A basic calculus is presented for stochastic service guarantee analysis in communication networks. Central to the calculus are two definitions, maximum-(virtual)-backlog-centric (m.b.c) stochastic arrival curve and stochastic service curve, which respectively generalize arrival curve and service curve in the deterministic network calculus framework. With m.b.c stochastic arrival curve and stochastic service curve, various basic results are derived under the (min, +) algebra for the general case analysis, which are crucial to the development of stochastic network calculus. These results include (i) superposition of flows, (ii) concatenation of servers, (iii) output characterization, (iv) per-flow service under aggregation, and (v) stochastic backlog and delay guarantees. In addition, to perform independent case analysis, stochastic strict server is defined, which uses an ideal service process and an impairment process to characterize a server. The concept of stochastic strict server not only allows us to improve the basic results (i) -(v) under the independent case, but also provides a convenient way to find the stochastic service curve of a serve. Moreover, an approach is introduced to find the m.b.c stochastic arrival curve of a flow and the stochastic service curve of a server.
The introduction of quality of service (QoS) architectures to the Internet invites to apply new models to the analysis of network nodes. These models, which include the Guaranteed Rate (GR) model for the Integrated Services (IntServ) architecture and the Packet Scale Rate Guarantee (PSRG) model for the Differentiated Services (DiffServ) architecture, specify the service of a network router using bounds on service rate and delay. In this paper, we propose a measurement approach to estimate parameters for these models, which is of particular importance when these parameters cannot be obtained or verified through theoretical analysis. The idea of the proposed approach is to conduct measurement externally on the router and to estimate the desired parameters through burst period and backlog period measurements.
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