  In this work, we propose an axiomatic approach for measuring the
performance/welfare of a system consisting of concurrent agents in a
resource-driven system. Our approach provides a unifying view on popular system
optimality principles, such as the maximal average/total utilities and the
max-min fairness. Moreover, it gives rise to other system optimality notions
that have not been fully exploited yet, such as the maximal lowest total
subgroup utilities. For the axiomatically defined welfare measures, we provide
a generic gradient-based method to find an optimal resource allocation and
present a theoretical guarantee for its success. Lastly, we demonstrate the
power of our approach through the power control application in wireless
networks.
