assuring qos guarantees for heterogeneous services in rina networks with Δq

Assuring QoS Guarantees for Heterogeneous Services in

RINA Networks with ΔQ

Sergio Leon(1), Jordi Perelló(1), Davide Careglio(1), Eduard Grasa(2), Miquel Tarzan(2), Neil Davies(3) and Peter Thompson (3)

(1) Universitat Politècnica de Catalunya (UPC) (2) Fundació Privada i2CAT (i2CAT) (3) Predictable Network Solutions

* This research has been funded by the European Project FP7 PRISTINE, as well as the Spanish National project SUNSET.

UPC

Sergio Leon, Jordi Perelló, Davide Careglio, Eduard Grasa, Miquel Tarzan, Neil Davies and Peter Thompson, “Assuring QoS Guarantees for Heterogeneous Services in RINA Networks with ΔQ”

Summary

Applications and their requirements

A quick look at RINA

QoS in RINA

RINA and ΔQ scheduling policies

Scenario description

Numerical results

Conclusions

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UPC


Applications and their requirements

Application requirements have evolved over time:

Limits on delay and acceptable jitter

Possibility and distribution of acceptable losses

Secure flows

Etc.

IP with TCP/UDP does not fulfil current requirements

Other solutions based on IP neither!

Next generation networks should be able to get and fulfil QoS requirements at each layer

Here comes RINA

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UPC


A quick look at RINA(1/2)

RINA : Recursive InterNetworking Architecture

Key idea:

“Networking is Inter Process

Communication (IPC) and only IPC”

What it really is:

Clean-slate recursive Internet model

Same type of layer, Distributed IPC Facility (DIF), at each level

All DIFs share the same functionality

Even so, each DIF can be fully configured via policies

Each DIF may provide full support for a wide range of QoS

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UPC


A quick look at RINA(2/2)

Each IPC Process (IPCP) shares the same API

Upper IPCP and applications use that to request flows with specific QoS requirements

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UPC


QoS in RINA

Multiple QoS Cubes available at each DIF

QoS Cubes define measures like:

Minimum quality provided:

• Maximum delay and jitter

• Probability of loss (0 if reliable)

• Minimum bandwidth

Maximum quality provided:

• Maximum bandwidth

• Maximum supported burst and duration

Additional capabilities:

• Flow security

• Cost and assurance on overbooked scenarios

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UPC


RINA and ΔQ scheduling policies(1/4)

Scheduling is the main way to ensure short-term QoS requirements

In particular, when performing scheduling, 3 measures become tightly linked:

Delay / Losses / Bandwidth

Three parameters: only two degrees of freedom!

In RINA, QoS Cubes provide simple bandwidth constraints

And requirements in terms of delay and losses

Just what we need for ΔQ-aware scheduling policies

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UPC



ΔQ scheduling policies focus on sharing unavoidable degradation

How much added delay a packet/flow suffers?

How probable is it that packets are dropped?

What will the throughput of a flow be?

ΔQ scheduling policies merge:

Multiplexing (Cherish/Urgency matrix)

Flow shaping Cherish 1 Cherish 2 Cherish 3

Urgency 1 A1 A2 A3

Urgency 2 B1 B2 B3

Urgency 3 C1 C2 C3

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UPC



ΔQ manages inter-flow contention

Cherish/Urgency multiplexor per output port

Shared buffer between all flows

Capacity to discard an incoming packet given the flow cherish level and global occupation

Serve based on urgency

Shares degradation between flows given their QoS

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UPC



ΔQ manages intra-flow contention

Policer/Shaper per flow, QoS, set of flows, etc.

Shaping long bursts and spacing packets avoids the starvation of low requirement flows

Policing ensures that flows behave as contracted

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UPC


Scenario Description(1/2)

Inter-datacenter communication between multiple network domains

QoS has to be supported at each layer

Particularly in backbone networks

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UPC


Scenario Description(2/2)

Our focus is a small backbone network of 10 nodes

It supports traffic

Internet traffic: Best-effort traffic (BE) and Urgent traffic (sBE)

Inter-DC traffic: Urgent traffic (GU) and non-urgent (SN)

Inter-DC traffic is more valuable, but with same urgencies

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UPC


Numerical results(1/2)

ΔQ policies allows us to ensure minimum or even null losses for high-priority traffic even at 150% link capacity

Latency can be also contained for urgent traffic, independently of their losses

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C/U + Cherish ··· - Cherish

+ Urgent GU sBE

- Urgent SN BE

UPC


Numerical results(2/2)

Compared to existing IP-based solutions:

Losses can be gracefully shared between QoS classes. as well as latency and jitter

This means that:

Degradation is not equally shared between flows

Nor does it concentrate in the lowest priority classes only!

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Weighted Fair QueueBaseline Best-Effort

UPC


Conclusions

Assuring QoS guarantees is a requirement for future networks

Not only that, but a way to inform and maintain these requirements between layers

RINA provides a model capable of fully supporting QoS for current and future application requirements

In this regard, ΔQ scheduling policies provide a way to effectively ensure QoS guarantees, even in overloaded scenarios

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Thanks. Questions?

The authors of this work would like to thank all members of the PRISTINE Project consortium for the valuable

discussions and inputs