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(1)

Dynamic Network Resources Allocation in Grids

through a Grid Network Resource Broker

Davide Adami, Stefano Giordano, Michele Pagano

INGRID 2007 – Instrumenting the GRID

Second International Workshop on Distributed Cooperative Laboratories

(2)

Outline

Introduction

Target and motivations of the research activity

Grid Network Resource Broker Architecture

WCBDS (Wang-Crowcroft with Bandwidth and Delay Sorting) Path

Computation Algorithm

Simulations results

(3)

A parallel renderer/encoder

Parallel

DivX

Encoding

Output

Store

Frame

Sequencer

GoP

Assembler

(4)

Instrumentation/Computing Grid Environment

Grid Concept

“A Grid is a collection of distributed computing resources

High Speed Optical Network

with G-MPLS Control Plane

(5)

Grid Networking Issues

Grid Application

Grid Application

Grid Application

1.

1.

A network infrastructure which prevents degrading the throughput

A network infrastructure which prevents degrading the throughput

of

of

grid applications due to network delay and network fault is requ

grid applications due to network delay and network fault is required

ired

2.

2.

It is necessary to carry out network resource scheduling

It is necessary to carry out

network resource scheduling

as well as

as well as

computing resource scheduling

computing resource scheduling.

.

3.

3.

A network design and deployment methodology for complicated grid

A network design and deployment methodology for complicated grid

networking is necessary.

networking is necessary.

Diffserv

(6)

Scheduling Process:

Enhanced Deployment Cycle

Weighted

Task Interaction Graph

of the application

•Vertex: Computational Cost

•Edge: Communication Cost

•Application nodes are mapped

into computing resources

•Cumulative bandwidth

requirements are given

•Network Query

(list of candidate solutions)

(7)

Diffserv

Diffserv

-

-

aware

aware

MPLS TE network

MPLS TE network

Grid

Application

Manager

Grid Network Resource Broker

PC Cluster

GNRB Monitoring and

Management Area

(8)

Capturing device

Capturing device Network Monitoring System

Visualization GUI Measurement Sampling Modules Sampling Sampling Network Element Configuration Manager Path Computation Element Network Information Database Admission Control Module Network Resource Scheduler Measurement Database Network Resources Manager

Grid Application Manager Grid Application Topology Discovery Service

GNRB Functional Blocks

(9)

GNRB Architecture

• Network Resources Manager

• Policy-based provisioning

• Path computation

• Network Resources Scheduling

• Topology Discovery Service

• Network Element Configuration Manager

• Service provisioning

• GNRB and Network Monitoring System

• Link utilization

• QoS measurements (packet loss, delay, jitter)

(10)

Network Monitoring System

DiffServ/MPLS network traffic monitoring

(11)

GNRB Network Services

• Network Topology Discovery

• Provides information about the topology of the network and QoS

metrics associated to the links

Best

Best

-

-

effort

effort

connections

connections

• Weighted Topology Discovery

• Best paths, according to a metric specified by the GAM are

computed by the NRM

Network

Network

resources

resources

may

may

be

be

allocated

allocated

• QoS provisioning

• Premium service (Peak Rate, Burst Size, Latency)

(12)

Path Computation Algorithm

Goal

Given a set of N LSP set-up requests, the basic function of the

PCE is to find N network paths that satisfy their QoS constraints

(Bandwidth B

min

, Delay D

max

)

QoS Metrics

•Bandwidth

: Concave metric

B(p)=min[B(i,j); B(j,k); .. B(l,m)]

•Delay

: Additive metric

D(p)=D(i,j)+D(j,k)+…D(l,m)

i

j

k

l

m

(13)

End-to-end Delay



Propagation delay



Transmission delay



Queueing delay

Queueing delay: Deterministic Upper Bound

End-to-end Delay

i

LSP

rate

guaranteed

i

r

size

burst

max

M

1

=

=

+

=

= k j j i i i

S

r

M

D

Delay

for LSP i

i

LSP

size

packet

L

size

packet

L

r

L

R

L

S

i i i j j i

=

=

=

+

=

max

max

max max

Node j Delay

in case of WFQ

scheduling discipline

(14)

The WCBDS Algorithm

Z = N ? EXIT Bandwidth Based Re-ordering Delay Based Re-ordering Yes No Z Requests accepted WC Algorithm N Requests N Requests Z = N ? WC Algorithm Z = N ? WC Algorithm N Requests EXIT EXIT Yes No Yes Z Requests accepted Z Requests accepted

Wang-Crowcroft Algorithm

1. Set d

ij

=

if B

ij

< B

min

2. Compute the path P with the

minimum delay

3. Calculate the delay D* of P

4. If D* < D

max

select the path P

(15)

B

3 - 30

C

4 - 20

A

D

4 – 20

E

F

4 - 10

1 - 30

2 – 30 4 - 20

2 - 20

6 - 10

B

min

= 3 Mbps

D

max

=100 ms

1.

A_B_C_F

2.

A_D_E_C_F

1) Prune the links with

B

av

< B

min

2) Find minimum delay path

1.

D = 96.43ms

2.

D = 102.49ms

B

3 - 30

C

4 - 20

A

D

4 – 20

E

F

4 - 10

1 - 30

2 – 30 4 - 20

2 - 20

6 - 10

X

X

X

Wang-Crowcroft Algorithm

B

min

= 3 Mbps

D

max

=98 ms

Rejected!

(16)

NS2 Software Modules

MNS - MPLS Network Simulator

Old Modules

New Modules

RSVP-TE\ns with Reservation Styles

OSPF-TE\ns

(17)

New MPLS Node Architecture in NS2

OSPF-TE

module

OSPF-TE

module

RSVP-TE

module

RSVP-TE

module

(18)

LSR4 LSR9 LSR5 LSR8 LSR10 LSR11 LSR14 LSR16 Node17 Node18 LSR15 LSR6 Node1 Node0 Node2 Node3 LSR12 LSR13 LSR7 Network 0

Network 0 Network 1Network 1

Network 2 Network 2

MPLS

Backbone

Node19 Node20

Network Topology

(0.3, 100) (1, 50) (2, 10) (2, 20) (2, 10) (2, 10) (2, 100) (2, 20) (2.5, 15) (1, 10) (2.5, 10) (2.5, 10) (2.5, 10) (2.5, 10) (1, 10) (2.5, 10) (2.5, 10) (1, 30)

(19)

First Scenario

84

4-5-8-10-16

100

600

16

4

Time

(ms)

Path

Delay

(ms)

Bandwidth

(Kbps)

Egress

LER

Ingress

LER

LSR4 LSR9 LSR5 LSR8 LSR10 LSR11 LSR14 LSR16 Node17 Node18 LSR15 LSR6 Node1 Node0 Node2 Node3 LSR12 LSR13 LSR7 Network 0 Network 1 Network 2 MPLS Backbone Node19 Node20

(20)

Second Scenario

Time

(ms)

Path

Delay

(ms)

Bandwidth

(Kbps)

Egress

LER

Ingress

LER

LSR4 LSR9 LSR5 LSR8 LSR10 LSR11 LSR14 LSR16 Node17 Node18 LSR15 LSR6 Node1 Node0 Node2 Node3 LSR12 LSR13 LSR7 Network 0 Network 1 Network 2 MPLS Backbone Node19 Node20

(21)

Third Scenario

84

4-5-8-10-16

100

600

16

4

Time

(ms)

Path

Delay

(ms)

Bandwidth

(Kbps)

Egress

LER

Ingress

LER

LSR4 LSR9 LSR5 LSR8 LSR10 LSR11 LSR14 LSR16 Node17 Node18 LSR15 LSR6 Node1 Node0 Node2 Node3 LSR12 LSR13 LSR7 Network 0 Network 1 Network 2 MPLS Backbone Node19 Node20

Traffic Load 75%

on the path

15_14_11_6_4

(22)

Fourth Scenario

Time

(ms)

Path

Delay

(ms)

Bandwidth

(Kbps)

Egress

LER

Ingress

LER

LSR4 LSR9 LSR5 LSR8 LSR10 LSR11 LSR14 LSR16 Node17 Node18 LSR15 LSR6 Node1 Node0 Node2 Node3 LSR12 LSR13 LSR7 Network 0 Network 1 Network 2 MPLS Backbone Node19 Node20

Traffic Load 75%

on the path

15_14_11_6_4

(23)

Conclusion

The design and deployment of grids for remote instrumentation

services require the introduction of new control plane mechanisms

to dynamically allocate resources in high-speed (G)-MPLS networks

A centralized approach, based on a GNRB, has been designed and

developed

A new algorithm for the computation of path with bandwidth and

delay constraints has been proposed

Preliminary simulation results are promising

References

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