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Resource scheduling has been one of the key challenges facing both academia and industry ever since the inauguration of cloud computing. Most of the existing research and practices have been focused on the maximization of the profits of cloud providers, whereas attention to the real needs of cloud users has largely been neglected. In this research, we propose a resource scheduling mechanism empowered...
With the rapid development and popularity of cloud computing technology, more and more Collaborative Virtual Environment (CVE) systems are migrated to cloud computing environment to improve the effectiveness of resource usage. Virtual Machine (VM) placement in cloud data center is a key issue of providing high-efficient cloud platform for CVE system. However, most existing VM placement algorithms...
With the explosion of data in the past decade, big data is becoming a research hotspot in the information field. Many cloud-based distributed data processing platforms have been proposed to provide efficient and cost effective solutions for big data query processing, such as Hadoop, Hive, Pig, etc. However, most of the current research works are focus on improving the performance of query processing...
Scheduling mechanism in cloud computing environment concerns more about the needs of users due to the commercial purpose of cloud computing. In response to this user-oriented feature, an Adaptive Resource Scheduling Mechanism based on User Behavior Feedback(ARSM-UBF) is developed to schedule cloud resources from the perspective of users. In ARSM-UBF, information collected from scheduling interaction...
In service-oriented environments (e.g. Cloud Computing or Utility Computing), automated service discovery is crucial to enable self-organizing technical components that are able to discover and consume services autonomously. To this end, precise and robust service discovery algorithms are desirable. In this paper, we propose an approach combining both syntactic and semantic search to increase accuracy...
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