1. Offset-Time-Based QoS Scheme
Extend JET to achieve isolation of traffic classes
The burst blocking probability of a priority class is independent of the offered load from the lower-priority classes
Basic idea: give a larger extra offset time to a higher priority class
Reservation for a higher priority burst has a better chance to succeed.
Burst assembly: multiple IP packets are assembled into a burst based on their destination address and priority class
can be made in much advance than lower priority bursts

2. Offset-Time-Based QoS Scheme
Assume two classes of services: class 0 and class 1 (class 1 has higher priority)
An extra offset time is given to class 1 traffic, but not to class 0 traffic
Assume the base offset time is negligible compared to the extra offset time
Assume a link has only one wavelength for data and an additional wavelength for control
Notations:
req(i) : class i request, i = 0,1
: the arriving time for req(i)
: the service start time for req(i)
: the burst length requested by req(i)

3. Offset-Time-Based QoS Scheme
A class 1 request can obtain a higher priority for wavelength reservation than a class 0 request
Case 1: req(1) comes before req(0)
Req(1) will succeed
Req(0) will be blocked if and , or

4. Offset-Time-Based QoS Scheme
Case 2: req(0) comes before req(1)
When , req(1) would be blocked if
The blocking can be avoided by using a large enough offset time so that
needs to be larger than the maximum burst length in class 0

5. Offset-Time-Based QoS Scheme

6. Offset-Time-Based QoS Scheme
When extra offset time for req(1) is large enough:
The blocking probability of class 1 is only a function of the offered load belonging to class 1
The blocking probability of class 0 depends on the offered load belonging to both classes
Extend to n (n>2) classes
An extra offset time is given to class i traffic (0 < i  n)
Assume burst duration has exponential distribution, when
, the probability that req(i) will not be blocked by req(i-1) is 95% (L = average duration of a burst in class i-1)

7. Other QoS Schemes: Intentional Dropping
Problems of offset-time-based QoS scheme
The extra offset time introduces an additional delay at the edge
Performance of differentiation depends on the burst length
Unfair to long bursts belonging to low priority classes
Intentional dropping [Chen et al, Globecom 01]
Address the problems of offset-time-based QoS scheme
Bursts are selectively dropped according to loss rate measurement to achieve proportional burst loss probability
Density function f(x) = lambda*e^(-lambda*x), mean = 1/lambda

8. Intentional Dropping Proportional QoS model: want Notations
lossratei : the burst loss rate of class i
si : proportional factor associated with class i, set by service provider
Notations
lossi : bursts dropped of class i
arrivali : bursts arrival of class i
ERROR : a parameter that controls the accuracy of proportional relations
lossratei = lossi / arrivali : online blocking probability measurement for class i;

9. The Algorithm

10. The Algorithm
Resetting counters from time to time ensures that the online measurement is done over the most recent traffic history

11. Other QoS Schemes: Burst Segmentation
Achieve differentiation at the packet level
Packets from low priority service classes are assembled to form the tail or head of each burst
Packets from high priority service classes are assembled in the middle of each burst.
Segment at the tail or head of a burst that overlaps with another burst are dropped when contention happens

12. Burst Scheduling Algorithms
Assume nodes have wavelength conversion capability
Job of burst scheduler
Choose a proper wavelength for the burst considering the existing reservations made on each wavelength
Make a new reservation on the selected channel

13. Horizon Also called LAUC (latest available unscheduled channel)
For each wavelength, the scheduling horizon is maintained
Scheduling horizon: the latest time at which the wavelength is currently scheduled to be in use
The channels whose scheduling horizon precede the new burst’s arrival time are considered available
An available channel with the latest scheduling horizon is chosen
Minimize the gap created
Drawback: waste gaps between two existing reservations

14. LAUC with Void Filing (LAUC-VF)
Given a data burst with arrival time t and duration L
Find the outgoing channels that are available for the time period of (t, t+L).
If there is at least one such channel, select the latest available channel, i.e., the channel having the smallest gap between t and the end of last data burst before t
Minimize the void generated between the start of new reservation and an existing reservation

15. Variants of LAUC-VF
Min-EV (Ending Void): try to maximize the new void generated between the end of new reservation and an existing reservation
Best Fit: try to minimize the total length of starting and ending voids generated after the reservation
LAUC-VF and its variants have comparable bandwidth utilization that is much higher than Horizon

16. Illustration of Scheduling Algorithms

17. Contention Resolution
Contention occurs when burst scheduler can’t find an available channel for the new burst
Ways to resolve contention
Deflection
Dropping
Preemption
Burst segmentation

18. Deflection
A burst is sent to a different output channel instead of the preferred one
Deflection can be applied in wavelength, space, and time domains
Wavelength domain: the burst is sent on another wavelength through wavelength conversion
Space domain: the burst is sent to a different output port
Time domain: the burst is delayed for a fixed time by passing through an FDL

19. Dropping/Preemption/Burst Segmentation
If a burst can’t be deflected, it can be dropped
An incoming burst can preempt an existing burst
Burst segmentation: segment at the tail or head of a burst that overlaps with another burst is dropped or deflected