Fair Resource Allocation in Optical Networks under Tidal Traffic

by   Tania Panayiotou, et al.

We propose a game-theoretic alpha-fair routing and spectrum allocation (RSA) framework for reconfigurable elastic optical networks under modeled tidal traffic, that is based on the maximization of the social welfare function parameterized by a scalar alpha (the inequality aversion parameter). The objective is to approximate an egalitarian spectrum allocation (SA) that maximizes the minimum possible SA over all connections contending for the network resources, shifting from the commonly considered utilitarian SA that merely maximizes the network efficiency. A set of existing metrics are examined (i.e., connection blocking, resource utilization, coefficient of variation (CV) of utilities), and a set of new measures are also introduced (i.e., improvement on connection over- (COP) and under-provisioning (CUP), CV of unserved traffic), allowing a network operator to derive and evaluate in advance a set of alpha-fair RSA solutions and select the one that best fits the performance requirements of both the individual connections and the overall network. We show that an egalitarian SA better utilizes the network resources by significantly improving both COP (up to 20 the utilitarian allocation, while attaining zero blocking. Importantly, the CVs of utilities and unserved traffic indicate that a SA that is fairest with respect to the amount of utilities allocated to the connections does not imply that the SA is also fairest with respect to the achievable QoS of the connections, while an egalitarian SA better approximates a fairest QoS-based SA.


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