Non-asymptotic Delay Bounds for Networks with Heavy-Tailed Traffic

Liebeherr, Jörg; Burchard, Almut; Ciucu, Florin

doi:10.1109/infcom.2010.5461913

Cited by 12 publications

(3 citation statements)

References 35 publications

(48 reference statements)

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“…There has been some recent work non-asymptotic analysis [9][10][11][12][13], but these have focused on specific aspects such as spectrum sensing [10], latency issues [11,13], or gateway effects in mesh networks [12], and none of them consider the effects of routing control protocols or mobility.…”

Section: Related Workmentioning

confidence: 99%

Symptotics: a framework for estimating the scalability of real-world wireless networks

et al. 2016

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We present a framework for non-asymptotic analysis of real-world multi-hop wireless networks that captures protocol overhead, congestion bottlenecks, traffic heterogeneity and other real-world concerns. The framework introduces the concept of symptotic scalability to determine the number of nodes to which a network scales, and a metric called change impact value for comparing the impact of underlying system parameters on network scalability. A key idea is to divide analysis into generic and specific parts connected via a signature-a set of governing parameters of a network scenario-such that analyzing a new network scenario reduces mainly to identifying its signature. Using this framework, we present the first closed-form symptotic scalability expressions for line, grid, clique, randomized grid and mobile topologies. We model both TDMA and 802.11, as well as unicast and broadcast traffic. We compare the analysis with discrete event simulations and show that the model provides sufficiently accurate estimates of scalability. We show how our impact analysis methodology can be used to progressively tune network features to meet a scaling requirement. We uncover several new insights, for instance, on the limited impact of reducing routing overhead, the differential nature of flooding traffic, and the effect real-world mobility on scalability. Our work is applicable to the design and deployment of real-world multi-hop wireless networks including community mesh networks, military networks, disaster relief networks and sensor networks.

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Section: Related Workmentioning

confidence: 99%

Symptotics: a framework for estimating the scalability of real-world wireless networks

et al. 2016

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“…The EBB model can express non-trivial processes, such as Markov-modulated On-Off processes [2], but it does not apply to heavy-tailed or long-range correlated traffic. Extensions of the EBB traffic model have been proposed for bounding functions with faster than polynomial decay [17] and even heavy-tailed decay [14].…”

Section: A Traffic Envelopesmentioning

confidence: 99%

The impact of link scheduling on long paths: Statistical analysis and optimal bounds

Ghiassi-Farrokhfal

Liebeherr

Burchard

2011

2011 Proceedings IEEE INFOCOM

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Abstract-We study how the choice of packet scheduling algorithms influences end-to-end performance on long network paths. Taking a network calculus approach, we consider both deterministic and statistical performance metrics. A key enabling contribution for our analysis is a significantly sharpened method for computing a statistical bound for the service given to a flow by the network as a whole. For a suitably parsimonious traffic model we develop closed-form expressions for end-to-end delays, backlog, and output burstiness. The deterministic versions of our bounds yield optimal bounds on end-to-end backlog and output burstiness for some schedulers, and are highly accurate for endto-end delay bounds.

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Section: A Traffic Envelopesmentioning

confidence: 99%

Statistical Analysis of Link Scheduling on Long Paths

Ghiassi-Farrokhfal¹,

Liebeherr²,

Burchard³

2011

Preprint

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We study how the choice of packet scheduling algorithms influences end-to-end performance on long network paths. Taking a network calculus approach, we consider both deterministic and statistical performance metrics. A key enabling contribution for our analysis is a significantly sharpened method for computing a statistical bound for the service given to a flow by the network as a whole. For a suitably parsimonious traffic model we develop closedform expressions for end-to-end delays, backlog, and output burstiness. The deterministic versions of our bounds yield optimal bounds on end-to-end backlog and output burstiness for some schedulers, and are highly accurate for end-to-end delay bounds.

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Non-asymptotic Delay Bounds for Networks with Heavy-Tailed Traffic

Cited by 12 publications

References 35 publications

Symptotics: a framework for estimating the scalability of real-world wireless networks

Symptotics: a framework for estimating the scalability of real-world wireless networks

The impact of link scheduling on long paths: Statistical analysis and optimal bounds

Statistical Analysis of Link Scheduling on Long Paths

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