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In the first phase, the Cloud Resource Optimizer (CRO) enumerates an integral number of resource instances 'j' for every cloud user, which if reserved can ensure minimum cost from cloud users' point of view, which has been adapted from [43].
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In both cases and before adjusting any resources, the optimizer actuator consults the list of background processes to avoid any conflict.
A genetic crew scheduler model consists of a master plan, job sequencer, crew scheduler, genetic optimizer, resource constrained scheduler, precedence analyzer, auditing facility, and the crew schedules.
The optimizer outputs the resource assignments and rate allocation to the MAC and APP layer, respectively.
The second approach employs a QoE optimizer which performs radio resource allocation decision for the eNodeB.
It consists of the user-defined control period (UDCP) optimizer and the optimized control period (OCP) optimizer.
The optimizer actuator begins adjusting resources gradually for the application B before the end of the application A in order to not impact the user experience.
Therefore, in power load sharing (PLS), the load balance is performed based on the occupied physical resource block (PRB), whereas the previous PTS optimizer depended on blocked calls.
A competitive swarm optimizer for large-scale optimization (CEO) [39].
The best transitions per peptide were optimized using the Peptide Optimizer software tool.
The optimizer estimates the available radio resources for video transmission by retrieving channel quality information from the eNodeB.
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