A scheduling algorithm for relative delay differentiation

Bodamer, Stefan

doi:10.1109/hpsr.2000.856683

Cited by 11 publications

(7 citation statements)

References 25 publications

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“…For instance, [30] proposed the local optimal proportional differentiation (LOPD) scheduler, which attempts to provide proportional average delay differentiation in each busy period. [3] extended the PDD model in the direction of deadline violation probabilities, proposing a scheduler that aims for proportional delay violation probabilities among classes. Finally, [22] proposed a joint buffer management and Scheduling (JoBS) mechanism which determines both the scheduling order and the packet drop decisions.…”

Section: B Recent Contributions In Pddmentioning

confidence: 99%

Proportional differentiated services: delay differentiation and packet scheduling

Dovrolis

Stiliadis²,

Ramanathan

2002

IEEE/ACM Trans. Networking

383

513

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The proportional differentiation model provides the network operator with the 'tuning knobs' for adjusting the per-hop quality-of-service (QoS) ratios between classes, independent of the class loads. This paper applies the proportional model in the differentiation of queueing delays, and investigates appropriate packet scheduling mechanisms. Starting from the proportional delay differentiation (PDD) model, we derive the average queueing delay in each class, show the dynamics of the class delays under the PDD constraints, and state the conditions in which the PDD model is feasible. The feasibility model of the model can be determined from the average delays that result with the strict priorities scheduler. We then focus on scheduling mechanisms that can implement the PDD model, when it is feasible to do so. The proportional average delay (PAD) scheduler meets the PDD constraints, when they are feasible, but it exhibits a pathological behavior in short timescales. The waiting time priority (WTP) scheduler, on the other hand, approximates the PDD model closely, even in the short timescales of a few packet departures, but only in heavy load conditions. PAD and WTP serve as motivation for the third scheduler, called hybrid proportional delay (HPD). HPD approximates the PDD model closely, when the model is feasible, independent of the class load distribution. Also, HPD provides predictable delay differentiation even in short timescales.Index Terms-Dynamic priorities, quality of service, resource management algorithms.

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Section: B Recent Contributions In Pddmentioning

confidence: 99%

Proportional differentiated services: delay differentiation and packet scheduling

Dovrolis

Stiliadis²,

Ramanathan

2002

IEEE/ACM Trans. Networking

383

513

View full text Add to dashboard Cite

show abstract

“…This policy is useful for handling real-time packets that become useless when it arrives at its destinations after a determined delay. In [22], the authors proposed an enhanced version of EDF SSD called weighted EDF (WEDF) SSD. In this, the packets are served according to its deadline and deadline violation probability; furthermore, it differentiates packets drop during congestion period based on its excess probabilities and its class weights.…”

Section: Earliest Deadline First Schedulingmentioning

confidence: 99%

Expedited forwarding end‐to‐end delay and jitter in DiffServ

Alshaer

Elmirghani

2008

Int J Communication

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SUMMARYThe scheduling disciplines and active buffer management represent the main components employed in the differentiated services (DiffServ) data plane, which provide qualitative per-hop behaviors corresponding to the QoS required by supported traffic classes. In the first part of this paper, we compute the per-hop delay bound that should be guaranteed by the different multiservice scheduling disciplines, so that the end-to-end (e2e) delay required by expedited forwarding (EF) traffic can be guaranteed. Consequently, we derive the e2e delay bound of EF traffic served by priority queuing-weighted fair queuing (PQ-WFQ) at every hop along its routing path. Although real-time flows are principally offered EF service class, some simulations on DiffServ-enabled network show that these flows suffer from delay jitter and they are negatively impacted by lower priority traffic. In the second part of this paper, we clarify the passive impact of delay jitter on EF traffic, where EF flows are represented by renewal periodic ON-OFF flows, and the background (BG) flows are characterized by the Poisson process. We analyze through different scenarios the jitter effects of these BG flows on EF flow patterns when they are served by a single class scheduling discipline, such as first-input first-output, and a multiclass or multiservice scheduling discipline, such as static priority service discipline. As a result, we have found out that the EF per-hop behaviors (PHBs) configuration according to RFCs 2598 and 3246 (IETF RFC 2598, June 1999 RFC 3246, IETF, March 2002) cannot stand alone in guaranteeing the delay jitter required by EF flows . Therefore, playout buffers must be added to DiffServ-enabled networks for handling delay jitter problem that suffers from EF flows.

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“…This means that for a given set of arrival load values {λ i }, the corresponding feasible delays, {d f i } are evaluated and effectively achieved by the differentiation mechanism. Therefore, deviations from the initial target delays {d i } are expected to occur, and consequently, the obtained values can be expressed by (8), where ∆ i represents the delay deviation of Class i . One of the contributions of the proposed mechanism is the ability to control such deviations, in fact the Congestion Differentiation Parameters have the semantic power to establish maximum relations for the spread of {∆ i } values.…”

Section: Parameter Configurationmentioning

confidence: 99%

“…Instead, the mechanism discussed in this paper is more adequate for scenarios where admission control procedures are more relaxed and operate in network edges devices. Related to this aspect, [8] proposes a modified EDD schema in order to differentiate the probability of queuing delay violations under a congested network. In our opinion, it is also fundamental to differentiate the relative value of such violations, i.e.…”

Section: Introductionmentioning

confidence: 99%

Enhancing Delay Differentiation Semantics of Class-Based IP Networks

Sousa

Carvalho

Freitas

2004

Lecture Notes in Computer Science

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This paper presents a time-sensitive scheduler oriented to delay differentiation in class-based networks, studying its behaviour from a single node to an end-to-end perspective. The novel feature of this scheduler is that it tries to bound the queuing delay per class and, simultaneously, to control the excess queuing delays in order to avoid class starvation. The study analyses the scheduler behaviour for heterogeneous class-load distributions and distinct timescales proving the robustness of the mechanism. Discussion on its operational feasibility conditions is carried out and configuration guidelines for its use are provided. In addition, the paper proposes a new queue selection procedure in order to improve its performance in high speed networks.10 ρ = λ •S, where λ is the arrival rate andS the average service time. 11 This is a platform-dependent factor.

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A scheduling algorithm for relative delay differentiation

Cited by 11 publications

References 25 publications

Proportional differentiated services: delay differentiation and packet scheduling

Proportional differentiated services: delay differentiation and packet scheduling

Expedited forwarding end‐to‐end delay and jitter in DiffServ

Enhancing Delay Differentiation Semantics of Class-Based IP Networks

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