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Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies.
Accordingly, market based resource allocation models for cloud computing have been proposed.
Packet reception rate- (PRR-) based resource allocation is proposed to calculate the optimal time slot allocation for each user.
Thus, we consider utility-based resource allocation instead of rate-based resource allocation in this paper.
Experiments based on real TerraFly workload show that our system can accurately predict the workload's resource demands online and automatically allocate the resources accordingly to meet the performance target and save substantial resource cost compared to peak-load-based resource allocation.
In second step, a resource block is selected based on resource allocation scenarios.
Secondly, a Q-learning based joint resource allocation algorithm is designed.
Physicians are required to make decisions based on resource allocation, despite the insufficient training they received on resource allocation [ 53- 55].
Furthermore, users can model and specify non-performance based parameters that influence resource allocation.
"That information could be compared with other sorts of performance or resource allocation issues".
Furthermore, heuristics are used to ameliorate the search performance for resource allocation problem.
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