2009 03 11 routing oslo - universitetet i oslo · `routing basics `quality of service routing...

11/03/2009Oslo NOOslo, NO

Marília [email protected]

Routing BasicsQuality of Service RoutingRouting in Wireless Mesh NetworksResearch ChallengesProjects

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RIPOSPFBGP

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GoalsE d t d ti it◦ End-to-end connectivity

◦ Maximise network performance◦ Fault tolerance

Ad t ti t d i t l i◦ Adaptation to dynamic topologies

Building blocksg◦ Routing policies◦ Routing information exchange◦ Path computationp◦ Routing table maintenance

◦ Forwardingg

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IG IG

IG

IGIG

IG IG

IGIG

EG

CoreNetwork

EGEG Sistema autónomo

Sistema autónomo

EG

IG IG IG IG

Sistema autónomo

IG

G GIG - Interior GatewayEG - Exterior Gateway

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Protocol◦ Exchange of routing information

AlgorithmAlgorithm◦ (Shortest) Path computation

V2 V35

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3 6

3

5

V1V6

2

3

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2 2 33

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24

8

V4 V5

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1

2

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Distance Vector◦ Each router sends to its neighbors information

about the distance to all the destinations it knows

Link State◦ Each router sends/floods information about the

state of its links

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Routing Information Protocol (RIP)

Open Shortest Path First (OSPF)

Border Gateway Protocol (BGP)

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Routing Information Protocol (RIP)Interior Gateway Routing Protocol (IGRP)Interior Gateway Routing Protocol (IGRP)

◦ Each router sends to its neighbors information about the distance to all the destinations it knows

◦ Based on the information received from its neigbors, each router computes the shortest path to all destinations

◦ Routing metricNumber of hops

◦ AlgorithmBellman-Ford

The routers are not aware of the topology of the network – only the distance to the destinations

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Open Shortest Path First (OSPF)

Each router floods information about the state of its links Every router has a complete map of the network topologyEvery router has a complete map of the network topology

◦ Routing metricN b f hNumber of hopsValue configured

l h◦ AlgorithmDijkstra

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Fast convergence without loops◦ Flooding◦ Flooding◦ Coherent maps of the network in all nodes

Support for multiple metricsSupport for multiple metrics◦ One network map for each metric

Support for multiple pathsSupport for multiple paths◦ Load balancing◦ QoS aware routing

Scalability◦ Hierarachical routing

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Sistema autónomo

ASBRÁrea A Área B

Área C

ABR ABR

ASBR

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Category Information Maintained Communication Partners

Information Distributed

Distance vector

Distance vectors for all destinations

Neighbour nodes Distance vectors for all destinations

Network weighted graph All nodes in the State of theLink state

Network weighted graph All nodes in the network

State of the individual links of each node

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Path Vector Protocols

◦ Border Gateway Protocol (BGP)

◦ Inter-Domain Routing Protocol (IDRP)

Why not Link State or Distance Vector?

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Distance-vector◦ Assumes all routers use the same routing metric◦ Policy information is not distributed

Link-state◦ Metrics may vary in different autonomous systemMetrics may vary in different autonomous system◦ Flooding between different autonomous systems is

very hard

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Routing information◦ Sequence of the autonomous systems to be

traversed to reach the destination◦ Policies may be used to choose autonomous systemPolicies may be used to choose autonomous system

to favor or to avoid

Without routing metrics◦ No problem of inconsistency between autonomous

systemssystems◦ No value for the cost to reach the destination

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Distributes information about the autonomous systems to be used to reach the destination

Initially, BGP routers exchange the complete routing tables

Afterwards only updates are distributed to the neighborAfterwards, only updates are distributed to the neighbor autonomous systems

Each message contains at least:◦ Source of the information (RIP, OSPF, …)◦ List of autonomous systems to reach the destination (AS-PATH)◦ Next Hop

If h h h h d i i hIf there are more than one path to the destination, the autonomous systems traversed may me analysed and the best one selected according to policies

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Routing protocol

Routing algorithm

Routing metrics

Routing scope

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Nowadays the Internet is used in almost all everyday situations, ranging from the simple email exchange and web browsing, through videoconferencing and distributed games upvideoconferencing and distributed games, up to distributed simulations and virtual reality.

This wide variety of applications has brought up the limitations of the best-effort service provided by the original Internet.

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Why Quality of Service?F li i◦ For applications

Improved performanceSeamless utilization

◦ For providersResource OptimizationOver-provisioning avoidancep g

◦ For usersCost controlUtilization of modern applicationsUtilization of modern applications

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IETF flavors◦ Integrated Services◦ Differentiated Services◦ Signaling◦ Signaling

RSVPNSIS

TechnologyIEEE 802 11◦ IEEE 802.11e◦ IEEE 802.16d◦ IEEE 802.16e

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Quality of Service routing aims at selecting suitable paths for the different types of trafficsuitable paths for the different types of traffic generated by diverse applications based on information about the state of the network with h bj i f i i h ffithe objectives of improving the traffic

performance and network resource utilization.

The first objective concerns the level of serviceoffered to the end-user.

The second objective pertains to the revenueobtained by Internet Service providers.

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Simplicity: minimize the number of signalling d h d d hmessages and the memory needed to store the

routing tables

Robustness: avoid forwarding errors that may lead to packet loss, loops and instability

Fast convergence time: react promptly to network changes and provide rapidly all routers with achanges and provide rapidly all routers with a consistent vision of the network

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Stability: adapt in a limited manner to the d i f h k i h i idynamic of the network without causing routing oscillations

Scalability: be able to scale to large networks and high traffic volumes

Resiliency: support alternate paths / mechanisms to be used in case of failureto be used in case of failure

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d ?How can we do it?

How much does it cost?How much does it cost?

Do we need it?

Is it feasible?

Why not overprovisioning?

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It’s all about metrics and algorithms!

◦ Anything else?

Besides, it is about applications, topologies, users, types of networks, ISP policies, business models, technologies, IETF, QoS models, … Q ,

You name it!

So, let’s start smoothly ☺

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Traditional routing algorithms

◦ Compute the shortest path to the destination

◦ All packets for a certain destination are forwarded to the same NH

How to support different QoS needs?

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To select paths suitable for traffic with diverse prequirementsImprove network utilization

QoS parametersTraffic requirements

D lExplicit QoSparameters

DelayJitter

Nº hopsLosses

Classes of service Bandwidth

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Quality of Service Routing (QoSR)Q y g (Q )

Multi-Constrained Path ProblemT fi d th P b t d d d h◦ To find a path P between nodes s and d, such as

( ) , 1, 2,...,i i

w P L i q≤ =

◦ wi(P) - weight of path P for metric i◦ Li – maximum metric value for a path to be

( )i i

q

Li maximum metric value for a path to be admissible

P is an admissible path35

P is an admissible path

AB

Restrictions (from A to B):

D l (D) 25 A il bl b d id h (BW) 60 36Delay (D) = 60

Routing granularitydd◦ Destination address

◦ Destination address, class of service◦ FlowRouting decision◦ Hop-by-hop◦ Source-basedSource basedPath computation◦ Pre-computation

O d d◦ On-demand◦ Hybrid

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Routing metricb f h◦ Number of hops

◦ Available bandwidth◦ DelayDelay◦ Losses◦ …

Algorithm◦ Distance vector◦ Distance vector◦ Link state◦ …

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Destination address◦ All the packets for the same destination are

forwarded to the same NH◦ No alternate paths are used

Destination address, class◦ All the packets of the same class for the same

destination are forwarded to the same NHdestination are forwarded to the same NH◦ Alternate paths per class

Flow

+ load balancing+ state+ complexityFlow

◦ All the packets of the same flow are forwarded to the same NH

+ complexity

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Hop-by-hop Sourcep y p+ Scalability+ Response time

Loops may occur

+ More complex algorithms can be used- Inaccuracy- Loops may occur

- Complex QoS routing - Inaccuracy- Scalability

Signaling is needed Most used for QoSR

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Pre-computation+ Setup time- Path computation for all requirements and destinations

On-demand+ Network state is up-to-datep+ Only the needed path is computed- Processing overhead if the request arrival rate is high

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QoSR: on-demand or hybrid approaches

1. Information distribution communication overheadoverhead

2. Metric selection path computation algorithm complexity

3 Routing table structure complexity and storage3. Routing table structure complexity and storage

4. Stability

5. Inaccuracy

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Which information?◦ TopologyTopology ◦ Resources available◦ Congestion state

H ?How?◦ LSAs extensions◦ Probing◦ SignalingSignaling

When?◦ Topology changes

N t k t t h◦ Network state changes◦ Periodically◦ When needed

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QoSR causes communication resource consumptionh h f f h d◦ the increase in the amount of routing information exchanged

◦ the amount and size of routing messages◦ the number of routers that must receive the routing messages

Trade-off: up-to-date data/communication overhead

Solutions◦ Quantification: average, moving average

Th h ld b d i i f d t◦ Threshold based emission of updates◦ Selective flooding◦ Hierarchical organization

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1. Information distribution communication h doverhead

2 Metric selection path computation algorithm2. Metric selection path computation algorithm complexity

3. Routing table structure complexity and storage

4 Stability4. Stability

5. Inaccuracyy

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Applications have multiple requirements

Paths must satisfy multiple requirementsPaths must satisfy multiple requirements

The complexity of the path computation algorithm depends on the composition rule of the metrics used

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Metric composition rulesp

∑=n

ilmpm )()(Additive Number of hops∑=i

ip1

)()( p

∏=n

ilmpm )()(Multiplicative Losses

nilpm 21)min()( ==Concave Bandwidth

∏=i

ip1

)()(p

nilpm i ,...,2,1),min()(Concave Bandwidth

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Problem◦ To find a path which satisfies two or more

additive or multiplicative constraints is NP-completecomplete◦ What can we do?

?

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Algorithmic Approaches

◦ Exact AlgorithmsNo complexity reduction, optimal solutions

◦ Heuristics AlgorithmsComplexity reduction, near optimal paths

◦ Hybrid AlgorithmsFlexible approach to be used under multiple circumstancescircumstances

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Bandwidth Restricted Paths (BRP)Bandwidth + additive metricBandwidth + additive metric

Metric orderingSequential filtering

Restricted Shortest Paths (RSP)2 additive metricsHeuristics

Metric orderingMetric combination

◦ Extensions to Bellman-Ford or Dijkstraalgorithms

H i i

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Heuristics:Reduce algorithm complexity/processing overhead

Metric ordering◦ To identify the most important metric◦ To select the best path according the first metric◦ In case of a tie, select the best path according to the p g

second metric

L d b l iShortest-widest path • Load balancing• Better performance with light load• Damages best-effort traffic performance

• Limit resource consumption• Better performance with high load• More resistent to routing information inaccuracy

Widest-shortest path

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Sequential filteringq g◦ To exclude all the links which have less bandwidth than

a certain threshold – Pruning policyOn-demand path computation: the request depicts theOn demand path computation: the request depicts the valuePath pre-computation: to establish value ranges

◦ To select the shortest path according to the second metric on the pruned graph

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Metric ordering◦ To find feasible paths according to one constraint◦ Select the best/optimal path according to the second

constraint

◦ Example: Delay-Constrained Least Cost (DCLC) problemNetwork: G(V,E)Network: G(V,E)Edge e = (u,v) ∈ E has two associated metrics: Cost - c(e) and Delay - d(e)Given a source node s and a destination node d, P(s, d) is the set of all paths from s to d.

∑∈

=iPe

i ecPc )()( ∑∈

=iPe

i edPd )()(' )(:)( PddsP d lΔ≤

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)(min),('

:

)(:),(

iDCLC

PddsP

PcdsPP

delayi

i∈

Δ≤

Metrics combinationGi ddi i i d l d( ) d◦ Given two additive metrics delay – d(e) and cost –c(e) for a link e ◦ Where α and β are the relative weights of each

imetric

+= edecew )()()( βα

∑∈

=

+=

PeewPw

edecew)()(

)()()( βα

◦ Do you find any problems with this approach?

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1. Information distribution communication overheadoverhead

2. Metric selection path computation algorithm complexity

3 Routing table structure complexity and storage3. Routing table structure complexity and storage

4. Stability

5. Inaccuracy

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Large routing tableLong look p◦ Long lookup

◦ Limited scalability

h d ?What to do?

◦ Store only the best pathy p◦ Use a normal routing table for BE and on-demand

path computation for QoS flows◦ Use class-based routingg

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Basic forwarding does destination-based packet classification and a corresponding Forwarding Information Base lookupand a corresponding Forwarding Information Base lookup

QoS-aware packet classification depends on the traffic classification used in the networkclassification used in the network◦ Flow classification - there is the need to keep in the FIB one entry

for each flow◦ MPLS networks - a layer two lookup is done and the classification◦ MPLS networks a layer two lookup is done and the classification

is only made using a label

SolutionsSolutions◦ Efficient packet classification◦ Fast hardware lookup methods of commercial routers

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5. Inaccuracyy

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Instability occurs when reaction is excessive

Sources of instability◦ Congestion based metricsCongestion based metrics◦ Update distribution policies◦ Network topology◦ Traffic patterns◦ Traffic patterns◦ Mobility

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Approaches to avoid instability

◦ Distribution of quantified metrics◦ Load balancing◦ Load balancing◦ Hybrid routing

Long duration flows: on-demandShort duration flows: pre-computation

◦ Route-pinning◦ Class-pinningClass pinning

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Advertisement of metrics that are quantified instead of advertising instantaneous valuesadvertising instantaneous values◦ Contributes to routing stability, but◦ Reduces the dynamic nature and the adaptation capabilities of the

routing protocol

◦ It is necessary to configure the mechanism of metrics quantification in order to achieve a fruitful trade-off between routing stability and routing adaptation

Two timescales for metrics evaluation◦ Long-term timescale, end-to-end delay information is used for

path pre-computationSh t t ti l l l i d l i f ti i d t◦ Short-term timescale, local queuing delay information is used to adjust the pre-computed paths to handle temporary traffic bursts without the need of computing all the paths in the network

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Hybrid routing (1)◦ Long duration flows: on-demand ◦ Short duration flows: pre-computation

◦ Dynamic routing is only used for long-lived flows reduces communication and processing overhead

◦ Long lived flows avoid successive path computations Long lived flows avoid successive path computations contributing to stability

Hybrid routing (2)Hybrid routing (2)◦ Long duration flows: smoothed metric◦ Short duration flows: actual metric

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5. Inaccuracyy

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It is desirable that the state kept at all routers remains up-to-date and that it reflects the complete and detailed state of the network

However, is this possible?

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Sources

◦ Reduced frequency of updates

◦ Information aggregation in hierarchical networks

◦ Delay introduced in large networks

◦ Utilization of estimatesUtilization of estimates

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Due to this wide range of factors, the global state that is kept by each router is just an approximation of the real actual state

When the path computation algorithms use this inaccurate information as if it was exactthis inaccurate information as if it was exact, their performance can be highly damaged

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Approaches

◦ State of the network represented as probability functionsfunctions

◦ Probing instead of flooding

◦ Multiple-path routing

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State of the network represented as probability ffunctions

◦ QoS routing algorithms that cope with inaccuracy in routingQoS routing algorithms that cope with inaccuracy in routing information need to be adapted to make path computation based on information that is neither complete nor exact.

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Problem Scheme Metrics AlgorithmBandwidth-C t i d P th

Logarithmic-BCP-ISI Logarithmic function of the probability th t li k d t

Shortest-Path Constrained Path under Inaccurate State Information (BCP-ISI)

that a link can accommodate a connection

(e.g. Dijkstra)

Relaxed-BCP-ISI Mean and variance of the bandwidth available in the link

Modified Dijkstra

Safety-Based-Routing(SBR) Safety metrics: estimation of the Safest-Shortest y g( ) ymaximum change of bandwidth until the next update

Sa est S o testPath or Shortest Safest Path

Delay-Constrained Path under

Basic-Delay-Constraint (BDC) p.d.f of the minimum delay the link can provide plus the propagation delay

Link-State for i lPath under

Inaccurate State Information (DCP-ISI)

provide plus the propagation delay special cases

Random-Basic-Delay-Constraint (RBDC)

Transformation of the mean and variance of the queuing delay

Modified Dijkstra

Transformed-Delay-Constraint (TDC) p.d.f of the available residual rate on the link

Algorithm min-PRlink PR

Bandwidth-Delay Constrained Path under Inaccurate State Information

Association of Relaxed-BCP-ISI and Random-Basic-Delay-Constraint

Mean and variance of the bandwidth available in each link and transformation of the mean and variance of the queuing delay

Link-State for special cases

(BDCP-ISI)

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Probing instead of flooding

◦ The utilization of probing avoids the staleness of link-state information because the probes gather the most recent state information.

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Multiple-path routingScheme Metrics AlgorithmRandom-Safety-Based-Routing (R-SBR) Safety metrics Randomized extension to Safest-

Shortest Path (Modified Bellman-Ford))

Randomized Bandwidth-Delay Constrained path (R-BDC) Safety metrics and delay (transformed in number of hops)

Randomized Multiple-path

Shortest-K-Widest Path (SKWP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra)

Widest-K-Shortest Path (WKSP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra)

R d K Wid t P th (RKWP)Random-K-Widest Path (RKWP) Bandwidth Pruned K-Shortest Path (Modified Dijkstra)

Bypass Based Routing (BBR) Obstruction metrics

Shortest-Obstruct-Sensitive Path (SOSP) and the Obstruct-Sensitive-Shortest-Path (OSSP)

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Shortest-Path (OSSP)Proportional Sticky Routing (PSR) Flow blocking

probability Weighted-Round-Robin-Like Path (WRRLP)

QoSR-DiffServQoSR complements DiffServ by selecting different paths for◦ QoSR complements DiffServ by selecting different paths for different traffic classes

◦ Traffic differentiation in routers performed by DiffServmechanismsmechanisms

QoSR-IntServ◦ QoSR selects paths for PATH messagesQoSR selects paths for PATH messages◦ RSVP reserves resources

QoSR-MPLSQoSR MPLS◦ QoSR selects paths◦ MPLS uses LDP to establish LSPs

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Intra-domain QoSRQ◦ Single administrative control◦ Flexible, efficient

Inter-domain QoSR◦ Multiple administrative control◦ Multiple administrative control◦ Simple, stable and inter-operational

Different requirements!

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BGP extensions◦ QoS support

Traffic control schemesTraffic control schemes◦ Internet-wide

Overlays◦ End-system

Multi-homingSmart routingSmart routing

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QoS BGP extensionsNew QoS attributes distributed in BGP UPDATE messages

Inband signalling results in low converge and instability problems Dynamic changes on network state are notDynamic changes on network state are not considered

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Traffic control schemes◦ Overlay network-based mechanisms

A large number of overlay entities is placed across several ASesThe role of these nodes is to periodically monitor the performance and availability of paths between them

However, since overlays do not control de beahaviour of the d l i i f t t Q S t t b dunderlying infrastructure, QoS support may not be ensured

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Traffic control schemes INC3Destination prefixes: p1, p2, p3, p4

Multi-homingConsists on the increase of Internet connectivity by contracting multiple broadband lines

INP1 4 5

6contracting multiple broadband lines

Smart Route Controller (SRC)1

3Used by multi-homed stub ASes, as they provide a holistic way to solve local end-to-end traffic challenges through shifting some traffic between ISP i h i l

INP2 INP3

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INP4

INP5

ISPs in short timescales

SRC SRC

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INC1 INC2

Pros:To find paths s itable for different t pes of traffic◦ To find paths suitable for different types of traffic

◦ Improve network utilization

CCons:◦ Communication, processing and storage overhead◦ Complex implementation◦ Instability may occur

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Routing Protocols

Routing metrics

Quality of Service Routing Protocols

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AKA table driven - From the “wired world”: Paths are pre computed◦ Paths are pre-computed

◦ Updates are exchanged periodically◦ For networks with low mobility and frequent data

transmissiontransmission

+ Response time- Communication overheadCommunication overhead- Processing overhead due to frequent path computation and

computation of “useless” paths to destinations which are not popular

DSDV - Highly Dynamic Destination-Sequenced Distance-Vector Routing OLSR - Optimized Link State Routing protocol

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AKA on demand – From the “signalling world”h d d◦ Paths are determined upon request

◦ For networks with high mobility and infrequent data transmission

+ Node lifetime+ Bandwidth since requests are only sent on demand- Bandwidth when flooding is used- Response time due to the route discovery mechanism

DSR- Dynamic Source Routing ProtocolAODV- Ad Hoc On-Demand Distance VectorDYMO - Dynamic MANET On-demand

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A combination of pro-active and reactivell d f d d d◦ Typically proactive in defined zones and reactive outside

+ The best of both worlds- Creation and management of zones/clusters

ZHLS - Zone-based Hierarchical Link StateZRP - Zone Routing ProtocolCBRP - Cluster Based Routing Protocol

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MAC parameters Has routing h◦ Traffic load

◦ Interference◦ Noise

anything to do with these?

◦ Noise◦ Topology

MAC performance can be considerably impacted by routing decisions

MAC / Routing Cross-layer

metrics

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metrics

Hop countE i+ Easy computation

- Does not consider the characteristics of wireless environments (different link transmission rates, loss

i )ratios)- Does not consider congestion level

Expected Transmission Count Metric (ETX)+ Takes into consideration link loss ratios and

interference between the successive links of a pathinterference between the successive links of a path- Does not consider different transmission rates- Does not include link utilization

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Expected Transmission Time (ETT) Intra-flow interference: Inter-flow interference:+ Evolution of ETX+ Takes into account link loss ratio and bandwidth- Does not consider channel interference

Intra flow interference:

Interference of adjacent links using the same channel

Inter flow interference:

Interference between multiple flows from one or multiple sources

Does not consider channel interference

Weighted Cumulative ETT (WCETT)+ Computes ETT over a path+ Considers intra-flow interference

Does not consider inter flow interference- Does not consider inter-flow interference

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Metric of Interference and Channel Switching (MIC)(MIC) + Considers intra-flow interference – channel diversity+ Considers inter-flow interference – ETT weighted by the g y

number of nodes it interferes with- Overhead needed to maintain up to date information- Does not consider traffic load in each nodeDoes not consider traffic load in each node

Multiple-path routing metricsh l l h ( )◦ Channel Aware Multipath (CAM)

◦ Weighted Interference Multipath (WIM)

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QoS extensions for AODV (QAODV)

QoS extensions to OLSR (QOLSR)

QoS extension to DYMO (DYMOQoS)

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Routing & mobility

Routing for resilience

Routing & cross-layer design

Routing and forwarding security in MANETs

Routing scalability

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Wireless networks disseminationk◦ Network types

Cellular Networks (with infrastructure)Ah Hoc NetworksSensor Networks

◦ Different technologiesUMTS802.11Bluetooth…

◦ Integration of technologies3rd and 4th Generation networks

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Challenges◦ Limitation of devices

Low processingLow resourcesLow resourcesLow memoryLow autonomy (energy)Radio interferenceRadio interference

◦ High mobilityInaccurate path information

◦ No centralized management

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In networks failures may occur:Due to:◦ Due to:

hardware degradationmalicious attacksmaintenance operationsmaintenance operationshuman errorsaccidentsnatural disasterstopology changes (mobility)

◦ For variable amounts of time:short-termed (transient failures)medium-termed failures (updates/reboots)long-termed failures (fibber cut)

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Check this paper:

◦ Ian F. Akyildiz, Xudong Wang, “Cross-Layer Design in Wireless Mesh Networks”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 57, NO 2 MARCH 2008NO. 2, MARCH 2008

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Study of Routing Mechanisms for Mobile Ad-hoc Networks – David PalmaQoS Routing in Wireless Mesh Networks –Vinicius BorgesVinicius BorgesInterference-aware Routing Metrics for Wireless Mesh Networks – Daniel PereiraWireless Mesh Networks Daniel PereiraAnalysis of Clustering Schemes for Mobile Ad-Hoc Networks – Luis ConceiçãoçRouting and Forwarding Security in WMNs –Viviane Lima and Vitor Ruivo

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Q3M - QoS Architecture for Multi-user Mobile Multimedia Sessions in 4G Systems

E Q S E d E d Q S S OEuQoS – End-to-End QoS Support OverHeterogeneous Networks

WEIRD – WiMAX Extensions to Isolated Data Research NetworksResearch Networks

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GINSENG◦ Performance Control in Wireless Sensor Networks

Use of WSNs in industrial environments where performance assurances are criticalperformance assurances are critical.

MICIE◦ Tool for systemic risk analysis and secure mediation of data

exchanged across linked CI information infrastructuresTo design and implement a so-called "MICIE alerting system" that o des g a d p e e t a so ca ed C a e t g syste t atidentifies, in real time, the level of possible threats induced on a given CI by "undesired" events happened in such CI and/or other interdependent CIs

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David Palma, Marilia Curado: "NODRoP, Nature Optimized Deferred Routing Protocol", INFOCOM'09, 28th Annual Joint Conference of the IEEE Computer and Communications Societies Student Workshop 2009Societies - Student Workshop, 2009

Alexandre Fonte, Marilia Curado, Edmundo Monteiro, “Interdomain quality of service routing: setting the grounds for the way ahead”, Annals of Telecommunications, Springer Paris, ISSN 0003-4347, Volume 63, Numbers 11-12 / December, 2008, pp 683-695

Daniel Pereira, Alicia Trivino Cabrera, Marilia Curado, “Analysis of Metrics for Routing Optimization in Wireless Mesh Networks”, International Workshop on Traffic Management and Traffic Engineering for the Future Internet (FITraMEn 08), Porto, Portugal, 11-12 December, 2008

Alexandre Fonte, José Martins, Marilia Curado, Edmundo Monteiro: Stabilizing Intelligent Route Control: Randomized Path Monitoring, Randomized Path Switching or History-Aware Path Switching?. In Proc. of MMNS 2008, Samos, Greece, September 2008

Masip-Bruin, X., M. Yannuzzi, J. Domingo-Pascual, A. Fonte, M. Curado, E. Monteiro, F. Kuipers, P. Van Mieghem, S. Avallone, G. Ventre, P. Aranda-Gutierrez, M. Hollick, R. Steinmetz, L. Iannone and K. Salamatian, 2006, "Research Challenges in QoS Routing", Computer Communications, Vol. 29, pp. 563-581.

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David Palma, Marilia Curado, “Inside-out OLSR Scalability Analysis” submitted to the 7th International Conference onAnalysis , submitted to the 7th International Conference on Wired / Wireless Internet Communications, University of Twente, The Netherlands, May 27-29, 2009

Viviane Lima, Vitor Ruivo, Marilia Curado, “Securing Wireless Mesh Networks: a Winning Combination of Routing and Forwarding Mechanisms” submitted to the First IFIPForwarding Mechanisms , submitted to the First IFIP Conference on Network and Service Security, Paris, France, June 24-26, 2009

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ili @d [email protected]://cisuc.dei.uc.pt/lct/

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2009 03 11 routing oslo - universitetet i oslo · `routing basics `quality of service routing...

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