Pages that link to "Item:Q1701633"
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The following pages link to Design and theoretical analysis of virtual machine placement algorithm based on peak workload characteristics (Q1701633):
Displaying 12 items.
- A multi-objective ant colony system algorithm for virtual machine placement in cloud computing (Q394732) (← links)
- Using a vision cognitive algorithm to schedule virtual machines (Q747400) (← links)
- A comparative performance analysis of evolutionary algorithms on \(k\)-median and facility location problems (Q1626279) (← links)
- Research on QoS service composition based on coevolutionary genetic algorithm (Q1626285) (← links)
- Optimal energy-efficient placement of virtual machines with divisible sizes (Q1653041) (← links)
- Scheduling method of data-intensive applications in cloud computing environments (Q1666118) (← links)
- Virtual machine placement for minimizing connection cost in data center networks (Q1751257) (← links)
- An optimal resource allocation scheme for virtual machine placement of deploying enterprise applications into the cloud (Q2130016) (← links)
- Hybrid algorithms for placement of virtual machines across geo-separated data centers (Q2331587) (← links)
- Multi-objective temporal bin packing problem: an application in cloud computing (Q2664301) (← links)
- An Inhomogeneous Hidden Markov Model for Efficient Virtual Machine Placement in Cloud Computing Environments (Q4687618) (← links)
- (Q5127846) (← links)
