摘要：In cloud computing, a key characteristic is On-demand resource management. For proper
resource allocation, fair computational resource sharing should be done by cloud
providers. Better resources should be allocated to all users. Resource utilization
enhancement is also focused by reducing resource fragmentation, where virtual machines
are mapped to physical servers. In cloud environment, an adaptive resource allocation
mechanism is proposed in this recent work. A limited resource quantity mapping to
independent user for finishing their jobs is focused. However, based on operational costs,
there will be an increase in energy requirement for operating cloud infrastructure.
According to literature, energy minimization is focused in this work by CPU utilization
regulation while operating at maximum frequency. For computing energy consumption,
resource utilization and fairness, introduced a Dynamic Particle Swarm Optimization
(DPSO) model. The computation is done while executing jobs by VMs on cloud
computing resources in absent presence. The Google workload trace is used in simulation
and resource wastage are minimized using proposed algorithm and achieves a better
utilization of resource when compared with other allocation techniques as demonstrated in
results.
关键词：Dynamic Particle Swarm Optimization; Energy Efficiency; Resource Allocation; Cloud Computing;
