Multicast traffic scheduling in single hop wdm networks with tuning latencies
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Multicast Traffic Scheduling in Single-Hop WDM Networks with Tuning Latencies. Ching-Fang Hsu Department of Computer Science and Information Engineering National Cheng Kung University June 2004. Outline. Network Model QoS Parameters Multicast QoS Traffic Scheduling Algorithm

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Multicast Traffic Scheduling in Single-Hop WDM Networks with Tuning Latencies

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Multicast traffic scheduling in single hop wdm networks with tuning latencies

Multicast Traffic Scheduling in Single-Hop WDM Networks with Tuning Latencies

Ching-Fang Hsu

Department of Computer Science and Information Engineering

National Cheng Kung University

June 2004


Outline

Outline

  • Network Model

  • QoS Parameters

  • Multicast QoS Traffic Scheduling Algorithm

  • The Maximum Assignable Slots (MAS) Problem

  • The Optimal MAS Solution

  • Near-optimal Solutions to The MAS Problem

  • Performance Evaluation

  • Conclusions


Network model

Network Model

  • A broadcast-and-select star-coupler topology is considered.


Network model contd

Network Model (contd.)

  • Transmission in the network operates in a time-slotted fashion.

  • The normalized tuning delay , is expressed in units of cell duration.

  • All transceivers are tunable over all wavelengths with the same delay.

    • Each station is equipped with a pair of fixed transceivers (control channel) and a pair of tunable transceivers (data channel).


Qos parameters

QoS Parameters

  • CBR and ABR traffic types are considered.

  • Multicast virtual circuits (MVC’s)

  • A 2-tuple notation <c, d> to describe cell rate

    • c is the maximum number of slots that can arrive in any d slots.

    • For CBR transmission, d is also the relative deadline, i.e., a cell of a CBR MVC must be sent before slot t+d if it arrives in slot t

    • For an ABR VC, <c, d> just means that slots within a L-slot period should be assigned to it.


Qos parameters contd

QoS Parameters (contd.)

  • Minimum cell rate (MCR) and peak cell rate (PCR)

    • For a CBR MVC, MCR=PCR

  • 6-tuple notation to identify a MVC

    • <cm, dm, cp, dp, s, M>

      • MCR, PCR, the source ID, and the set of destination Ids

      • For a CBR MVC, < cp, dp > = <-1, -1>


Qos parameters contd1

QoS Parameters (contd.)

  • Each CBR MVC has its own deadline (dm), or local cycle length.

  • Global cycle length -- the period of a traffic scheduling containing CBR traffic

    • L=lcm(), where  { | is the local cycle length of MVCi's MCR}


Multicast traffic scheduling in single hop wdm networks with tuning latencies

: MVC1, <3, 8, -1, -1, s1, {m1, m2}>

: MVC2, <3, 4, -1, -1, s2, {m3, m4}>

W = 3, d = 1

: MVC3, <1, 4, 1, 4, s3, {m5, m6}>


The multicast qos traffic scheduling problem

The Multicast QoS Traffic Scheduling Problem

  • Given N stations, W available wavelengths for data transmission, L-slot global cycle and a W  L slot-allocation matrix D; each station is equipped with a pair of tunable transceiver and each needs  time slots for tuning from i to j, i  j. For a setup request rs = < cm, dm, cp, dp, s, M>, find a new feasible slot-allocation matrixDnew with a new global cycle length Lnew such that rs is arranged into Dnew and all the QoS requirements of accepted MVC's in D are not affected.


The multicast qos traffic scheduling algorithm

The Multicast QoS Traffic Scheduling Algorithm


The multicast qos traffic scheduling algorithm available slot scan

The Multicast QoS Traffic Scheduling Algorithm -- Available Slot Scan

  • Available slot matrixA

    • A = [aij]WL , aij{0, 1}

  • Some nonzero entries may not be allocated simultaneously due to the tuning latency constraint.


Multicast traffic scheduling in single hop wdm networks with tuning latencies

B :

1 1 0 0 0 0 0 0

1 1 0 0 0 0 0 0

0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0

(b) D and A for a request MVC3 = <1, 16, -1, -1, s1, {m3, m4}>

(c) Assignable matrix B for A in (b)


The multicast qos traffic scheduling algorithm the maximum assignable slots mas problem

The Multicast QoS Traffic Scheduling Algorithm -- The Maximum Assignable Slots (MAS) Problem

  • How to retrieve the maximum available slots concurrently for assignment from available matrix A?

    • Derive an auxiliary graph with each entry in A with value 1 as a node and a link is created between two nodes whose representative entries can be assigned concurrently.

    • Find the maximum clique in the graph


The optimal mas omas solution

The Optimal MAS (OMAS) Solution

  • The Optimal MAS (OMAS) Strategy

    • Comparability graphs

      • An undirected graph G = (V, E) is a comparability graph if there exists an orientation (V, F) of G satisfying

        F F-1 = , F+ F-1 = E, F2  F,

        where F2 = {ac | ab, bc  F}

      • The maximum clique problem is polynomial-time solvable in comparability graphs.


Optimal mas omas solution contd

Optimal MAS (OMAS) Solution (contd.)

  • Auxiliary Graph Transformation

    • For each nonzero entry aij in the first  columns, move the column contains aijto the leftmost and then set all entries that cannot be assigned concurrently with aijto zero. The auxiliary graph of the new matrix Pij is a comparability graph.

    • Set the entries of the first  columns to zero, the auxiliary graph of the new matrix Q is a comparability graph.

  • The OMAS solution is the maximum of the solutions among Pij and Q


Near optimal solutions to the mas problem

Near- Optimal Solutions to The MAS Problem

  • The time complexity of OMAS strategy is O(W|A|2) in the worst case.

  • Longest Segment First (LSF)

    • A segment : a set of continuous available time slots on the same wavelength

    • Assign the slots on the segment basis

    • O(|A|2log|A|)

  • Freest Wavelength First (FWF)

    • Freest wavelength : the wavelength that contains the most available time slots

    • Assign the slots on the wavelength basis

    • O(W|A|log|A|)


Multicast traffic scheduling in single hop wdm networks with tuning latencies

Freest Wavelength First (FWF)

Longest Segment First (LSF)


Performance evaluation

0.0386

LSF

FWF

0.0376

OMAS

0.0366

0.0356

Blocking Probability

0.0346

0.0336

0.0326

1

2

3

4

5

6

7

8

9

10

d

Tuning Latency

Performance Evaluation


Conclusions

Conclusions

  • QoS multicast services in WDM star-coupled networks is investigated.

  • The slot scanning problem is defined as the MAS problem and its optimal solution is derived.

  • FWF is a considerable replacement of OMAS for its lower complexity and near-optimal blocking performance.


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