• 제목/요약/키워드: Dynamic Service Selection

검색결과 60건 처리시간 0.026초

다계층 네트워크에서 동적 자원 할당 체계 방식 연구 (Dynamic Resource Assignment in the Multi-layer Networks)

  • 강현중;김현철
    • 융합보안논문지
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    • 제13권6호
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    • pp.77-82
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    • 2013
  • 최근 네트워크 사용자의 가치 변화와 이용 패턴을 살펴보면, 단순 웹 정보, 단방향 정보습득의 일방적인 데이터 전달에서, 멀티미디어 활용의 증가, 보안 및 개인화의 요구 증대, 자유로운 이동성에 대한 욕구 증가 등의 변화가 생기고 있다. 이러한 욕구의 변화로 인해 개별적으로 제공되는 각각의 서비스는 점차 융합화된 형태의 통합 서비스로 발전하고, 네트워크 또한 각각의 서비스를 위한 개별 망에서 이용자의 다양한 통합 욕구를 실현시켜 주는 지능형 통합망의 형태로 발전할 것으로 전망되며, 관련한 기술의 핵심이 되는 통신망 제어기술 또한 급속히 발전하고 있다. 본 논문에서는 자원의 효율적 사용은 물론 다중 도메인 (multi-domain)환경에서 다계층 (multi-layer)간의 정보 전달을 최소화하고, 최적의 경로선택을 할 수 있는 방법을 제안하였다. 기존의 경로선택에서 각각의 계층에 대한 정보를 이용하여 경로를 선택한 것에 비하여 다계층 구조상에서 다 계층의 정보를 활용하여 경로선택에 대한 다각화를 통한 최적의 경로선택이 수행되도록 제안하였다.

Selection of Machine Learning Techniques for Network Lifetime Parameters and Synchronization Issues in Wireless Networks

  • Srilakshmi, Nimmagadda;Sangaiah, Arun Kumar
    • Journal of Information Processing Systems
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    • 제15권4호
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    • pp.833-852
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    • 2019
  • In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

융합 서비스 모델 개발 방법론 및 체계 연구 (A Framework for Creating Inter-Industry Service Models in the Convergence Era)

  • 권혁인;류귀진;주희엽;김만진
    • Asia pacific journal of information systems
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    • 제21권1호
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    • pp.81-101
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    • 2011
  • In today's rapidly changing and increasingly competitive business environment, new product development in tune with market trends in a timely manner has been a matter of the utmost concern for all enterprises. Indeed, developing a sustainable new business has been a top priority for not only business enterprises, but also for the government policy makers accountable for the health of Its national economy as well as for decision makers in what type of organizations. Further, for a soft landing of new businesses, building a government-initiated industry base has been claimed to be necessary as a way to effectively boost corporate activities. However, the existing methodology in new service and new product development is not suitable for nurturing industry, because it is mainly focused on the research and development of corporate business activities instead of new product development. The approach for developing new business is based on 'innovation' and 'convergence.' Yet, the convergence among technologies, supplies, businesses and industries is believed to be more effective than innovation alone as a way to gain momentum. Therefore, it has become more important than ever to study a new methodology based on convergence in industrial quality new product development (NPD) and new service development (NDS). In this research, therefore, we reviewed any restrictions in the existing new product and new service development methodology and the existing business model development methodology. In doing so, we conducted industry standard collaboration analysis on a new service model development methodology in the private sector and the public sector. This approach is fundamentally different from the existing one in that ours focuses on new business development under private management. The suggested framework can be categorized into industry level and service level. First, in the industry level, we define new business opportunities In occurrence of convergence between businesses. For this, we analyze the existing industry at the industry level to identify the opportunities in a market and its business attractiveness, based on which the convergence industry is formulated. Also, through the analysis of environment and market opportunity at the industry level. we can trace how different industries are lined to one another so as to extend the result of the study to develop better insights into industry expansion and new industry emergence. After then, in the service level, we elicit the service for the defined new business, which is composed of private service and supporting service for nurturing industry. Private service includes 3steps: plan-design-do; supporting service for nurturing industry has 4 steps: selection-make environment- business preparation-do and see. The existing methodology focuses on mainly securing business competitiveness, building a business model for success, and offering new services based on the core competence of companies. This suggested methodology, on other hand, suggests the necessity of service development, when new business opportunities arise, in relation to the opportunity analysis of supporting service based on the clear understanding of new business supporting infrastructure optimization. Meanwhile, we have performed case studies on the printing and publishing field with the restrict procedure and development system to assure the feasibility and practical application. Even though the printing and publishing industry is considered a typical knowledge convergence industry, it is also known as a low-demand and low-value industry in Korea. For this reason, we apply the new methodology and suggest the direction and the possibility of how the printing and publishing industry can be transformed as a core dynamic force for new growth. Then, we suggest the base composition service for industry promotion(public) and business opportunities for private's profitability(private).

An Adaptable Destination-Based Dissemination Algorithm Using a Publish/Subscribe Model in Vehicular Networks

  • Morales, Mildred Madai Caballeros;Haw, Rim;Cho, Eung-Jun;Hong, Choong-Seon;Lee, Sung-Won
    • Journal of Computing Science and Engineering
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    • 제6권3호
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    • pp.227-242
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    • 2012
  • Vehicular Ad Hoc Networks (VANETs) are highly dynamic and unstable due to the heterogeneous nature of the communications, intermittent links, high mobility and constant changes in network topology. Currently, some of the most important challenges of VANETs are the scalability problem, congestion, unnecessary duplication of data, low delivery rate, communication delay and temporary fragmentation. Many recent studies have focused on a hybrid mechanism to disseminate information implementing the store and forward technique in sparse vehicular networks, as well as clustering techniques to avoid the scalability problem in dense vehicular networks. However, the selection of intermediate nodes in the store and forward technique, the stability of the clusters and the unnecessary duplication of data remain as central challenges. Therefore, we propose an adaptable destination-based dissemination algorithm (DBDA) using the publish/subscribe model. DBDA considers the destination of the vehicles as an important parameter to form the clusters and select the intermediate nodes, contrary to other proposed solutions. Additionally, DBDA implements a publish/subscribe model. This model provides a context-aware service to select the intermediate nodes according to the importance of the message, destination, current location and speed of the vehicles; as a result, it avoids delay, congestion, unnecessary duplications and low delivery rate.

병원약국학(病院藥局學) 대학원전공개설(大學院專攻開設)을 위(爲)한 교육내용(敎育內容)에 관(關)한 연구(硏究) (Establishment of Graduate Education in Hospital Pharmacy)

  • 김종국;이민화
    • Journal of Pharmaceutical Investigation
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    • 제13권1호
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    • pp.23-35
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    • 1983
  • Since the national health insurance was introduced in 1978, the increased utilization of hospitals and the growing importance of pharmaceutical services to hospital patients have made the administration of these services a very complex and specialized responsibility. The pharmaceutical services has always been an essential component of comtemporary hospital care. In the hospital, the pharmaceutical services is the professional department which concerns itself with the evaluation, selection, control and utilization of drugs. The director of this service must be a versatile professional person who can work effectively in a heterogenous society of educated persons. However, graduate education in hospital pharmacy has not been introduced yet in Korea. The necessity of graduate education hospital pharmacy has been discussed in this research. Graduate education in hospital pharmacy emphasizes preparation for assumption of responsibility as the senior hospital pharmacist or the director of pharmaceutical services. Graduates should also be prepared as administrators of a department that must operate with great efficiency. They should be prepared serve as a consultant on drugs for the medical and allied health professional staff, organizing and disseminating a large and dynamic body of information in their interest and to establish professional roles that emphasize procurement, storage, manufacturing, packaging, distribution, control and evaluation of drugs. Senior hospital pharmacist is a teacher charged with responsibility fer formal and informal instruction of other hospital personnel in pharmaceutical sciences. In addition, the graduates have the opportunity to be a researcher dealing with aspect of hospital care and are intensively educated in the professional aspects of hospital pharmacy practices. The curriculum of graduate education in hospital pharmacy should be established detailly and carefully to fit the educational objective.

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MPLS 트래픽 엔지니어링을 위한 간섭 예측 기반의 online 라우팅 알고리듬 (Interference-Prediction based Online Routing Aglorithm for MPLS Traffic Engineering)

  • 이동훈;이성창;예병호
    • 대한전자공학회논문지TC
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    • 제42권12호
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    • pp.9-16
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    • 2005
  • 인터넷 규모의 확장과 트래픽의 증가로 인해 발생하는 망 혼잡 상황을 해결하기 위해 본 연구는 망 제어 기술의 일환책으로서 간섭 예측 정보를 이용한 online 라우팅 알고리듬을 제안한다. 차세대 통합망은 사용자 서비스별 요구 수준에 따라 종단간의 QoS를 보장해야 한다. 이를 위해 동적 대역폭 할당이 효율적으로 이루어져야 하며, 망 전체 성능을 고려한 경로 설정 알고리듬이 필요하다. 본 논문에서 제안한 알고리듬은 현재 라우팅 요청이 요구하는 대역폭의 양이 미래의 잠재적인 트래픽을 간섭하는 정도를 예측하여, 이를 최소화시키는 방안을 제시한다. 망 전체 성능을 최대화하고, 한정된 자원이 낭비되는 것을 방지하기 위해 제안 알고리듬은 요구 대역폭, link 상태정보, 그리고 ingress-egress pair 정보 등을 복합적으로 고려한다. 또한 간섭을 예측하는 것은 동적으로 변화하는 망 상황에서 보장된 대역폭을 제공하게 함으로써 사용자의 요구를 최대한 수용할 수 있게 한다. 본 논문에서는 Internet traffic engineering에 적합한 최적 경로 설정 알고리듬을 제안하기 위해 라우팅 알고리듬이 갖추어야 할 요구 조건과 최근 연구동향을 분석하였으며, QoS 라우팅의 대표적인 연구사례를 분석하였다. 그리고 이를 기반으로 기존의 알고리듬의 문제점을 파악하고 최적의 해결 방안을 제시한다. 개선된 사항은 시뮬레이션을 통해 기존 알고리듬과 비교 및 분석되었다.

시맨틱과 워크플로우 혼합기법에 의한 자동화된 웹 서비스 조합시스템 (Automated Composition System of Web Services by Semantic and Workflow based Hybrid Techniques)

  • 이용주
    • 정보처리학회논문지D
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    • 제14D권2호
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    • pp.265-272
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    • 2007
  • 본 논문에서는 BPEL 기법에 OWL-S 기법을 도입하는 혼합기법을 사용하여 자동화된 웹 서비스 조합시스템을 구현한다. BPEL 기법은 에러 처리나 트랜잭션 관리와 같은 비즈니스 환경에서 요구되는 실질적인 전체 기능을 지원하고 있으나, 주된 단점은 정적 조합 기법으로써 서비스 선택 및 워크플로우 관리가 사전에 수동으로 이루어져야만 한다. 반면에, OWL-S 기법은 자동적인 웹 서비스 발견 및 통합을 실현하기 위해 기계 가독형으로 웹 서비스 기능을 묘사할 수 있는 메카니즘, 즉 온톨로지(ontology)를 사용한다. 이에 따라 호환 가능한 웹 서비스들 간의 동적 통합이 가능하고, 웹 서비스 조합 실행 시에 웹 서비스 발견이 가능하다. 그러나 이러한 기법은 아직 연구 중에 있으며, 실제 적용을 위해서는 BPEL의 상용기법이 요구된다. 본 연구에서는 BPEL4WS와 OWL-S 혼합 시스템인 SemanticBPEL의 구조를 설계하고 웹 서비스 탐색 및 통합 알고리즘을 제안한다. 특히 SemanticBPEL 시스템은 오픈 소스 툴들을 기반으로 구현되었으며, 기존에 개발되어 있는 다양한 BPEL 시스템들과 기능을 비교하여 그 우수성을 보여주고 있다.

빅데이터를 활용한 도시공원 이용행태 특성의 시계열 분석 (A Time Series Analysis of Urban Park Behavior Using Big Data)

  • 우경숙;서주환
    • 한국조경학회지
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    • 제48권1호
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    • pp.35-45
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    • 2020
  • 본 연구는 현대사회에서 도시민의 행태를 지원하는 공간으로 공원에 주목하였다. 현대의 도시공원은 특정한 역할을 하는 공간으로 국한되지 않으며, 공공의 성격을 가지고 있어 이용자의 이용행태에 따라 그 기능·의미가 변화할 수 있다. 또한, 현재 온라인상의 데이터는 방문할 공원의 선택 혹은 공원 이용행태의 결정을 지원하는 단계로 접어들었다. 이에 본 연구는 빅데이터의 자료 기반의 특징인 시계열 분석이 가능하도록 데이터를 수집할 수 있는 최초 년도인 2000년부터 2018년까지 여의도공원·여의도 한강공원과 양재 시민의 숲의 행태 변화를 빅데이터 기법인 텍스트마이닝(Text Mining)과 소셜 네트워크(Social Network;사회연결망)분석을 활용하여 분석하였다. 연구결과의 요약은 다음과 같다. 먼저 시간의 흐름에 따라 주요 이용행태와 행태에 영향을 미치는 요소에 변화가 있었다. 여의도공원·여의도 한강공원의 이용행태는 제 I시기는 '타다'(동적행태), 제 II시기는 '찍다'(정보통신서비스 행태), 제 III시기는 '걷다'(동적행태), 제 IV시기는 '먹다'(에너지원 행태)로 시간의 흐름에 따라 주요 행태가 다양하게 변화하는 모습이고, 양재 시민의 숲은 제 I시기는 '걷다'(동적행태), 제 II시기는 '걷다'(동적행태), 제 III시기는 '걷다'(동적행태), 제 IV시기는 '놀다'(동적행태)로 주로 동적행태 위주의 행태가 나타나는 것으로 나타났다. 주요 행태에 영향을 미치는 요소로 여의도공원·여의도 한강공원은 스포츠 및 레저, 문화·예술, 여가와 관련된 요소가 도출되었고, 양재 시민의 숲은 자연자원 요소가 도출되어 주요 이용행태에 영향을 미치는 요소에 차이가 있었다. 다음으로 대상지의 행태는 시기별로 특정 행태에 집중화되어 있으며, 차후 발생하는 행태를 선택하거나 제약하는 역할을 하는 것으로 나타났다. 이러한 결과는 대상지에 다양한 행태가 일어나지 않을 뿐만 아니라, 공간, 시설 등이 골고루 활용되지 않고 있다는 것을 알 수 있다. 연구결과의 흥미로운 점은 두 공원에서 공통적으로 눈에 띄게 급증한 행태는 에너지원 행태(먹다, 마시다)와 소비행태(사다, 대여하다)이다. 에너지원 행태는 두 공원에서 모두 제 III시기에서 제 IV시기 사이에 10배 이상으로 치솟았으며, 다른 행태와 빈도에서 큰 차이를 보이며 월등히 높았다. 또한, 공원에 방문하는 시민들은 식음료비, 자전거 등의 대여비, 이밖에 행사 참여 등과 관련된 소비의사가 있으며, 공원이 도심 내 휴식공간에서 지역경제 활성화라는 측면에서 본다면 긍정적으로 평가할 수 있을 것이다. 본 연구는 데이터 기법을 활용하여 도시공원 이용행태를 분석하였다는 점과 오늘날 도시공원은 휴식, 산책 등의 역할을 넘어서 시대적인 트렌드를 반영하며, 소비 성향이 나타나는 놀이공간으로 성향이 변화하였다는 결과를 도출하였다는 점에서 큰 의의가 있다. 현대 도시공원에서 일어나는 행태는 양과 내용이 과거와 다르게 변화하고 있다. 그러므로 빅데이터를 통해 수집되는 대규모 집단의 행태를 유형화하고, 이러한 결과를 바탕으로 이루어지는 다학제적인 논의를 통해 오늘날 도시공원을 시민들이 어떻게 이용하고 있는지를 보다 명확하게 이해할 수 있을 것이다.

Challenges and Opportunities of Small Business Management and Start-Ups in India

  • Potluri, Rajasekhara Mouly;Lee, Jung Wan;Khan, Saqib Rasool;Vali, Syed Mastan
    • 유통과학연구
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    • 제10권7호
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    • pp.5-11
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    • 2012
  • The core objective of this research article is to investigate different challenges and opportunities in management as well as start-ups of small businesses in India. The prudence behind this research is to examine various problems in front of the small businesses and to offer vital support and cooperation to overcome those with the support of concerned institutions through consultancy and training programs. The researchers have an intention to make available the research results to the governmental agencies, concerned small business institutions and also to the educational institutions which are continually design plans, programs, policies and strategies to upgrade the managerial and technical dexterities of the small business Indian operators. After thorough revision of relevant literature on small businesses and its management, the researchers used a well structured questionnaire and in-depth personal interviews with 586small business operators selected from manufacturing, trading (retailing and wholesaling), finance, servicing/repair businesses which are located in the coastal districts of Andhra Pradesh in India. The researchers have used convenience sampling and collected data was analyzed with the support of Microsoft Excel and frequency distribution. Noticeably, majority of the small businessmen in India are facing myriad number of challenges both in management and at the time of establishment of their business operations. In particular, 72.47 percent of small businesses operators' have substantiated their strong opinion towards the challenges they are facing particularly finance, marketing and other problems while managing their businesses. The researchers also attempted to get the opinions on problems of the various categories of small businesses while starting their operations. A staggering 68percent of respondents identified the problems related to preparation of business plan, location selection, marketing and other problems like lack of proper credit facilities, skilled manpower, and other infra related problems while setting up of their businesses. On an average, 64.62 and 63.51 percent of small businesses are facing various kinds of problems both at the time of day-to-day management as well as start-up of their businesses respectively. The present research confined with the opinions of only four categories of small business operators particularly from the manufacturing, finance, trading (retailing and wholesaling), and servicing/repair which are continuing their business operations from the nine coastal districts of Andhra Pradesh in India. The present study emphatically provides concrete information required to the business community for identifying an assortment of challenges faced by different small business operators in managing and at the time of their inception. This research paper is first of its kind from this part of the world by offering extensive and credible information required for prospective entrepreneurs in facing the dynamic challenges in managing their business. Furthermore, this research presents invaluable inputs to the stakeholders like all types of governments, policy makers, practitioners, researchers, and educators' about the various impediments faced by the small business community in India.

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Prediction Model of User Physical Activity using Data Characteristics-based Long Short-term Memory Recurrent Neural Networks

  • Kim, Joo-Chang;Chung, Kyungyong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.2060-2077
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    • 2019
  • Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.