Sharp bounds in stochastic network calculus

CiucuFlorin,; PoloczekFelix,; SchmittJens,

doi:10.1145/2494232.2465746

Cited by 7 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Figure 10 indicates that the upper and lower bounds for Aloha are quite tight. For CSMA/CA, however, only the upper bounds remain reasonably tight whereas the lower bounds tend to degrade with the number of hops k. This is due to the underlying application of the Boole's inequality, which is known to be loose in the case of correlated arrivals (see, e.g., [10]).…”

Section: Numerical Resultsmentioning

confidence: 99%

“…This saturation condition translates into system theoretic terms as follows: the input signal to the second system in Figure 4 is the infinite signal A 2 (t) = ∞ for ∀t (also called the impulse), whereas the corresponding output, i.e., the impulse-response, is the signal S 2 (t), or S 2 (0, t) in the notation from Eq. (10). Therefore, the construction of S 2 (s, t) is analogous to the construction of impulse-response functions in LTI systems, which are the output from an LTI system with input given by the Kronecker signal (see [26]).…”

Section: A Centralized Schedulingmentioning

confidence: 99%

See 1 more Smart Citation

Towards a system theoretic approach to wireless network capacity in finite time and space

Ciucu

Khalili

Jiang

et al. 2014

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications

Self Cite

View full text Add to dashboard Cite

Copies of full items can be used for personal research or study, educational, or not-for profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content is not changed in any way.Publisher's statement: "© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP URL' above for details on accessing the published version and note that access may require a subscription. Abstract-In asymptotic regimes, both in time and space (network size), the derivation of network capacity results is grossly simplified by brushing aside queueing behavior in nonJackson networks. This simplifying double-limit model, however, lends itself to conservative numerical results in finite regimes. To properly account for queueing behavior beyond a simple calculus based on average rates, we advocate a system theoretic methodology for the capacity problem in finite time and space regimes. This methodology also accounts for spatial correlations arising in networks with CSMA/CA scheduling and it delivers rigorous closed-form capacity results in terms of probability distributions. Unlike numerous existing asymptotic results, subject to anecdotal practical concerns, our transient results can be used in practical settings, e.g., to compute the time scales at which multi-hop routing is more advantageous than single-hop routing.

show abstract

Section: Numerical Resultsmentioning

confidence: 99%

Section: A Centralized Schedulingmentioning

confidence: 99%

Towards a system theoretic approach to wireless network capacity in finite time and space

Ciucu

Khalili

Jiang

et al. 2014

IEEE INFOCOM 2014 - IEEE Conference on Computer Communications

Self Cite

View full text Add to dashboard Cite

show abstract

“…for some 0 < K < 1; see Theorem 1 in [15], which recovers Theorem 2.1 from [44]. In turn, the pre-factor from Eq.…”

Section: B Review Of Martingale Resultsmentioning

confidence: 60%

Sharp bounds in stochastic network calculus

Ciucu

Poloczek

Schmitt

2013

Proceedings of the ACM SIGMETRICS/international Conference on Measurement and Modeling of Computer Systems

Self Cite

View full text Add to dashboard Cite

The practicality of the stochastic network calculus (SNC) is often questioned on grounds of potential looseness of its performance bounds. In this paper it is uncovered that for bursty arrival processes (specifically Markov-Modulated OnOff (MMOO)), whose amenability to per-flow analysis is typically proclaimed as a highlight of SNC, the bounds can unfortunately indeed be very loose (e.g., by several orders of magnitude off). In response to this uncovered weakness of SNC, the (Standard) per-flow bounds are herein improved by deriving a general sample-path bound, using martingale based techniques, which accommodates FIFO, SP, and EDF scheduling disciplines. The obtained (Martingale) bounds capture an additional exponential decay factor of O e −αn in the number of flows n, and are remarkably accurate even in multiplexing scenarios with few flows.

show abstract

End-to-End Backlog and Delay Bound Analysis for Multi-Hop Vehicular Ad Hoc Networks

Chang

et al. 2017

IEEE Trans. Wireless Commun.

View full text Add to dashboard Cite

Sharp bounds in stochastic network calculus

Cited by 7 publications

References 12 publications

Towards a system theoretic approach to wireless network capacity in finite time and space

Towards a system theoretic approach to wireless network capacity in finite time and space

Sharp bounds in stochastic network calculus

End-to-End Backlog and Delay Bound Analysis for Multi-Hop Vehicular Ad Hoc Networks

Contact Info

Product

Resources

About