Systemic risks/benefits of selfish network operations & management in dynamic environment

Allowing selfish agents to acquire and exploit system information has both positive and negative effects on the overall performance of resource allocation systems. The positive effect results from reduction in the uncertainty inherently present in large-scale systems. The negative effect, which can be mitigated through congestion pricing, is due to agent selfishness. However, current research, concentrated around the notion of “Price of Anarchy”, is mostly concerned with the negative effect. This paper evaluates systemic risks/benefits of selfish agent ability to acquire and exploit dynamic system information in a specific case of selfish routing in a large-scale, random, loss network. Our analysis indicates that the beneficial effect of this ability dominates in a case of high system uncertainty - low load, while the negative effect dominates in a case of low system uncertainty - high load. In the intermediate cases while the beneficial effect still dominates in the “normal” operating mode, the negative effect manifests itself in a risk of cascading overload driving the system to an emergent metastable, i.e., persistent, congested mode. Future research should consider resource allocation models with elastic selfish users and evaluate effect of the congestion pricing.