Queues with equally heavy sojourn time and service requirement distributions

For the G/G/1 queue with First-Come First-Served, it is well known that the tail of the sojourn time distribution is heavier than the tail of the service requirement distribution when the latter has a regularly varying tail. In contrast, for the M/G/1 queue with Processor Sharing, Zwart and Boxma showed that under the same assumptions on the service requirement distribution, the two tails are ``equally heavy''. By means of a probabilistic analysis we provide a new insightful proof of this result, allowing for the slightly weaker assumption of service requirement distributions with a tail of intermediate regular variation. The new approach allows us to also establish the ``tail equivalence'' for two other service disciplines: Foreground-Background Processor Sharing and Shortest Remaining Processing Time. The method can also be applied to more complicated models, for which no explicit formulas exist for (transforms of) the sojourn time distribution. One such model is the M/G/1 Processor Sharing queue with service that is subject to random interruptions. The latter model is of particular interest for the performance analysis of communication networks.