云数据中心网络中的先应式碎片整理算法

在云数据中心网络内，虚拟机（Virtual machine， VM）被动态创建和下线，这就导致资源碎片不被后续VM请求所利用。为解决上述问题，以最小化使用服务器数 量为目标的服务器整合技术被提出。虽然这种方法可以在某一时间段内减少资源碎片，但却付出了较大的VM迁移代价。因此本文提出了一种基于预测的先应式碎片 整理算法，在减少无效VM迁移的同时，将资源碎片重新整合为可用的连续资源，从而最大化VM收益。文中对此问题进行了数学定义，随后设计了启发式方法获取近似最优解。仿真结果表明，所提算法能够获取最大收益，并能够大幅度降低VM迁移成本。

Provident Resource Defragmentation Algorithm for Cloud Data Center Network

In a cloud data center network, virtual machines (VMs) can be dynamically created and terminated, causing the fact that fragmented resources cannot be further utilized. To solve the problem, the server consolidation is proposed to minimize the number of active servers. Although the approach can reduce resource fragmentation at particular time, it may be over aggressive at the price of too frequent VM migration. Therefore, a novel provident resource defragmentation algorithm is proposed to reduce the unnecessary VM migration and maxmize the profit by re-consolidating fragments into available continuous resources. An optimization problem is formulated, and a heuristic method for obtaining near-optimal results is developed. Extensive numerical results confirm that the framework provides the highest profit and significantly reduces the VM migration cost.