IEEE/ACM Transactions on Networking (TON)
Loss probability calculations and asymptotic analysis for finite buffer multiplexers
IEEE/ACM Transactions on Networking (TON)
Analysis on Generalized Stochastically Bounded Bursty Traffic for Communication Networks
LCN '02 Proceedings of the 27th Annual IEEE Conference on Local Computer Networks
A Calculus for End-to-end Statistical Service Guarantees
A Calculus for End-to-end Statistical Service Guarantees
Scaling properties of statistical end-to-end bounds in the network calculus
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
A basic stochastic network calculus
Proceedings of the 2006 conference on Applications, technologies, architectures, and protocols for computer communications
Network calculus: a theory of deterministic queuing systems for the internet
Network calculus: a theory of deterministic queuing systems for the internet
IEEE Transactions on Multimedia
On deterministic traffic regulation and service guarantees: a systematic approach by filtering
IEEE Transactions on Information Theory
Stochastically bounded burstiness for communication networks
IEEE Transactions on Information Theory
Statistical service assurances for traffic scheduling algorithms
IEEE Journal on Selected Areas in Communications
Entropy of ATM traffic streams: a tool for estimating QoS parameters
IEEE Journal on Selected Areas in Communications
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Recently some stochastic (probabilistic) extensions of the deterministic network calculus have been developed, mainly for exploiting the statistical multiplexing of flows aggregated in packet based communication networks. This exploitation could result "better" stochastic performance bounds than those bounds provided by the inherently worst case analysis of the deterministic network calculus. The core of these stochastic extensions is the re-definition of the so-called arrival and service curve in a probabilistic manner. Until this time the re-definitions of these curves are based on tail probability like functionals. In this paper we perform a new kind of stochastic network calculus based on defining arrival and service curves using a different functional called tail weight. The power of this approach is demonstrated by presenting fundamental results on backlog and delay bounds and concatenation of nodes, furthermore suitable service curves and numerical examples are also presented for one of the most complicated packet service disciplines, the generalized processor sharing scheduler.