Computer Networks: The International Journal of Computer and Telecommunications Networking
Closed-form analysis of end-to-end network delay with Markov-modulated Poisson and fluid traffic
Computer Communications
Network calculus and queueing theory: two sides of one coin: invited paper
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
Almost sure stability of networked control systems under exponentially bounded bursts of dropouts
Proceedings of the 14th international conference on Hybrid systems: computation and control
Perspectives on network calculus: no free lunch, but still good value
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
Perspectives on network calculus: no free lunch, but still good value
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
An end-to-end stochastic network calculus with effective bandwidth and effective capacity
Computer Networks: The International Journal of Computer and Telecommunications Networking
On applying stochastic network calculus
Frontiers of Computer Science: Selected Publications from Chinese Universities
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The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad classes of arrival and service distributions. The benefits of the derived service curve are illustrated for the exponentially bounded burstiness (EBB) traffic model. It is shown that end-to-end performance measures computed with a network service curve are bounded by 𝒪(H log H), where H is the number of nodes traversed by a flow. Using currently available techniques, which compute end-to-end bounds by adding single node results, the corresponding performance measures are bounded by 𝒪(H3).