Cloud computing has recently emerged as an important service to manage applications efficiently over the Internet. Various cloud providers offer pay per use cloud services that requires Quality of Service (QoS) management to efficiently monitor and measure the delivered services through Internet of Things (IoT) and thus needs to follow Service Level Agreements (SLAs). However, providing dedicated cloud services that ensure user's dynamic QoS requirements by avoiding SLA violations is a big challenge in cloud computing. As dynamism, heterogeneity and complexity of cloud environment is increasing rapidly, it makes cloud systems insecure and unmanageable. To overcome these problems, cloud systems require self-management of services. Therefore, there is a need to develop a resource management technique that automatically manages QoS requirements of cloud users thus helping the cloud providers in achieving the SLAs and avoiding SLA violations. In this paper, we present SLA-aware autonomic resource management technique called STAR which mainly focuses on reducing SLA violation rate for the efficient delivery of cloud services. The performance of the proposed technique has been evaluated through cloud environment. The experimental results demonstrate that STAR is efficient in reducing SLA violation rate and in optimizing other QoS parameters which effect efficient cloud service delivery.

中文翻译：

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STAR：云资源的SLA感知自主管理

云计算最近已成为有效管理 Internet 应用程序的重要服务。各种云提供商提供按使用付费的云服务，需要服务质量 (QoS) 管理来有效地监控和衡量通过物联网 (IoT) 交付的服务，因此需要遵循服务水平协议 (SLA)。然而，提供专用的云服务，通过避免违反 SLA 来确保用户的动态 QoS 要求是云计算中的一大挑战。随着云环境的动态性、异构性和复杂性的迅速增加，使得云系统变得不安全和难以管理。为了克服这些问题，云系统需要对服务进行自我管理。所以，需要开发一种资源管理技术，自动管理云用户的 QoS 要求，从而帮助云提供商实现 SLA 并避免违反 SLA。在本文中，我们提出了一种称为 STAR 的 SLA 感知自主资源管理技术，主要侧重于降低 SLA 违规率，以实现云服务的高效交付。已通过云环境评估了所提出技术的性能。实验结果表明，STAR 在降低 SLA 违规率和优化影响高效云服务交付的其他 QoS 参数方面是有效的。我们提出了一种称为 STAR 的 SLA 感知自主资源管理技术，主要侧重于降低 SLA 违规率，以实现云服务的高效交付。已通过云环境评估了所提出技术的性能。实验结果表明，STAR 在降低 SLA 违规率和优化影响高效云服务交付的其他 QoS 参数方面是有效的。我们提出了一种称为 STAR 的 SLA 感知自主资源管理技术，主要侧重于降低 SLA 违规率，以实现云服务的高效交付。已通过云环境评估了所提出技术的性能。实验结果表明，STAR 在降低 SLA 违规率和优化影响高效云服务交付的其他 QoS 参数方面是有效的。