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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Computer Networks II
QoS: Techniques and
Architectures
Giorgio Ventre
COMICS LAB
Dipartimento di Informatica e Sistemistica
Università di Napoli Federico II
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Nota di Copyright
Quest‟insieme di trasparenze è stato ideato e realizzato dai
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Dipartimento di Informatica e Sistemistica dell‟Università di
Napoli e del Laboratorio Nazionale per la Informatica e la
Telematica Multimediali. Esse possono essere impiegate
liberamente per fini didattici esclusivamente senza fini di lucro,
a meno di un esplicito consenso scritto degli Autori. Nell‟uso
dovrà essere esplicitamente riportata la fonte e gli Autori. Gli
Autori non sono responsabili per eventuali imprecisioni
contenute in tali trasparenze né per eventuali problemi, danni o
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Why better-than-best-effort (QoS-enabled) Internet ?
Quality of Service (QoS) building blocks
End-to-end protocols: RTP, H.323
Network protocols:» Integrated Services(IntServ), RSVP.
» Scalable differentiated services: DiffServ
Control plane: QoS routing, traffic engineering, policy management, pricing models
Overview
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Why Better-than-Best-Effort (QoS)?
To support a wider range of applications
» Real-time, Multimedia, etc
To develop sustainable economic models
and new private networking services
» Current flat priced models, and best-effort
services do not cut it for businesses
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Quality of Service: What is it?
Multimedia applications: network audio and video
network provides application with level of performance needed for application to function.
QoS
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
What is QoS?
“Better performance” as described by a set of parameters or measured by a set of metrics.
Generic parameters:
» Bandwidth
» Delay, Delay-jitter
» Packet loss rate (or loss probability)
Transport/Application-specific parameters:
» Timeouts
» Percentage of “important” packets lost
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
What is QoS (contd) ?
These parameters can be measured at
several granularities:
» “micro” flow, aggregate flow, population.
QoS considered “better” if
» a) more parameters can be specified
» b) QoS can be specified at a fine-granularity.
QoS spectrum:Best Effort Leased Line
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Fundamental Problems
In a FIFO service discipline, the performance
assigned to one flow is convoluted with the
arrivals of packets from all other flows!
» Can‟t get QoS with a “free-for-all”
» Need to use new scheduling disciplines which
provide “isolation” of performance from arrival rates
of background traffic
B
Scheduling DisciplineFIFO
B
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Fundamental Problems
Conservation Law
(Kleinrock): (i)Wq(i) = K
Irrespective of scheduling
discipline chosen:
» Average backlog (delay) is
constant
» Average bandwidth is
constant
Zero-sum game => need
to “set-aside” resources
for premium services
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
QoS Big Picture: Control/Data Planes
Internetwork or WANWorkstation
Router
Router
RouterWorkstation
Control Plane: Signaling + Admission Control or
SLA (Contracting) + Provisioning/Traffic Engineering
Data Plane: Traffic conditioning (shaping, policing, marking
etc) + Traffic Classification + Scheduling, Buffer management
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
QoS Components
QoS => set aside resources for premium
services
QoS components:
» a) Specification of premium services:
(service/service level agreement design)
» b) How much resources to set aside?
(admission control/provisioning)
» c) How to ensure network resource utilization,
do load balancing, flexibly manage traffic
aggregates and paths ?
(QoS routing, traffic engineering)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
QoS Components (Continued)
» d) How to actually set aside these resources in
a distributed manner ?
(signaling, provisioning, policy)
» e) How to deliver the service when the traffic
actually comes in (claim/police resources)?
(traffic shaping, classification, scheduling)
» f) How to monitor quality, account and price
these services?
(network mgmt, accounting, billing, pricing)
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
How to upgrade the Internet for QoS?
Approach: de-couple end-system evolution from network evolution
End-to-end protocols: RTP, H.323 etc to spur the growth of adaptive multimedia applications
» Assume best-effort or better-than-best-effort clouds
Network protocols: IntServ, DiffServ, RSVP, MPLS, COPS …
» To support better-than-best-effort capabilities at the network (IP) level
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
QOS SPECIFICATION, TRAFFIC, SERVICE CHARACTERIZATION, BASIC MECHANISMS
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Service Specification
Loss: probability that a flow‟s packet is lost
Delay: time it takes a packet‟s flow to get
from source to destination
Delay jitter: maximum difference between
the delays experienced by two packets of
the flow
Bandwidth: maximum rate at which the
soource can send traffic
QoS spectrum:
Best Effort Leased Line
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Hard Real Time: Guaranteed Services
Service contract
» Network to client: guarantee a deterministic
upper bound on delay for each packet in a
session
» Client to network: the session does not send
more than it specifies
Algorithm support
» Admission control based on worst-case analysis
» Per flow classification/scheduling at routers
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Soft Real Time: Controlled Load Service
Service contract:
» Network to client: similar performance as an
unloaded best-effort network
» Client to network: the session does not send
more than it specifies
Algorithm Support
» Admission control based on measurement of
aggregates
» Scheduling for aggregate possible
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Traffic and Service Characterization
To quantify a service one has two know
» Flow‟s traffic arrival
» Service provided by the router, i.e., resources reserved at each router
Examples:
» Traffic characterization: token bucket
» Service provided by router: fix rate and fix buffer space
– Characterized by a service model (service curve framework)
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Token Bucket
Characterized by three parameters (b, r, R)» b – token depth
» r – average arrival rate
» R – maximum arrival rate (e.g., R link capacity)
A bit is transmitted only when there is an available token
» When a bit is transmitted exactly one token is consumed
r tokens per second
b tokens
<= R bps
regulatortime
bits
b*R/(R-r)
slope R
slope r
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Characterizing a Source by Token Bucket
Arrival curve – maximum amount of bits transmitted by time t
Use token bucket to bound the arrival curve
time
bits
Arrival curve
time
bps
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Example
Arrival curve – maximum amount of bits transmitted by time t
Use token bucket to bound the arrival curve
size of time
interval
bitsArrival curve
time
bps
0 1 2 3 4 5
1
2
1 2 3 4 5
1
2
3
4
(b=1,r=1,R=2)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Per-hop Reservation
Given b,r,R and per-hop delay d
Allocate bandwidth ra and buffer space Ba such that to guarantee d
bits
b
slope rArrival curve
d
Ba
slope ra
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
What is a Service Model?
The QoS measures (delay,throughput,
loss, cost) depend on offered traffic, and
possibly other external processes.
A service model attempts to characterize
the relationship between offered traffic,
delivered traffic, and possibly other
external processes.
“external process”
Network elementoffered traffic
delivered traffic
(connection oriented)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Arrival and Departure Process
Network ElementRin Rout
Rin(t) = arrival process
= amount of data arriving up to time t
Rout(t) = departure process
= amount of data departing up to time t
bits
t
delay
buffer
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Traffic Envelope (Arrival Curve)
Maximum amount of service that a flow
can send during an interval of time t
slope = max average rate
b(t) = Envelope
slope = peak rate
t
“Burstiness Constraint”
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Service Curve
Assume a flow that is idle at time s and it is
backlogged during the interval (s, t)
Service curve: the minimum service
received by the flow during the interval (s, t)
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Big Picture
t t
slope = C
t
Rin(t)
Service curvebits bits
bits
Rout(t)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Delay and Buffer Bounds
t
S (t) = service curve
E(t) = Envelope
Maximum delay
Maximum buffer
bits
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Mechanisms: Traffic Shaping/Policing
Token bucket: limits input to specified Burst Size (b) and Average Rate (r).» Traffic sent over any time T <= r*T + b
» a.k.a Linear bounded arrival process (LBAP)
Excess traffic may be queued, marked BLUE, or simply dropped
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Mechanisms: Queuing/Scheduling
Use a few bits in header to indicate which queue (class) a packet goes into (also branded as CoS)
High $$ users classified into high priority queues, which also may be less populated
=> lower delay and low likelihood of packet drop
Ideas: priority, round-robin, classification, aggregation, ...
Class C
Class B
Class A
Traffic
Classes
Traffic
Sources
$$$$$$
$$$
$
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Mechanisms: Buffer Mgmt/Priority Drop
Ideas: packet marking, queue thresholds,
differential dropping, buffer assignments
Drop RED and BLUE packets
Drop only BLUE packets
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
SCHEDULING
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Packet Scheduling
Decide when and what packet to send on
output link
» Usually implemented at output interface
1
2
Scheduler
flow 1
flow 2
flow n
Classifier
Buffer
management
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Focus: Scheduling Policies
Priority Queuing: classes have different priorities; class may depend on explicit marking or other header info, eg IP source or destination, TCP Port numbers, etc.
Transmit a packet from the highest priority class with a non-empty queue
Preemptive and non-preemptive versions
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Scheduling Policies (more)
Round Robin: scan class queues serving one from
each class that has a non-empty queue
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Round-Robin Discussion
Advantages: protection among flows» Misbehaving flows will not affect the performance
of well-behaving flows– Misbehaving flow – a flow that does not implement any
congestion control
» FIFO does not have such a property
Disadvantages:» More complex than FIFO: per flow queue/state
» Biased toward large packets – each flow receives service proportional to the number of packets it sends (multiplied by the bytes carried by packets).
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Generalized Processor Sharing(GPS)
Assume a fluid model of traffic
» Visit each non-empty queue in turn (RR)
» Serve infinitesimal from each
» Leads to “max-min” fairness
GPS is un-implementable!
» We cannot serve infinitesimals, only packets
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Weighted Fair Rate in GPS
A work conserving GPS is defined as
where» wi – weight of flow i
» Wi(t1, t2) – total service received by flow i during [t1, t2)
» W(t1, t2) – total service allocated to all flows during [t1, t2)
» B(t) – number of flows backlogged
)(),(),(
)(
tBiw
dtttW
w
dtttW
tBj ji
i
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Weighted Fair Rate Computation in GPS
Associate a weight wi with each flow i
If link congested, compute f such that
Cwfr i
i
i ),min(
8
6
2
26
2
f = 2: min(8, 2*3) = 6
min(6, 2*1) = 2
min(2, 2*1) = 2
10(w1 = 3)
(w2 = 1)
(w3 = 1)
Bit x bit Round Robin
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Bit-by-bit Round Robin when dealing with Packets
Single flow: clock ticks when a bit is transmitted. For packet i:
» Pi = length, Ai = arrival time, Si = begin transmittime, Fi = finish transmit time
» Fi = Si+Pi = max (Fi-1, Ai) + Pi
Multiple flows: clock ticks when a bit from all active flows is transmitted round number
» Can calculate Fi for each packet if number of flows is known at all times
– This can be complicated
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Standard techniques of approximating fluid GPS» Select packet that finishes first in GPS assuming
that there are no future arrivals
Important properties of GPS» Finishing order of packets currently in system
independent of future arrivals
Implementation based on virtual time» Assign virtual finish time to each packet upon
arrival
» Packets served in increasing order of virtual times
Packet Approximation of Fluid System
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Fair Queuing (FQ)
Idea: serve packets in the order in which they would have
finished transmission in the fluid flow system
Mapping bit-by-bit schedule onto packet transmission
schedule
Transmit packet with the lowest Fi at any given time
Variation: Weighted Fair Queuing (WFQ)
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Approximating GPS with WFQ
Fluid GPS system service order
0 2 104 6 8
Weighted Fair Queueing
» select the first packet that finishes in GPS
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
FQ Example
F=10
Flow 1
(arriving)
Flow 2
transmittingOutput
F=2
F=5
F=8
Flow 1 Flow 2 Output
F=10
Cannot preempt packet
currently being transmitted
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
FQ Advantages
FQ protect well-behaved flows from ill-behaved flows
Example: 1 UDP (10 Mbps) and 31 TCP‟s sharing a 10 Mbps link
FQ
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1 4 7 10 13 16 19 22 25 28 31
Flow NumberT
hro
ug
hp
ut(
Mb
ps
)RED
0
1
2
3
4
5
6
7
8
9
10
1 4 7 10 13 16 19 22 25 28 31
Flow Number
Th
ro
ug
hp
ut(
Mb
ps
)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Big Picture
FQ does not eliminate congestion it just
manages the congestion
You need both end-host congestion control
and router support for congestion control
» end-host congestion control to adapt
» router congestion control to protect/isolate
Don‟t forget buffer management: you still
need to drop in case of congestion. Which
packet‟s would you drop in FQ?
» one possibility: packet from the longest queue
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Parekh-Gallager theorem
Let a connection be allocated weights at each
WFQ scheduler along its path, so that the least
bandwidth it is allocated is g
Let it be leaky-bucket regulated such that # bits
sent in time [t1, t2] <= g(t2 - t1) +
Let the connection pass through K schedulers,
where the kth scheduler has a rate r(k)
Let the largest packet size in the network be P
1
1 1
)(///___K
k
K
k
krPgPgdelayendtoend
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Significance
P-G Theorem shows that WFQ scheduling can provide end-to-end delay bounds in a network of multiplexed bottlenecks
» WFQ provides both bandwidth and delayguarantees
» Bound holds regardless of cross traffic behavior (isolation)
» Needs shapers at the entrance of the network
Can be generalized for networks where schedulers are variants of WFQ, and the link service rate changes over time
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
QoS ARCHITECTURES
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateless vs. Stateful QoS Solutions
Stateless solutions – routers maintain no fine
grained state about traffic
scalable, robust
weak services
Stateful solutions – routers maintain per-flow state
powerful services
– guaranteed services + high resource utilization
– fine grained differentiation
– protection
much less scalable and robust
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Existing Solutions
Stateful Stateless
QoS
Tenet [Ferrari &
Verma ‟89]
IntServ [Clark et al
‟91]
ATM [late ‟80s]
DiffServ
- [Clark &
Wroclawski „97]
- [Nichols et al ‟97]
Network
support for
congestion
control
Round Robin [Nagle
‟85]
Fair Queueing
[Demers et al ‟89]
Flow Random Early
Drop (FRED) [Lin &
Morris ‟97]
DecBit [Ramkrishnan &
Jain ‟88]
Random Early Detection
(RED) [Floyd & Jacobson
‟93]
BLUE [Feng et al ‟99]
REM [Low at al ‟00]
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Integrated Services (IntServ)
An architecture for providing QOS guarantees in IP
networks for individual application sessions
Relies on resource reservation, and routers need to
maintain state information of allocated resources (eg:
g) and respond to new Call setup requests
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Signaling semantics
Classic scheme: sender initiated
SETUP, SETUP_ACK, SETUP_RESPONSE
Admission control
Tentative resource reservation and confirmation
Simplex and duplex setup; no multicast support
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
RSVP: Internet Signaling
Creates and maintains distributed reservation
state
De-coupled from routing:
» Multicast trees setup by routing protocols, not RSVP
(unlike ATM or telephony signaling)
Receiver-initiated: scales for multicast
Soft-state: reservation times out unless refreshed
Latest paths discovered through “PATH”
messages (forward direction) and used by RESV
mesgs (reverse direction).
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Call Admission
Session must first declare its QoS
requirement and characterize the traffic it
will send through the network
R-spec: defines the QoS class assigned
T-spec: defines the traffic characteristics
A signaling protocol is needed to carry the
R-spec and T-spec to the routers where
reservation is required; RSVP is a leading
candidate for such signaling protocol
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Call Admission
Call Admission: routers will admit calls based on
their R-spec and T-spec and based on the current
resource allocated at the routers to other calls.
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
Achieve per-flow bandwidth and delay guarantees
» Example: guarantee 1MBps and < 100 ms delay to a flow
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
Allocate resources - perform per-flow
admission control
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
Install per-flow state
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
SenderReceiver
Challenge: maintain per-flow state
consistent
Stateful Solution: Guaranteed Services
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
Per-flow classification
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
Per-flow buffer management
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution: Guaranteed Services
SenderReceiver
• Per-flow scheduling
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateful Solution Complexity
Data path
» Per-flow classification
» Per-flow buffer
management
» Per-flow scheduling
Control path
» install and maintain
per-flow state for
data and control paths
Classifier
Buffer
management
Scheduler
flow 1
flow 2
flow n
output interface
…
Per-flow State
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Stateless vs. Stateful
Stateless solutions are more
» scalable
» robust
Stateful solutions provide more powerful
and flexible services
» guaranteed services + high resource utilization
» fine grained differentiation
» protection
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Question
Can we achieve the best of two worlds, i.e., provide services implemented by stateful networks while maintaining advantages of stateless architectures?
» Yes, in some interesting cases. DPS, CSFQ.
Can we provide reduced state services, I.e., maintain state only for larger granular flows rather than end-to-end flows?
» Yes: Diff-serv
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Differentiated Services (DiffServ)
Intended to address the following difficulties with Intserv and RSVP;
Scalability: maintaining states by routers in high speed networks is difficult due to the very large number of flows
Flexible Service Models: Intserv has only two classes, want to provide more qualitative service classes; want to provide „relative‟ service distinction (Platinum, Gold, Silver, …)
Simpler signaling: (than RSVP) many applications and users may only want to specify a more qualitative notion of service
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Differentiated Services Model
Edge routers: traffic conditioning (policing, marking,
dropping), SLA negotiation
» Set values in DS-byte in IP header based upon negotiated
service and observed traffic.
Interior routers: traffic classification and forwarding
(near stateless core!)
» Use DS-byte as index into forwarding table
Ingress
Edge Router
Egress
Edge Router
Interior Router
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Diffserv Architecture
Edge router:
- per-flow traffic management
- marks packets as in-profile and out-profile
Core router:
- per class TM
- buffering and scheduling
based on marking at edge
- preference given to in-profile packets- Assured Forwarding
scheduling
...
r
b
marking
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Packet format support
Packet is marked in the Type of Service
(TOS) in IPv4, and Traffic Class in IPv6:
renamed as “DS”
6 bits used for Differentiated Service Code
Point (DSCP) and determine PHB that the
packet will receive
2 bits are currently unused
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Traffic Conditioning
It may be desirable to limit traffic injection
rate of some class; user declares traffic
profile (eg, rate and burst size); traffic is
metered and shaped if non-conforming
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Per-hop Behavior (PHB)
PHB: name for interior router data-plane functions
» Includes scheduling, buff. mgmt, shaping etc
Logical spec: PHB does not specify mechanisms
to use to ensure performance behavior
Examples:
» Class A gets x% of outgoing link bandwidth over time
intervals of a specified length
» Class A packets leave first before packets from class B
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
PHB (contd)
PHBs defined:
» Expedited Forwarding: departure rate of packets from a class equals or exceeds a specified rate (logical link with a minimum guaranteed rate)
– Emulates leased-line behavior
» Assured Forwarding: 4 classes, each guaranteed a minimum amount of bandwidth and buffering; each with three drop precedence partitions
– Emulates frame-relay behavior
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Scalable Core (SCORE)
A trusted and contiguous region of network in
which
» edge nodes – perform per flow management
» core nodes – do not perform per flow management
core nodes edge nodes
edge nodes
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
SLA Definitions Today
SLA statistical definitions do matter» min/avg/max versus percentile
» Measured time interval
» interval between probes
» Point-to-point vs. point-to-multipoint vs. multipoint-to-multipoint
SLAs definitions today tend to be loose» averaged over a month
» averaged over many POP-to-POP pairs (temptation to add short pairs to reduce average…)
» Round-trip
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Deploying Tight-SLA services on an IP Backbone
Number of tools are available to enable tight SLA services to be offered
» Physical network design and topology
» Diffserv: per-hop congestion management– Applying differential queuing and scheduling
mechanism to implement a differentiated SLA scheme
» Capacity planning and active monitoring
» Tuning IGP Convergence– slow convergence upon link/node failure directly
impacts SLAs
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Deploying Tight-SLA services on an IP Backbone
Number of tools are available to enable tight SLA
services to be offered (contd …)
» Traffic engineering: avoid aggregation on
shortest path
– IP aggregation on the shortest path can cause sub
optimal use of resources, and can impact SLAs
» Fast ReRoute (FRR) Protection
– FRR can be used to protect key resources and
provide rapid restoration for tight SLAs
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
The key for controlling Loss, Latency and Jitter: Provisioning!
The service that traffic receives is dependent
upon the ratio of traffic load to available capacity
More Bandwidth (offer) than traffic (demand)
means
» Low loss
» Low Latency
» Low Jitter
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-Provisioned Backbone
Over provision by ~2x the max. aggregate
traffic load
» Refs: {BONALD, CASNER, CHARNY}
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-provisioning (Source: Stephen Casner, Packet Design, NANOG 22)
Jitter Measurement Summary
for the Week
69 million packets transmitted
Zero packets lost
100% jitter < 700s
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-provisioned Backbone
Effective
Simple» Available bandwidth > aggregate traffic
demand
» QoS mechanisms kept at to edge
» Network is simple to design, deploy and operate
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Overprovisioned Backbone - Drawback
Risk related to provisioning failure
No service isolation» VPN, VoIP, Internet: same fate!
Expensive» design for the aggregate!!!
» Internet receives the same quality as VoIP
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
99.99%
“Not every week is like this”(Source: Stephen Casner, Packet Design, NANOG 22)
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-provisioning – Expensive
Aggregate bandwidth overprovision comes at a cost, however:» e.g. 150Mbps of VoIP and 1.5Gbps of data
between two POPs
» 1.65Gbps of aggregate load
» requires 3.3Gbps of bandwidth for 2x over-provisioning
» typically provisioned using 2x STM16/OC48
» hence 5Gbps of bandwidth used tosupport 1.65Gbps aggregate load with 150Mbps of low delay, low jitter, low loss traffic
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Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-provisioning – Expensive
Dipartimento di Informatica e Sistemistica, Università di Napoli Federico II Computer Networks II – a.a. 2009/2010
Over-provisioning – Expensive