proportional differentiations provisioning packet scheduling & buffer management
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Proportional differentiations provisioning Packet Scheduling & Buffer Management
Yang ChenLANDER CSE Department
SUNY at Buffalo
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Outlines
Motivations and termsProportional differentiationImplementations and related issuesConclusion and Future works
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Quality of Service (QoS)
What is QoS? A measurement of how well the network
behaves and an attempt to define the characteristic and properties of specific services.
Who need QoS? User:
More applications have strict service requirements: low packet loss rate, short delay, etc;
Network operator: Resource in a network must be used efficiently;
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Intserv
Integrated Service Try to achieve per-flow, end to end
service guarantees; Per-flow state is kept at intermediate
router; Admission control, resource
reservation and corresponding signaling are required;
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Diffserv
Differentiated Service Aggregate individual flows with
similar QoS requirements; No complex signaling; Can be implemented gradually (on
the congested links);
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Differentiated Service
Absolute (quantitative) Provide a macro-flow with a
quantitative performance level.
Relative (qualitative) Provide a number of classes with
increasing performance.
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Primary Tradeoffs
Fairness Access to excess capacity
Isolation Protection from excess traffic from other users
Efficiency Number of flows that can be accommodated
for a given level of service
Complexity In terms of implementation and control
overhead
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QoS metrics of interest in packet networks
Average packet delayPacket loss rateDeadline violation probabilityJitterEtc….
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Scheduling and buffer management
Scheduling Support service differentiation on bandwidth
by controlling the actual transmission of packet.
Take effect on time-related QoS metrics.
Buffer management Support service differentiation on buffer by
deciding which packet can be stored for future transmission.
Take effect on loss-related QoS metrics.
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Outlines
Motivations and termsProportional differentiationImplementations and related issuesConclusion and Future works
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Proportional Differentiation
DefinitionIf qi is the QoS metric of interest, and si is the differentiation factor for class i, we have:
)...1,( Njis
s
q
q
j
i
j
i
For example: Given two classes 1 and 2, and the QoS metric is packet loss rate, s1=1; s2=2, the packet loss rate of class 2 should be twice that of the loss rate of class 1.
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Proportional Differentiation
Pros Controllable
Differentiation level between service classes can
be controlled by network operator; Predictable
Performance of higher classes is consistently better than the performance of lower Class
even in short time scale;
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Outlines
Motivations and termsProportional differentiationImplementations and related issuesConclusion and Future works
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Recall: QoS metrics of interest
Average packet delayPacket loss rateDeadline violation probabilityJitterEtc….
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Proportionally differentiated packet delay
Waiting Time Priority (WTP) Scheduling
One packet need to be scheduled
On-line priority measurement
is done
Class 0
Class 1
Class N
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Class 0
Class 1
Class NClass 1 has the highest priority
Proportionally differentiated packet delay
Waiting Time Priority (WTP) Scheduling
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Proportionally differentiated packet delay
Wait Time Priority (WTP) Scheduling Suppose class i is backlogged at time
t, and that wi(t) is the head waiting time of class i at t;
We have normalized head waiting time of class i at t as:
When a packet need to be scheduled, a backlogged class j is selected for
iii stwtw /)()(~
)(~max arg)(
twj itBi
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Proportionally differentiated packet delay
Proportional Average Delay schedulingHybrid Proportional Delay schedulingBacklog Proportional Rate schedulingEtc….
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Proportionally differentiated loss rate
Buffer Management
Class 0
Class 1
Class 2
Total buffer size 20
One packet arrives
On-line priority
measurement is done
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Proportionally differentiated loss rate
Buffer Management
Class 0
Class 1
Class 2
Total buffer size 20
Class 0 has the lowest priority
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Proportionally differentiated loss rate
Buffer Management
Class 0
Class 1
Class 2
Total buffer size 20
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Proportionally differentiated loss rate
Proportional Loss Rate (PLR) dropper Suppose there are two counters for each
class i, counter ai records packet arrival history of class i, counter di records packet drop history of class i;
We have normalized packet loss rate of class i as:
When a packet needs to be dropped, a backlogged class j is selected for
)/(~
iiii sadl
)(~
min arg)(
tlj itBi
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Proportionally differentiated loss rate
PLR() Using the entire packet loss history
PLR(M) Using the most recent M packet entry
PLR with active resetting Using the most recent packet entry with variable
history length within a limited deviation on proportional relations
Predicting the average drop distance di is the average number of successfully forwarded
packets between two packet drops, loss rate li is 1/di;
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Loss rate and Packet delay
Fluid flow assumption Service rate of class i is ri; Loss rate of class i is li;
An optimization problem is formulated with Objectives:
Minimum service rate changes ri; Minimum loss rate li;
Constraints: Proportional relations on loss rates and packet
delays of different service class;
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Deadline violation probability
Motivation Performance of multimedia applications do
not depend on average delay much but on the probability that the transmission delay exceeds a certain threshold
Deadline Each class i is associated with a delay bound
i. A packet of class i arriving at time tA will
receive a tag tA+ i as its deadline.
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Deadline violation probability
Earliest Deadline First (EDF)/Earliest Deadline Due schedulerShortest Time to Extinction (STE) schedulerCons: Only provide different deadline for each
service class, no differentiation for deadline violation probability, which is an important factor on some real-time application’s performance, e.g., Voice over IP.
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Deadline violation probability
Weighted EDF/EDD Provides differentiated deadline
violation probability.If the scheduler is in “congested mode” ,
WEDF scheduler is applied
Class 0
Class 1
Class N
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Deadline violation probability
“Congested Mode” There are more than one backlogged
class with the first packet with a deadline tA+i<ts+i (ts is the system time, i is a safety margin, e.g., i = i/10).
WEDF scheduler In “congested Mode”, a class j with
largest normalized measurement-based deadline violation probability is served.)/)((max arg
)(ii
tBistvpj
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Proportionally differentiated Jitter
Jitter Jitter of one packet is the difference of
this packet’s queueing delay and the delay of preceding packet.
Motivation Jitter will affect the performance of
both interactive and non-interactive applications involving digital continuous media.
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Proportionally differentiated Jitter
The long time average jitter for served packets of each class is recorded as ji*(t);The minimum jitter for all the packets in the queue is calculated as jimin(t)The average jitter for class i is:
)}()({
)()()(
min*
tqtn
tjtjtj
ii
ii
Where: ni(t): the packet of class i been served; qi(t): the packet of class i in the queue.
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Proportionally differentiated Jitter
Normalized average jitter
When a packet need to be scheduled, a backlogged class j is selected for
iii stjtj /)()(~
)(~
(max arg)(
tjj itBi
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Problems in the implementation
Problems Delay/Jitter differentiation
Difficult to provide accurate proportional differentiation on both long time and short time periods;
Hybrid solution will introduce extra computation; Loss rate/violation probability
Keeping the entire loss/violation history will give accurate only on long term average;
Keeping the most recent history will help the system to achieve accurate differentiation on short time period but requires extra hardware and operation.
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Feasibility Problem in this QoS model
Feasible A set of proportional factors is
feasible when there exists a work-conserving scheduler that can set the differentiation level as this set specifies.
Feasibility depends on traffic profile: total load and percentage of each class.
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Feasibility Problem in this QoS model
Analysis on average delay Conservation Law
N
iagiii qLd
1
N
n nnn
agii
Ls
qsd
1
Assume all classes have the same packet size distribution as 1.
N
n nn
agii
s
qsd
1
nn sssddd :::: 2121
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Feasibility Problem in this QoS model
Analysis on average delay (cont.) There is a lower bound for delay of each
class. This lower bound would result if that
class was given strict priority over the rest of the traffic
Given a steady traffic profile, one method has been proposed to figure out the feasible region of proportional factors
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Feasibility Problem in this QoS model
Assume all classes have the same packet size distribution. The necessary and sufficient feasibility conditions are N-1 inequalities
NkddN
ki
N
kii
SPNkii ,,2 ,
Where are the average delay for service classes from k to N, which are given the strict priority over all other Service classes. All the values of can be achieved either experimentally or theoretically.
SPNkd ,
SPNkd ,
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Feasibility Problem in this QoS model Assume there are two service classes:
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Outlines
Motivations and termsProportional differentiationImplementations and related issuesConclusion and Future works
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Conclusion
Proportional differentiation is versatile. This QoS model can be implemented on
various QoS metrics;
Proportional differentiation is controllable. The level of differentiation can be adjusted by
setting different proportional factors;
Proportional differentiation is predictable. It can keep the proportional relations even in
short time period;
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Conclusion
However In order to provide finer
differentiation, as a tradeoff, complexity increases in terms of implementation and control overhead.
Infeasibility situation exists on some traffic profiles with no efficient solution.
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Future worksFeasibility testing How to judge whether the proportional factors
are properly in a dynamic traffic condition?
Class selection How to selection a service class for a particular
traffic flow in order to fulfill end-to-end/absolute QoS requirements?
Class provisioning Given traffic conditions and proportional
factors, how much resource shall we provide?
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Main ReferencesC. Dovrolis and D. Stiliadis and P. Ramanathan“Proportional Differentiated Services: Delay Differentiation and Packet Scheduling.”C. Dovrolis and P. Ramanathan“Proportional Differentiated Services, Part II: Loss Rate Differentiation and Packet Dropping.”J. Liebeherr and N. Christin“Buffer Management and Scheduling for Enhanced Differentiated Service”S. Bodamer“A New Scheduling Mechanism to Provide Relative Differentiation for Real-Time IP Traffic.”T. Quynh, et al. “ Relative Jitter Packet Scheduling for Differentiated Services”
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Q&A
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