Learn More
The placement of virtual machines (VMs) on a cluster of physical machines (PMs) is a primary task in clouds. We can benefit a lot from appropriate placement policy, e.g. cost saving. In this paper, we raise a continuous virtual machine placement problem and propose an on-line algorithm to reduce the power consumption of clouds. Generic methods which deal(More)
Cloud computing is a newly emerging reliable and scalable paradigm in which customers pay for cloud resources they use on demand. However, current auto-scaling mechanisms in cloud lack the critical self-adaption policy which helps application providers decide on when and how to reallocate resources. Furthermore, virtualization techniques can not ensure an(More)
High availability, reliability and scalability are basic prerequisites for cloud applications. Due to dynamically varying workloads, it's necessary to provide resource guarantees to cloud applications for meeting QoS requirements. However, it's not trivial to generate a precise scalability policy for multi-tiers cloud applications to adapt to dynamically(More)
With the rapid development of virtualization techniques, modern data centers move into a new era of cloud in recent years. Despite numerous advantages such as high resource utilization and rapid service scalability, current virtualization techniques don't guarantee perfect performance isolation among virtual machines sharing the physical machine, which may(More)
Iterative learning control is a control technique used for the tracking of a finite duration trajectory. Iterative learning control (ILC) with focus on speed of tracking specific points and tracking error on these points is analyzed in this paper. A technique is introduced which employs the receding horizon optimization to track the points along with the(More)
  • 1