• Title/Summary/Keyword: Autonomic computing

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A Hierarchical Context Dissemination Framework for Managing Federated Clouds

  • Famaey, Jeroen;Latre, Steven;Strassner, John;Turck, Filip De
    • Journal of Communications and Networks
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    • v.13 no.6
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    • pp.567-582
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    • 2011
  • The growing popularity of the Internet has caused the size and complexity of communications and computing systems to greatly increase in recent years. To alleviate this increased management complexity, novel autonomic management architectures have emerged, in which many automated components manage the network's resources in a distributed fashion. However, in order to achieve effective collaboration between these management components, they need to be able to efficiently exchange information in a timely fashion. In this article, we propose a context dissemination framework that addresses this problem. To achieve scalability, the management components are structured in a hierarchy. The framework facilitates the aggregation and translation of information as it is propagated through the hierarchy. Additionally, by way of semantics, context is filtered based on meaning and is disseminated intelligently according to dynamically changing context requirements. This significantly reduces the exchange of superfluous context and thus further increases scalability. The large size of modern federated cloud computing infrastructures, makes the presented context dissemination framework ideally suited to improve their management efficiency and scalability. The specific context requirements for the management of a cloud data center are identified, and our context dissemination approach is applied to it. Additionally, an extensive evaluation of the framework in a large-scale cloud data center scenario was performed in order to characterize the benefits of our approach, in terms of scalability and reasoning time.

A Study on Status Definition and Diagnostic Algorithm for Autonomic Control of Manufacturing Facilities (제조설비 자율제어를 위한 상태 정의 및 진단 알고리즘에 대한 연구)

  • Ko, Dongbeom;Park, Jeongmin
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.2
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    • pp.227-234
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    • 2020
  • This paper introduces the state definition and diagnostic algorithm for autonomic control of manufacturing facilities. Smart factory systems through cyber-physical systems and digital twin technology are increasing the productivity and stability of existing manufacturing plants, which has become an issue recently. A Smart factory system is one of the key technologies that make up a smart factory system, to improve productivity, enable workers to make better decisions, and to control abnormal process flows. However, performing an autonomic control process based on large number of integrated plat data requires significant advance work. Therefore, in this paper, we define an abstracted facility state for manufacturing facility autonomic control and propose an algorithm to diagnose the current state. This makes the autonomic control process simpler by autonomic control based on the facility status rather then integrated facility data.

Affective Computing Among Individuals in Deep Learning

  • Kim, Seong-Kyu (Steve)
    • Journal of Multimedia Information System
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    • v.7 no.2
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    • pp.115-124
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    • 2020
  • This paper is a study of deep learning among artificial intelligence technology which has been developing many technologies recently. Especially, I am talking about emotional computing that has been mentioned a lot recently during deep learning. Emotional computing, in other words, is a passive concept that is dominated by people who scientifically analyze human sensibilities and reflect them in product development or system design, and a more active concept that studies how devices and systems understand humans and communicate with people in different modes. This emotional signal extraction, sensitivity, and psychology recognition technology is defined as a technology to process, analyze, and recognize psycho-sensitivity based on micro-small, hyper-sensor technology, and sensitive signals and information that can be sensed by the active movement of the autonomic nervous system caused by human emotional changes in everyday life. Chapter 1 talks about overview and Chapter 2 shows related research. Chapter 3 shows the problems and models of real emotional computing and Chapter 4 shows this paper as a conclusion.

A Self-optimizing Mechanism of Location Aware Systems for Ubiquitous Computing (유비쿼터스 컴퓨팅을 위한 위치 감지 시스템의 자가 치적화 기법)

  • Choi, Ho-Young;Choi, Chang-Yeol;Kim, Sung-Soo
    • The KIPS Transactions:PartA
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    • v.12A no.4 s.94
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    • pp.273-280
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    • 2005
  • The mobility or highly interconnected and communicating devices and users has implications for the QoS in a ubiquitous computing environment. Therefore, it is important for location aware systems to detect location of mobile object correctly and Provide high quality services in ubiquitous environment. However, it is not easy that location aware systems offer highly reliable QoS to users because process strategies of location aware systems are limited by the capability according to the applied detection target objects. In this paper, we design an autonomic architecture which analyzes the location aware system condition and autonomously chooses the best appropriate process strategy. We also have simulated the Proposed architecture in order to verify its performance. The test results show us that the architecture using self-optimizing mechanism provides higher QoS to users in variable bandwidth.

An Autonomic Self-management Mechanism for High-available Home Service Networked System (고가용성 홈 서비스 네트워크 시스템을 위한 오토노믹 자가 관리 메커니즘)

  • Choi, Chang-Yeol;Kim, Sung-Soo
    • Journal of KIISE:Computing Practices and Letters
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    • v.13 no.2
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    • pp.119-130
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    • 2007
  • Home service networked systems require a high-availability service with a proactive and practical fault management. However, as the system complexity grows, it is not easy to meet the requirement. Moreover, user may want to pay no attention to a sequence of complex or nervous maintenance jobs for system fault managements. Therefore, the home service networked systems must have self & remote fault management capability with a minimal human intervention for meeting high-availability requirement of the integrated systems that consist of the networked appliances or devices. In this paper, we present an autonomic healing utility equipped with a remote self-managing mechanism in order to both increase the availability of home service networked systems and decrease the maintenance cost.

Autonomic Self Healing-Based Load Assessment for Load Division in OKKAM Backbone Cluster

  • Chaudhry, Junaid Ahsenali
    • Journal of Information Processing Systems
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    • v.5 no.2
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    • pp.69-76
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    • 2009
  • Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.

An Autonomic -Interleaving Registry Overlay Network for Efficient Ubiquities Web Services Discovery Service

  • Ragab, Khaled
    • Journal of Information Processing Systems
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    • v.4 no.2
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    • pp.53-60
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    • 2008
  • The Web Services infrastructure is a distributed computing environment for service-sharing. Mechanisms for Web services Discovery proposed so far have assumed a centralized and peer-to-peer (P2P) registry. A discovery service with centralized architecture, such as UDDI, restricts the scalability of this environment, induces performance bottleneck and may result in single points of failure. A discovery service with P2P architecture enables a scalable and an efficient ubiquities web service discovery service that needs to be run in self-organized fashions. In this paper, we propose an autonomic -interleaving Registry Overlay Network (RgON) that enables web-services' providers/consumers to publish/discover services' advertisements, WSDL documents. The RgON, doubtless empowers consumers to discover web services associated with these advertisements within constant D logical hops over constant K physical hops with reasonable storage and bandwidth utilization as shown through simulation.

An Autonomic User-Dependent Weighting Method to Improve Efficiency of Recommendation (추천 성능 향상을 위한 사용자별 가중치 자동 설정 기법)

  • Lee, Seong-Jin;Lee, Youn-Jeong;Lee, Soo-Won
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.11b
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    • pp.781-783
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    • 2005
  • 추천 기술이란 과도하게 제공되는 정보를 여과하여 사용자에게 필요한 정보만을 제공해 주는 것으로 대표적으로는 협력적 여과가 있다. 그러나 협력적 여과는 희소성 문제와 확장성에 취약점을 보이고 있어 최근 이를 극복하기 위한 내용 기반 추천 기법에 관한 연구가 활발히 이루어지고 있다. 내용 기반의 추천 기법에서 효율적인 추천이 이루어지기 위해서는 각 요소별 가중치를 어떻게 설정할 것인가가 매우 중요하다. 기존의 연구에서는 요소별 가중치를 다양한 실험에 의해 결정하고 이를 모든 사용자에게 동일하게 적용하는 방식을 취하고 있다. 그러나 사용자마다 콘텐츠 선택 기준과 요인이 다를 수 밖에 없으므로 이러한 방식은 사용자의 선호 정보를 효과적으로 반영할 수 없다. 따라서 본 논문에서는 사용자의 선호 정보 분석과 함께 각 요소별 가중치를 사용자별로 자동으로 설정하여 보다 효과적인 추천이 이루어질 수 있는 기법을 제안한다.

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A Design and Implementation of Context-Adaptive Self-Configuration System in Ubiquitous Computing Environment (유비쿼터스 컴퓨팅 환경에서 상황적응형 자가구성 시스템의 설계와 구현)

  • 이승화;오제환;이은석
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2004.11a
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    • pp.233-241
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    • 2004
  • 본 논문에서는 분산된 관리대상의 시스템자원과 사용자정보, 사용패턴을 Context로 수집하여, 구성(Configuration)을 수행하는 적응형 자가관리시스템을 제안한다. 본 시스템은 기존에 수동으로 이루어지던 Configuration 작업들 (Install, Reconfiguration, Update)을 자율적으로 수행하여, 사용자의 시스템관리에 대한 부담을 줄여주게 되며, 많은 비용과 오류를 감소시켜준다. 본 시스템은 수집된 Context 정보를 기반으로 사용자의 환경에 맞는 구성요소를 선택하여 설치하게 되며, 사용자의 기존 애플리케이션의 환경설정과 사용패턴을 기반으로, 보다 개인화된 설정을 해준다. 설정 이후에는 사용자의 행동을 암시적 피드백으로 받아, 이를 학습하고 유사한 상황이 다시 발생할 경우, 이를 다음 행동에 반영한다. 그리고 기존에 중앙서버로부터 일률적으로 관련파일을 전송하고 관리하는 중앙집중배포방식의 여러 문제점에 대응하기 위해 Peer-to-Peer 방식으로 파일을 카피하고, 이를 통해 중앙서버의 과부하를 줄이는 동시에 빠른 파일의 배포가 가능하도록 하였다. 본 시스템의 평가를 위해 프로토타입을 구현하여, 기존 수동 Configuration작업, MS-IBM과 같은 관련시스템과의 비교를 수행하였으며, 기능적 측면과 작업에 소요되는 시간에 대한 비교결과를 통해 본 시스템의 유효성을 증명하였다.

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