Adaptive quality of service management for enterprise services
Adaptive quality of service management for enterprise services
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DOI：
10.1145/1326561.1326569
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发表时间：
2008-03
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影响因子：
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通讯作者：
D. Gmach;Stefan Krompass;A. Scholz;Martin Wimmer;A. Kemper
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文献类型：
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作者：
D. Gmach;Stefan Krompass;A. Scholz;Martin Wimmer;A. Kemper
过去，企业资源规划系统被设计为在中央主机上运行的单一软件系统。今天，这些系统被（重新）设计为分布在整个可用计算基础设施中的企业服务存储库。这些面向服务的体系结构（SOA）需要先进的自动和自适应管理概念，以便在例如可用性、响应性和吞吐量方面实现高质量的服务水平。自适应管理必须将服务实例分配给计算资源，使资源分配适应不可预见的负载波动，并智能地调度各个请求以保证协商的服务水平协议（SLA）。我们的AutoGlobe平台提供了这样一种全面的自适应服务管理，包括-基于自动检测的服务利用模式的静态服务到服务器分配，-基于模糊控制器的自适应服务管理，该模糊控制器通过自动启动例如服务迁移、服务复制来补救异常情况（向外扩展），以及-根据当前服务级别一致性程度对请求进行优先级排序的各个服务请求的自适应调度。所有三个互补的控制组件进行了详细的描述，并通过实际的业务应用场景分析其有效性。
In the past, enterprise resource planning systems were designed as monolithic software systems running on centralized mainframes. Today, these systems are (re-)designed as a repository of enterprise services that are distributed throughout the available computing infrastructure. These service oriented architectures (SOAs) require advanced automatic and adaptive management concepts in order to achieve a high quality of service level in terms of, for example, availability, responsiveness, and throughput. The adaptive management has to allocate service instances to computing resources, adapt the resource allocation to unforeseen load fluctuations, and intelligently schedule individual requests to guarantee negotiated service level agreements (SLAs). Our AutoGlobe platform provides such a comprehensive adaptive service management comprising —static service-to-server allocation based on automatically detected service utilization patterns, —adaptive service management based on a fuzzy controller that remedies exceptional situations by automatically initiating, for example, service migration, service replication (scale-out), and —adaptive scheduling of individual service requests that prioritizes requests depending on the current degree of service level conformance. All three complementary control components are described in detail, and their effectiveness is analyzed by means of realistic business application scenarios.