Analysis of Stochastic Service Guarantees in Communication Networks: A Server Model Yuming Jiang and Peder J. Emstad Centre for Quantifiable Quality of Service in Communication Systems ⋆ Department of Telematics Norwegian University of Science and Technology (NTNU), Norway ymjiang@ieee.org, peder@q2s.ntnu.no Abstract. Many communication networks such as wireless networks only provide stochastic service guarantees. For analyzing stochastic ser- vice guarantees, research efforts have been made in the past few years to develop stochastic network calculus, a probabilistic version of (min, +) deterministic network calculus. However, many challenges have made the development difficult. Some of them are closely related to server modeling, which include output characterization, concatenation property, stochastic backlog guarantee, stochastic delay guarantee, and per-flow ser- vice under aggregation. In this paper, we propose a server model, called stochastic service curve to facilitate stochastic service guarantee analysis. We show that with the concept of stochastic service curve, these chal- lenges can be well addressed. In addition, we introduce strict stochastic server to help find the stochastic service curve of a stochastic server, which characterizes the service of the server by two stochastic processes: an ideal service process and an impairment process. 1 Introduction Many communication networks such as wireless networks only provide stochas- tic service guarantees. Due to the increasing deployment and application of such networks to support real-time and multimedia applications, which require QoS guarantees, the development of an information theory for stochastic service guar- antee analysis in these networks has been identified as a grand challenge for fu- ture networking research [22]. Towards it, stochastic network calculus, the proba- bilistic generalization of (min, +) (deterministic) network calculus [6][5][14], has been considered as a fundamental and important step [17]. Many challenges have made stochastic network calculus difficult. Some of them are closely related to server modeling, which include output characteriza- tion, concatenation property, stochastic backlog guarantee, stochastic delay guar- antee, and per-flow service under aggregation. In particular, the experience from ⋆ “Centre for Quantifiable Quality of Service in Communication Systems, Centre of Excellence” is appointed by The Research Council of Norway and funded by the Research Council, NTNU and UNINETT. (http://www.ntnu.no/Q2S/)