ﻻ يوجد ملخص باللغة العربية
In virtualized data centers, consolidation of Virtual Machines (VMs) on minimizing the number of total physical machines (PMs) has been recognized as a very efficient approach. This paper considers the energy-efficient consolidation of VMs in a Cloud Data center. Concentrating on CPU-intensive applications, the objective is to schedule all requests non-preemptively, subjecting to constraints of PM capacities and running time interval spans, such that the total energy consumption of all PMs is minimized (called MinTE for abbreviation). The MinTE problem is NP-complete in general. We propose a self-adaptive approached called SAVE. The approach makes decisions of the assignment and migration of VMs by probabilistic processes and is based exclusively on local information, therefore it is very simple to implement. Both simulation and real environment test show that our proposed method SAVE can reduce energy consumption about 30% against VMWare DRS and 10-20% against EcoCloud on average.
We introduce a novel technique for neural point cloud consolidation which learns from only the input point cloud. Unlike other point upsampling methods which analyze shapes via local patches, in this work, we learn from global subsets. We repeatedly
A common paradigm for scientific computing is distributed message-passing systems, and a common approach to these systems is to implement them across clusters of high-performance workstations. As multi-core architectures become increasingly mainstrea
The traditional virtual machine building and and deployment process is centered around the virtual machine hard disk image. The packages comprising the VM operating system are carefully selected, hard disk images are built for a variety of different
Container technique is gaining increasing attention in recent years and has become an alternative to traditional virtual machines. Some of the primary motivations for the enterprise to adopt the container technology include its convenience to encapsu
Vector clock algorithms are basic wait-free building blocks that facilitate causal ordering of events. As wait-free algorithms, they are guaranteed to complete their operations within a finite number of steps. Stabilizing algorithms allow the system