A Reward-Based Fair Resource Allocation in EONs Considering Traffic Demand Behavior

This work proposes a reward-based framework for fair resource allocation in reconfigurable elastic optical networks (EONs) under modeled traffic demand fluctuations. The routing and spectrum allocation (RSA) problem is formulated based on the maximization of the reward-based constant elasticity social welfare function, with rewards received by connections when allocated spectrum slots, given their a-priori modeled traffic distributions. Connections are essentially contending for link resources, with the connections' preferences depending on the reward function used for scoring these resources. Two reward functions are utilized, considering different attributes of the optimization problem, according to fairness- and efficiency-related measures. The proposed framework can be used by a network operator for approximating in advance the provisioning of the resources for each connection that best meets predefined targets. Performance results demonstrate that both reward functions result in spectrum allocations where the quality-of-service (QoS) is as similar as possible for all connections, significantly improving connection over- and under-provisioning. Additionally, the reward function that also accounts for the modeled traffic further improves fairness and connection over-provisioning, while incurring only a small penalty in terms of the aggregate unserved traffic for all destinations.