Application or web services are increasingly being used across organisational boundaries. Moreover, new services are being introduced at the network and storage level. Languages to specify interfaces for such services have been researched and transferred into industrial practice. We investigate end-to-end quality of service (QoS) and highlight that QoS provision has multiple facets and requires complex agreements between network services, storage services and middleware services. We introduce SLAng, a language for defining Service Level Agreements (SLAs) that accommodates these needs. We illustrate how SLAng is used to specify QoS in a case study that uses a web services specification to support the processing of images across multiple domains and we evaluate our language based on it.

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SLAng: a language for defining service level agreements

We survey advances in theories and models for Internet quality of service (QoS). We start with the theory of network calculus, which lays the foundation for support of deterministic performance guarantees in networks, and illustrate its applications to integrated services, differentiated services, and streaming media playback delays. We also present mechanisms and architecture for scalable support of guaranteed services in the Internet, based on the concept of a stateless core. Methods for scalable control operations are also discussed. We then turn our attention to statistical performance guarantees and describe several new probabilistic results that can be used for a statistical dimensioning of differentiated services. Lastly, we review proposals and results in supporting performance guarantees in a best effort context. These include models for elastic throughput guarantees based on TCP performance modeling, techniques for some QoS differentiation without access control, and methods that allow an application to control the performance it receives, in the absence of network support.

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Theories and models for Internet quality of service

One of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it.

https://digital.library.adelaide.edu.au/dspace/bitstream/2440/35002/1/hdl_35002.pdf

Self-similar traffic and network dynamics

We consider a model of Internet congestion control that represents the randomly varying number of flows present in a network where bandwidth is shared fairly between document transfers. We study critical fluid models obtained as formal limits under law of large numbers scalings when the average load on at least one resource is equal to its capacity. We establish convergence to equilibria for fluid models and identify the invariant manifold. The form of the invariant manifold gives insight into the phenomenon of entrainment whereby congestion at some resources may prevent other resources from working at their full capacity.

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Fluid model for a network operating under a fair bandwidth-sharing policy

We consider a connection-level model of Internet congestion control, introduced by Massoulie and Roberts [Telecommunication Systems 15 (2000) 185–201], that represents the randomly varying number of flows present in a network. Here, bandwidth is shared fairly among elastic document transfers according to a weighted α-fair bandwidth sharing policy introduced by Mo and Walrand [IEEE/ACM Transactions on Networking 8 (2000) 556–567] [α∈(0, ∞)]. Assuming Poisson arrivals and exponentially distributed document sizes, we focus on the heavy traffic regime in which the average load placed on each resource is approximately equal to its capacity. A fluid model (or functional law of large numbers approximation) for this stochastic model was derived and analyzed in a prior work [Ann. Appl. Probab. 14 (2004) 1055–1083] by two of the authors. Here, we use the long-time behavior of the solutions of the fluid model established in that paper to derive a property called multiplicative state space collapse, which, loosely speaking, shows that in diffusion scale, the flow count process for the stochastic model can be approximately recovered as a continuous lifting of the workload process. Under weighted proportional fair sharing of bandwidth (α=1) and a mild local traffic condition, we show how multiplicative state space collapse can be combined with uniqueness in law and an invariance principle for the diffusion [Theory Probab. Appl. 40 (1995) 1–40], [Ann. Appl. Probab. 17 (2007) 741–779] to establish a diffusion approximation for the workload process and hence to yield an approximation for the flow count process. In this case, the workload diffusion behaves like Brownian motion in the interior of a polyhedral cone and is confined to the cone by reflection at the boundary, where the direction of reflection is constant on any given boundary face. When all of the weights are equal (proportional fair sharing), this diffusion has a product form invariant measure. If the latter is integrable, it yields the unique stationary distribution for the diffusion which has a strikingly simple interpretation in terms of independent dual random variables, one for each of the resources of the network. We are able to extend this product form result to the case where document sizes are distributed as finite mixtures of exponentials and to models that include multi-path routing. We indicate some difficulties related to extending the diffusion approximation result to values of α≠1. We illustrate our approximation results for a few simple networks. In particular, for a two-resource linear network, the diffusion lives in a wedge that is a strict subset of the positive quadrant. This geometrically illustrates the entrainment of resources, whereby congestion at one resource may prevent another resource from working at full capacity. For a four-resource network with multi-path routing, the product form result under proportional fair sharing is expressed in terms of independent dual random variables, one for each of a set of generalized cut constraints.

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State space collapse and diffusion approximation for a network operating under a fair bandwidth sharing policy

This paper presents a new approach to modeling end-toend performance for IP networks. Unlike earlier models, in which end stations generate traffic at a constant rate, the work discussed here takes the adaptive behaviour of TCP/IP into account. The approach is based on a fixed point method which determines packet loss, link utilization and TCP throughput across the network. Results are presented for an IP backbone network, which highlight how this new model finds the natural operating point for TCP, which depends on route lengths (via round-trip times and number of resources), end-to-end packet loss and the number of user sessions.

Fixed-Point Models for the End-to-End Performance Analysis of IP Networks

In this paper we report on a study of possible service level agreements in an IP network employing differentiated services. We discuss the nature of the quality of service guarantees given to network flows and relate this to the capacity provisioning processes of network operators. A contribution of this paper is to address the way service level agreements might be determined from a coherent collection of models of network phenomena which themselves naturally operate on widely differing time–scales. The very fastest timescales within IP routers. The next fastest time-scale relates to session level controls embedded within the end-system behaviour of the TCP/IP congestion avoidance algorithms, operating in the range of milliseconds to seconds. The per-packet routing and the management of aggregated traffic flows can take place over time‐scales ranging from seconds to minutes to days. Provisioning of network resources takes place over intervals of weeks and months. All of these phenomena influence the overall structure of service level agreements. This paper highlights the use of quantitative modelling methods which address fundamental concerns for network operators seeking to provide differentiated IP Quality of Service. The work described here is at a preliminary stage, but provides strong motivation for both further study and experimental validation. Our tentative conclusion is that the DiffServ Quality of Service mechanism is unlikely to be able to provide real measurable distinctions between classes on a pure IP network with no access restrictions, without either bandwidth partitioning at a lower layer or gratuitously damaging some traffic. It will, however, function as a back-stop minimum guaranteed level in times of congestion.

R. N. Macfadyen

Papers

Fixed-Point Models for the End-to-End Performance Analysis of IP Networks

An approach to service level agreements for IP networks with differentiated services