Abstract
High-energy consumption in data centers has become a critical issue. The dynamic server consolidation has significant effects on saving energy of a data center. An effective way to consolidate virtual machines is to migrate virtual machines in real time so that some light load physical machines can be turned off or switched to low-power mode. The present challenge is to reduce the energy consumption of cloud data centers. In this paper, for the first time, a server consolidation algorithm based on the culture multiple-ant-colony algorithm was proposed for dynamic execution of virtual machine migration, thus reducing the energy consumption of cloud data centers. The server consolidation algorithm based on the culture multiple-ant-colony algorithm (CMACA) finds an approximate optimal solution through a specific target function. The simulation results show that the proposed algorithm not only reduces the energy consumption but also reduces the number of virtual machine migration.
Highlights
Cloud computing is one of the most important changes in the field of the computer industry recently
That is, when v ∈ Vk, if the vacancy rate of the source physical machine is greater than the resource occupancy of the virtual machines, and the source physical machine has no other virtual machines, the vector v is added to the migration plan, and by this step, all the Vk are traversed until the end of the traversal
The multiple-ant-colony algorithm (MACA) was evolved by evolutionary algorithms in belief space in order to reduce the energy consumption of cloud data centers by making more physical machines to shutdown with the least number of migrations
Summary
Cloud computing is one of the most important changes in the field of the computer industry recently. Server consolidation is to reduce the energy cost of the data center by migration of the virtual machine to fewer servers, and some servers are shut down or worked in a low power state according to the resource requirement of virtual machines. The idea is to reduce the number of active physical machines according to the current resource requirements. These ants establish migration plans in parallel with specific objective functions. Simulation results show that CMACA reduces the energy consumption, and reduces the number of virtual machine migration frequency. We use the distributed system framework [9] to perform dynamic server consolidation, which can improve the resource utilization and reduce energy consumption of the physical machines
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