, multi-access edge computing includes a base station cooperative cache layer and user cooperative cache layer. Selecting the most appropriate cache content according to actual needs and determining the most appropriate location to optimize the cache performance have emerged as serious issues in multi-access edge computing that must be solved urgently. For this reason, a cache placement algorithm based on comprehensive utility in big data multi-access edge computing (CPBCU) is proposed in this work. Firstly, the cache value generated by cache placement is calculated using the cache capacity, data popularity, and node replacement rate. Secondly, the cache placement problem is then modeled according to the cache value, data object acquisition, and replacement cost. The cache placement model is then transformed into a combinatorial optimization problem and the cache objects are placed on the appropriate data nodes using tabu search algorithm. Finally, to verify the feasibility and effectiveness of the algorithm, a multi-access edge computing experimental environment is built. Experimental results show that CPBCU provides a significant improvement in cache service rate, data response time, and replacement number compared with other cache placement algorithms.

APMDI-CF: An Effective and Efficient Recommendation Algorithm for Online Users

  • Ya-Jun Leng;Zhi Wang;Dan Peng;Huan Zhang
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제17권11호
    • /
    • pp.3050-3063
    • /
    • 2023
  • Recommendation systems provide personalized products or services to online users by mining their past preferences. Collaborative filtering is a popular recommendation technique because it is easy to implement. However, with the rapid growth of the number of users in recommendation systems, collaborative filtering suffers from serious scalability and sparsity problems. To address these problems, a novel collaborative filtering recommendation algorithm is proposed. The proposed algorithm partitions the users using affinity propagation clustering, and searches for k nearest neighbors in the partition where active user belongs, which can reduce the range of searching and improve real-time performance. When predicting the ratings of active user's unrated items, mean deviation method is used to impute values for neighbors' missing ratings, thus the sparsity can be decreased and the recommendation quality can be ensured. Experiments based on two different datasets show that the proposed algorithm is excellent both in terms of real-time performance and recommendation quality.

A Method to Measure the Self-Supplied News Volumes of Internet Newspaper Company

  • Kim, Dong-Joo;Lee, Won Joo
    • 한국컴퓨터정보학회논문지
    • /
    • 제20권10호
    • /
    • pp.99-105
    • /
    • 2015
  • The growth of internet infrastructure and a tremendous increment of internet users lead actively to found internet newspaper publishing companies, which are able to dig up and publish own news articles. In disregard of these quantitative growth of internet newspaper companies, the qualitative growth of them doesn't coincide with the quantitative growth. Therefore, to require social responsibility and to build healthy media environment, Korean government has put in force registration system of internet newspaper company. According to this system, internet newspaper companies have to produce at the inside over 30 percent of weekly publications, and this requisite increases the needs of its verification. This paper investigates technologies to measure the self-supplied news volumes of internet newspaper company, examines validity of them, and presents appropriate method to measure. To compare huge amount of news articles rapidly, the presented method is based on the modified edit-distance, which reflects human cognition of word and empirical information related with it. To prove correctness of our presented method, we show experimental results for some real internet news articles.

항공기 주익구조물의 피로균열 진전 해석 및 실험을 위한 응력 스펙트럼 알고리즘 개발 (Stress Spectrum Algorithm Development for Fatigue Crack Growth Analysis and Experiment for Aircraft Wing Structure)

  • 천영철;장윤정;정태진;강기원
    • 대한기계학회논문집A
    • /
    • 제39권12호
    • /
    • pp.1281-1286
    • /
    • 2015
  • 항공기는 다양한 임무를 수행함으로써 장기간 운영 시 비행시간 누적으로 인해 피로균열을 발생시킬 수 있다. 주익 구조물에 균열이 발생하면 수명단축 등 여러 문제점들이 발생할 수 있다. 이의 해결을 위해 피로임계위치(Fatigue critical location, FCL)에서의 균열진전 해석이 필요하다. 균열진전 해석을 위해서는 장시간의 응력 스펙트럼이 필요한데 실제 항공기에서 필요한 만큼의 데이터를 얻는 것은 막대한 시간과 비이 소요된다. 본 논문에서는 SwRI(South West Research Institute)보고서에 제시되어있는 임무별 단시간 하중배수 자료를 바탕으로 Peak-Valley Cycle Counting 을 진행하여 장시간의 응력 스펙트럼을 산출하는 알고리즘을 개발하였다.

세포막 추출과 역추적 알고리즘 기반의 HeLa 세포 이미지 자동 셀 카운팅 기법 (Automated Cell Counting Method for HeLa Cells Image based on Cell Membrane Extraction and Back-tracking Algorithm)

  • 경민영;박정호;김명구;신상모;이현빈
    • 정보과학회 논문지
    • /
    • 제42권10호
    • /
    • pp.1239-1246
    • /
    • 2015
  • 셀 카운팅은 세포의 성장을 분석하는 방법으로써 생물학연구에서 가장 많이 사용된다. 최근까지도 다양한 자동 셀 카운팅 기법이 제안되고 있지만 암세포와 같이 분열 속도가 빠르고 군집하려는 성질을 갖는 세포들은 분리 및 검출이 쉽지 않아 세포 이미지 분석을 통하여 셀 카운팅의 신뢰도를 높이기가 어렵다. 본 논문에서는 암 연구의 연구재료로 매우 보편적으로 사용되는 HeLa 세포 이미지 분석을 이용한 자동 셀 카운팅 방법을 제시한다. 세포막 추출 기반의 세포 분할 알고리즘을 통하여 세포의 형태적 상황을 구분하고, 세포 간 경계가 희미한 세포군집 내의 세포 분할을 위하여 역추적 알고리즘을 사용함으로써 셀 카운팅 정확도를 높인다. 실험을 통하여 제안하는 세포 분할 알고리즘이 기존의 세포 분할 알고리즘에 비해 정확함을 입증하였고, 결과적으로 매우 높은 자동 셀 카운팅 정확도를 얻을 수 있음을 확인하였다.

기계학습 기반의 메타모델을 활용한 ZnO 바리스터 소결 공정 최적화 연구 (Sintering process optimization of ZnO varistor materials by machine learning based metamodel)

  • 김보열;서가원;하만진;홍연우;정찬엽
    • 한국결정성장학회지
    • /
    • 제31권6호
    • /
    • pp.258-263
    • /
    • 2021
  • ZnO 바리스터는 다결정구조를 가지는 반도체 소자로 결정립과 입계의 미세구조 제어를 통해 비선형적인 전류/전압 특성을 가지기 때문에 서지(surge)전압으로부터 회로를 보호하는 역할을 한다. 이러한 ZnO 바리스터에서 원하는 전기적 물성을 얻기 위해서는 소결 공정에서 미세구조의 제어가 중요하다. 따라서 소결 공정에서 중요한 변수들과 소결체의 전기적 물성인 유전율로 구성된 데이터셋을 정의한 후 실험계획법 기반으로 데이터를 수집했다. 수집된 실험데이터셋을 기계학습 알고리즘에 학습하여 메타모델을 개발했고, 개발된 메타모델에 수치기반 최적화 알고리즘인 HMA(Hybrid Metaheuristic Algorithm)를 적용하여 최대 유전율을 가질 수 있는 공정조건을 도출했다. 이러한 메타모델 기반의 최적화를 다변수 시스템인 세라믹공정에 적용한다면 최소한의 실험만으로 최적 공정조건 탐색이 가능할 것으로 판단된다.