Internet measurements show that a small number of large TCP flows are responsible for the largest amount of data transferred, whereas most of the TCP sessions are made up of few packets. Several authors have invoked this property to suggest the use of scheduling algorithms, which favor short jobs, such as LAS (least attained service), to differentiate between short and long TCP flows. We propose a packet level stateless, threshold based scheduling mechanism for TCP flows, RuN2C. We describe an implementation of this mechanism, which has the advantage of being TCP compatible and progressively deployable. We compare the behavior of RuN2C with LAS based mechanisms through analytical models and simulations. As an analytical model, we use a two level priority processor sharing PS + PS. In the PS + PS system, a connection is classified as high or low priority depending on the amount of service it has obtained. We show that PS + PS reduces the mean response time in comparison with standard processor sharing when the hazard rate of the file size distribution is decreasing. By simulations we study the impact of RuN2C on extreme values of response times and the mean number of connections in the system. Both simulations and analytical results show that RuN2C has a very beneficial effect on the delay of short flows, while treating large flows as the current TCP implementation does. In contrast, we find that LAS based mechanisms can lead to pathological behavior in extreme cases.

Inspired by several recent papers that focus on scheduling disciplines for network flows, we present a mean delay analysis of Multilevel Processor Sharing (MLPS) scheduling disciplines in the context of M/G/1 queues. Such disciplines have been proposed to model the effect of the differentiation between short and long TCP flows in the Internet. Under MLPS, jobs are classified into classes depending on their attained service. We consider scheduling disciplines where jobs within the same class are served either with Processor Sharing (PS) or Foreground Background (FB) policy, and the class that contains jobs with the smallest attained service is served first. It is known that the FB policy minimizes (maximizes) the mean delay when the hazard rate of the job size distribution is decreasing (increasing). Our analysis, based on pathwise and meanwise arguments of the unfinished truncated work, shows that Two-Level Processor Sharing (TLPS) disciplines, e.g., FB+PS and PS+PS, are better than PS scheduling when the hazard rate of the job size distribution is decreasing. If the hazard rate is increasing and bounded, we show that PS outperforms PS+PS and FB+PS. We further extend our analysis to study local optimality within a level of an MLPS scheduling discipline.