A simulation study on traffic aggregation in multi-service networks

Dolzer, Klaus; Payer, W.; Eberspächer, M. D.

doi:10.1109/hpsr.2000.856660

Cited by 13 publications

(11 citation statements)

References 9 publications

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“…In contrast, it makes much less impact on the delay bounds of aggregate scheduling. The result shows that aggregation is more advantageous if the number of hops is large, which is similar to the conclusion in [28].…”

Section: Discussionsupporting

confidence: 83%

“…Corollary 2: If flow conforms to the token-bucket model and , the e2e delay result of Theorem 6 becomes (28) Note that, thanks to the rate-control mechanism at aggregators, the e2e bound does not depend on the burstiness of other flows in the same aggregate. Thus, the bound is smaller than those of the work-conserving cases.…”

Section: A Delay Bound Iii: Nonwork-conserving Aggregatormentioning

confidence: 91%

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End-to-end delay bounds for traffic aggregates under guaranteed-rate scheduling algorithms

Sun

Shin

2005

IEEE/ACM Trans. Networking

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This paper evaluates, via both analysis and simulation, the end-to-end (e2e) delay performance of aggregate scheduling with guaranteed-rate (GR) algorithms. Deterministic e2e delay bounds for a single aggregation are derived under the assumption that all incoming flows at an aggregator conform to the token bucket model. An aggregator can use any of three types of GR scheduling algorithms: stand-alone GR, two-level hierarchical GR, and rate-controlled two-level hierarchical GR. E2e delay bounds are also derived for the case of multiple aggregations within an aggregation region when aggregators use the rate-controlled two-level hierarchical GR. By using the GR scheduling algorithms for traffic aggregates, we show not only the existence of delay bounds for each flow, but also the fact that, under certain conditions (e.g., when the aggregate traverses a long path after the aggregation point), the bounds are smaller than that of per-flow scheduling. We then compare the analytic delay bounds numerically and conduct in-depth simulation to: 1) confirm the analytic results and 2) compare the e2e delays of aggregate and per-flow scheduling. The simulation results have shown that aggregate scheduling is very robust and can exploit statistical multiplexing gains. It performs better than per-flow scheduling in most of the simulation scenarios we considered.Overall, aggregate scheduling is shown theoretically to provide bounded e2e delays and practically to provide excellent e2e delay performance. Moreover, it incurs lower scheduling and state-maintenance overheads at routers than per-flow scheduling. All of these salient features make aggregate scheduling very attractive for use in Internet core networks.Index Terms-Aggregate scheduling, end-to-end (e2e) delay bounds, token bucket model, traffic aggregation.

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Section: Discussionsupporting

confidence: 83%

Section: A Delay Bound Iii: Nonwork-conserving Aggregatormentioning

confidence: 91%

End-to-end delay bounds for traffic aggregates under guaranteed-rate scheduling algorithms

Sun

Shin

2005

IEEE/ACM Trans. Networking

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“…This step is repeated until no data is left within the burst. If the The performance of burst assembly algorithms has already network implements burst segmentation techniques, the last been studied for simulated traffic [3][4][5][6][7][8], namely for research in readable packet may be corrupt, and if so, it is discarded. the area of burst assembly algorithms, Quality of Service and burst traffic statistics.…”

mentioning

confidence: 99%

Assessment of Burst Assembly Algorithms using Real IPv4 Data Traces

García

Monteiro

Freire

2006

The 2nd International Conference on Distributed Frameworks for Multimedia Applications

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This paper describes the generation of data bursts using discusses the metrics devised for assessment of the burst real JPv4 data as input, compares the performance of the three assembly algorithms; Section IV presents the assessment of the aggregation algorithms and suggests a novel mechanism to adjust the burst assembly algorithms and Section V presents the novel burst assembly algorithm thresholds. The generated bursts are mechanism to adjust the burst assembly algorithm thresholds studied, in particular average packet delay per burst, burst interand main conclusions.

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“…The general conclusion is that providing a definite answer to the choice between reservation and BE depends on the load patterns. † The work in [14] addresses the issue of levels of aggregation and the main conclusion is that the best QoS is achieved when flows with identical characteristics are aggregated and the division of traffic into two classes, a Real-Time class and a non-Real-Time class, is adequate to meet the stringent delay QoS requirements of the audio and video. † In [15], the authors compare the 'fat dumb pipe' (besteffort) model with a differentiated services model.…”

Section: Introductionmentioning

confidence: 99%

Capacity requirements of traffic handling schemes in multi-service networks

Nyirenda-Jere

Frost

Akar

2005

Computer Communications

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This paper deals with the impact of traffic handling mechanisms on capacity for different network architectures. Three traffic handling models are considered: per-flow, class-based and best-effort (BE). These models can be used to meet service guarantees, the major differences being in their complexity of implementations and in the quantity of network resources that must be provided. In this study, the performance is fixed and the required capacity determined for various combinations of traffic handling architectures for edge-core networks. This study provides a comparison of different QoS architectures. One key result of this work is that on the basis of capacity requirements, there is no significant difference between semi-aggregate traffic handling and per-flow traffic handling. However, best-effort handling requires significantly more capacity as compared to the other methods. © 2004 Elsevier B.V. All rights reserved

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A simulation study on traffic aggregation in multi-service networks

Cited by 13 publications

References 9 publications

End-to-end delay bounds for traffic aggregates under guaranteed-rate scheduling algorithms

End-to-end delay bounds for traffic aggregates under guaranteed-rate scheduling algorithms

Assessment of Burst Assembly Algorithms using Real IPv4 Data Traces

Capacity requirements of traffic handling schemes in multi-service networks

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