1 - 6 of 6 Chapters
[Cloud computing lends itself to the processing of large data volumes and time-varying computational demands. Cloud data centers involve substantial computational resources, feature inherently flexible deployment, and deliver significant economic benefit—provided the resources are well utilized...
[In this chapter, we introduce a solution to the problem of cost-effective VM allocation and reallocation. Unlike traditional solutions, which typically reallocate VMs based on a greedy algorithm such as First Fit (each VM is allocated to the first server in which it will fit), Best Fit (each VM...
[In this chapter, we introduce the StarCube framework. Its core concept is the dynamic and cost-effective partitioning of a hierarchical data center network into several star networks and the provisioning of each service with a star network that is consistently independent from other services.]
[Based on the transformation of the fat-tree structure, the problem of allocating servers in hierarchical data center networks can be formulated as an integer programming problem. The objective is to maximize resource efficiency and to minimize reallocation cost while satisfying the topology...
[The simulation setup for evaluating Adaptive Fit is as follows. The number of VMs in the system varies from 50 to 650. Let the resource requirement for each VM vary in [0, 1] units; the capacity of each server is fixed at one. The requirement of each VM is assigned independently and randomly,...
[Operating cloud services using the minimum amount of cloud resources is a challenge. The challenge comes from multiple issues, such as the network requirements of intra-service communication, the dynamics of service demand, significant overhead of virtual machine migration, multi-tenant...
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