*A Resource Allocation Model Driven through QoC for Distributed Systems DOI: http://dx.doi.org/10.5772/intechopen.106458*

standard deviation, when compared to well-known strategies. From the use of the proposed QoC-based policy, was obtained average QoE scores between 80 and 100% considering each user. The resulting QoE values adhere to a flat surface for workloads with large amounts of tasks. Thus, our model shows a stable behavior considering obtained QoEs. Results show that the proposed model established fair behavior (fairness) in resource allocation. Our QoC-based policy stands out, especially when there are excessive workloads and a lack of resources. Among the works mentioned in related works, there are approaches to allocate resources considering the performance of the environment and user satisfaction. Although the related proposals aim to meet user demands, the authors do not provide metrics for effective measurement of user satisfaction. In addition to all that has been mentioned, the works found in the literature on resource allocation are generally applied to specific environments, which do not consider orchestrating different paradigms of distributed systems. Therefore, the main contributions of this work are a solution to the existing gap between user satisfaction and environmental performance (makespan) for distributed systems. Although this work aims to meet the needs of the system and the users, it does not guarantee the QoE individually for the users, it only proposes to improve the average satisfaction. Another limitation of the work is that although the model has been tried in specialized simulators, this model has not been implemented in a physically robust fog environment.
