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RISS 인기검색어
- 검색키워드
- 저자 : Steven Latré (검색결과 3 건)
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Algorithms for Network-Aware Application Component Placement for Cloud Resource Allocation
Maryam Barshan,Hendrik Moens,Steven Latré,Bruno Volckaert,Filip De Turck 한국통신학회 2017 Journal of communications and networks Vol.19 No.5
Due to the soaring popularity of cloud-based services overthe last years, the size and the complexity of cloud environmentshas been growing quickly. In the context of cloud systems, mappinga number of application components to a set of physical serversand assigning cloud resources to those components is challenging. Traditional resource allocation systems which rely on a centralizedmanagement paradigm suffer from scalability issues, makingthem inappropriate for large-scale cloud environments. Therefore,there is a need for providing new management solutions that scalewell to large size cloud systems. In this article, we present optimaland heuristic solutions for network-aware placement of multicomponentapplications with differing component characteristics. The optimal integer linear programming (ILP)-based solution minimizesthe application rejection rate and the cost of mapping whilerespecting application component requirements and physical networklimitations. As the execution time of the optimal model scalesexponentially, we also offer scalable heuristic solutions for centralizedand hierarchical application placement, which are thoroughlyexplained and evaluated and compared to the optimal solution. Our evaluations show that while the proposed centralized heuristicis near-optimal, the hierarchical approach is much faster and offershigher scalability compared to a centralized approach, e.g., mapping2.7 million application components onto 512k servers. Moreover,the percentage of servers used and fully placed applicationsremain close to that of the centralized and optimal solutions.
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A Hierarchical Context Dissemination Framework for Managing Federated Clouds
Famaey, Jeroen,Latre, Steven,Strassner, John,Turck, Filip De The Korea Institute of Information and Commucation 2011 Journal of communications and networks Vol.13 No.6
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.
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A Hierarchical Context Dissemination Framework for Managing Federated Clouds
Jeroen Famaey,Steven Latr´e,John Strassner,Filip De Turck 한국통신학회 2011 Journal of communications and networks Vol.13 No.6
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.
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