author: pere vilà supervisor: josep lluís marzo departament d’electrònica informàtica i...

PhD Thesis:

“Dynamic Management and Restoration of Virtual Paths in Broadband Networks based

on Distributed Software Agents”

Author: Pere Vilà

Supervisor: Josep Lluís Marzo

Departament d’Electrònica Informàtica i Automàtica

Universitat de Girona, May 2004

2

Acknowledgements

This work has been partially supported by the Ministry of Science and Technology of Spain under contracts: MCyT TIC2003-05567 MCyT TIC2002-10150-E CICyT TEL99-0976

And by the UdG research support fund: UdG-DinGruRec2003-GRCT40

3

Contents

Motivation Background Objectives Desired Characteristics Network Resource Management Proposed Dynamic Virtual Path Management Architecture based on

Software Agents Analysis and Simulation Results Conclusions Future Work Related Publications

Contents

Motivation

Background

Objectives

Desired Characteristics

Network Resource Management

Proposed Architecture

Specific Mechanisms

Putting Everything Together

Analysis & Simulations

Conclusions

Future Work

Related Publications

4

Motivation (1/5)

Network Resource Management (NRM) in ATM networks

NRM at a packet / cell level Buffer Management Packet scheduling.

NRM at a connection level Bandwidth Management Load Balancing

BCDS group background at the start of this work: Connection Admission Control in ATM Routing and Multicast in ATM

Network Management

Deals with the proper utilisation of the network resources. Objective: Try to dispatch the maximum user traffic using the same network

resources without service degradation. Network technology should have the necessary mechanisms for resource

reservations (ATM, MPLS, GMPLS).

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


5

Motivation (2/5)

Logical or Virtual Network Concept: Set of Logical Paths (LP)(allocated

resources) that can be visualised as a virtual topology.

Constitutes a higher layer. Independent of the physical network. Users establish connections over this

Logical Network. Flexibility: it can be adapted as

required. Advantages:

Physical Network

Logical or Virtual

Network

Established Logical Paths

Allows the separation of services to different LPs Enables the establishment of Virtual Private Networks Facilitates several Network Management functions

(e.g. fault protection).

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


6

Motivation (3/5)

Example:

Node 1 Node 3Node 2

Physical LinksUser

Connections

LP1

LP2

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


7

Motivation (3/5)

Example:

Node 1 Node 3Node 2

User Connections

LP1

LP2

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


Physical Links

8

Motivation (3/5)

Example:

Need of adaptation Nowadays this is performed in a centralised way

Manually by the human network managers Periodically as an optimisation problem (network design given a set of

constraints and traffic forecasts). For instance: Morning / afternoon / night configurations Every hour / day

Node 1 Node 3Node 2

User Connections

LP1

LP2

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


Physical Links

9

Motivation (4/5)

Detected problems:

Dynamic Reconfigurations

Periodic reconfigurations: Reconfigurations do not

coincide with the congestions Predictions are difficult

Dynamic Reconfigurations: Usually performed centralised Volume of the monitored

information bottleneck Scalability problem

Dynamic Distributed Reconfigurations

Dynamic Distributed Reconfigurations:

Lack of Global Network View Sub-optimal solutions

?

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


10

Motivation (5/5)

Moreover:

Trend in automating and distributing the network management functions

Dynamic Reconfigurations have also the problem of finding the right balance:

Too fast or too many reconfigurations may cause a management overwhelm.

Integration of the mechanisms that use the same resources (Logical Paths):

Dynamic Bandwidth Management Fault Protection Mechanisms

Natural area where to use Software Agents

Complex Distributed Problem

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


11

Background

We have focussed on the study of: The Network Management Standards

OSI Management Framework Telecommunications Management Network (TMN) Simple Network Management Protocol

The characteristics of the Network Management Function Architectures Centralised Distributed / Local Hybrid

Network Technologies with resource reservation mechanisms and the possibility of establish a logical network

ATM MPLS / GMPLS

Software Agents in Telecoms Multi Agent Systems Mobile Agents

Contents

Motivation

Background Man. Standards Man. Architectures Network Technologies Software Agents MAS Examples Mobile Agents Ex.

Objectives




Specific Mechanisms



Conclusions

Future Work


12

Network Management Standards

OSI Management Framework Centralised Use of standard protocols

Telecommunications Management Network (TMN) Use of an independent network Hierarchical architecture Use of OSI standards Responsibility Model (layered)

Simple Network Management Protocol (SNMP) The most widely used (Internet) Only defines protocols and MIBs Centralised – Hierarchical

Manager(Client)

NMAgent

(Server)

Management Information Base (MIB)

MOMO MO

Managed Objects (MO)

NotificationsNotifications

OperationsOperations

Managed System OSI Reference Model

MO

MO

MO

LM

LM

LM

LM

LM

LM

LM

Layer Managers (LM)

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


13

Network Management Function Architectures

Classification considering where the decision-making is placed

Centralised: Global network view Enable optimisation / planning Enable human interface Low robustness

Distributed: No central manager Decision-making equally distributed No global network view Fast response (short monitoring loop) Robustness Difficult human interaction

Hybrid: Combines centralised and distributed

characteristics

Pure Centralised Low scalability

Hierarchical High scalability Delays

Distributed with management centre Management by Delegation (MbD) Mobile Agents

Hierarchically distributed Distributed - Centralised

Distributed without management centre Collaboration Scalability evaluation difficult

Local Use of local information only High scalability Limited to specific cases

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


14

Network Technologies

Need of mechanisms to establish Virtual or Logical Paths Need of resource reservation mechanisms for these LPs Asynchronous Transfer Mode (ATM)

An integrated services network Fixed-length small packets (cells) Two-level hierarchy:

Virtual Circuits (user connections) Virtual Paths (constitute the Logical Network)

Multi-Protocol Label Switching (MPLS) and Generalised MPLS Flexible approaches to deploy connection-oriented networks Group user flows into Forwarding Equivalent Classes Label Switched Paths (LSP)

VPI=9

Physical Link

VPI=8

VCI=5

VCI=4

Cells

LSP 1

LSP 3

LSP 1Flows

IPL2

17

IP

L219

IP L225 IP

L217

IPL2

19

LSP 1 LSP 1

LSP 2LSP 2

LSP 3

17IP L22519 IP L22717IP L22719

LSP 2 LSP 2

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


15

Software Agents in Telecoms

Software agents: computer entities capable of acting autonomously, with certain degree of expertise to deal with the external world and they have the ability to cooperate in some way with other agents.

As the network management is a complex distributed task it is a natural area in which to apply software agents:

Multi-Agent Systems Static MAS are suitable for most of the networks, but usually used in reliable

high-capacity core networks. They usually have several types of agents.

Mobile Agents They can move between nodes and interact with the network element locally. Suitable for networks with low throughput and/or availability. Facilitate software upgrades and extensibility – service management.

There are many software agent proposals in network management.

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


16

Multi-Agent Systems Examples HYBRID [Somers et al. 97]

Architecture based on a geographical hierarchical structure. Upper layers delegate management to lower layers. Uses many different complex agents performing all the management functions.

Tele-MACS [Hayzelden 98] Integration of reactive and planning agents in a layered structure Its main objective is the connection admission control function

IMPACT [Luo et al. 99] Presents a multilayered structure of several types of agents Its objective includes admission control, routing, multiple service provider

support, etc and was tested on a real ATM test-bed. Others:

References

[Eurescom P712 URL][Corley et al. 2000]

[Bodanese and Cuthbert, 1999]

[Gibney et al., 1999]

[Willmott and Faltings, 2000]

DescriptionProject P712 called “Intelligent and mobile agents and their applicability to service and network management”. Cases study including the investigation into how agents could enable customers, service providers and network providers to negotiate automatically for services and network resources.

Resource management of mobile telephony networks. Use of hybrid agents for a distributed channel allocation scheme.

Market-based call routing based on self-interested agents representing network resources without assuming a priori co-operation

On-line QoS call routing in ATM networks. Hierarchical structure with a controller agent responsible for resource allocation decisions in disjoint local regions of the network.

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


17

Mobile Agents Examples

Swarm Intelligence [Bonabeau et al. 99] Systems inspired by the biological behaviour of social insects (e.g. ants, bees) Ant Colonies for network routing problems [Di Caro and Dorigo 97]

[Schoonderwoerd et al. 96] JAMES [Silva et al. 99]

Mobile agent platform (infrastructure) for network management Mobile agents start on the central manager an migrate through network nodes

and finally return to the central manager. Each mobile agent has a specific itinerary and a set of missions

Other:References[Halls and

Rooney, 1998]

[Gavalas et al., 2000]

[White et al., 1998a][White et al., 1998b]

[Caripe et al., 1998]

[Sahai and Morin, 1999]

[Bohoris et al., 2000]

[Du et al., 2003]

Description

ATM switch control, connection admission control, similar to MbD

Network modelling, fault management, Mobile Agent framework and architecture.

Network-awareness applications, network monitoring

Mobile Agent framework targeted to mobile user applications where users are intermittently connected to the network through unreliable or expensive connections.

Dynamic service management and reconfiguration, focusing on service performance and fault tolerance management, among others.

Framework for Mobile Agent-based distributed network management with a high integration with SNMP.

Mobile agents – SNMP integration, SNMP table views, polling and filtering

Contents

Motivation


Objectives




Specific Mechanisms



Conclusions

Future Work


18

Proposal: Objectives / Contribution

After the study we could conclude that: Most of the proposed MAS are too complex and / or have scalability problems. Other mechanisms focus only on a single NRM function.

Proposal: dynamic network resource management architecture for broadband core networks. Coordination / integration of the main NRM mechanisms which make use of LPs. Control the number of reconfigurations. Reconfiguration is only necessary when

a problem is detected. Lightweight monitoring. Monitoring and decision whether to change an LP or not, can be naturally

distributed over the network nodes (~ distributed architecture). The scenario suggest the use of static agents. Moreover the use of Software

Agents can also be seen as a design metaphor.

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


19

Proposal: Desired Characteristics

Modularity in the sense that such a mechanism can be activated or deactivated without disrupting the normal network operation and also in the sense that this mechanism can be deployed only in several sections of a network.

Robustness in the sense that if part of the system crashes it does not take down the whole system.

Scalability, i.e. when the network grows the architecture must not degrade its operation.

Independence in the sense that the system should not interfere with other network management systems.

Simplicity / Flexibility, enabling easy updating and upgrading, and not representing too much load for the network elements.

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


20

Proposal: Network Resource Management

Focus on the Logical Network Management: The adaptation of the Virtual or Logical Paths

Short- to mid-time process

Main tasks we consider: Focus on the established LPs Dynamic Bandwidth Management Fault Protection Spare Capacity Management

Tasks we do not consider: Initial Logical Network design The establishment / release of LPs

1) Connection demand2) Connection accepted or rejected3) Network performance problems4) Virtual Network reconfiguration5) Detected physical network bottlenecks6) Physical network upgraded

User Pool

Network Provisioning


Connection AdmissionControl

Time Scale

days

hours

min.

sec.

ms1 2

65

43

Multi-Agent

SystemRo

uti

ng

Contents

Motivation

Background

Objectives



Dynamic Bandwidth Fault Protection &

Spare Capacity


Specific Mechanisms



Conclusions

Future Work


21

Proposal: Dynamic Bandwidth Management

Maximise the resource utilisation - minimise the Connection Blocking Probability (CBP)

Two actions can be usually performed:

2 31

4 5 6

LP1

LP2

LP3

31

4 5 6

LP1

LP2

LP3

Increase LP1 by: Using available bandwidth Using underused bandwidth already

assigned to other LPs (pre-emption)

Contents

Motivation

Background

Objectives




Spare Capacity


Specific Mechanisms



Conclusions

Future Work


Re-allocation of bandwidth between LPs: Re-routing of LPs:

22

Proposal: Fault Protection and Spare Capacity

Pre-planned mechanisms (fast mechanisms): Establishment of alternative LPs (backup LPs) which become active in case of a

failure (resource consuming). Focus on the end-to-end protection (physically disjoint LPs).

Spare Capacity Management: Minimisation of the bandwidth reserved for protection purposes. Set of a desired protection level (e.g. against a simultaneous single link failure). Set of LP priorities. Sharing the capacity reserved for protection.

Contents

Motivation

Background

Objectives




Spare Capacity


Specific Mechanisms



Conclusions

Future Work


Backup LP1Working

LP1 Backup LP2

Link failure

Working LP2

23

Proposal: Architecture Two-level agent hierarchy with two types of software agents:

Network Monitoring (M) agents. Network Performance (P) agents.

They are situated at the network nodes: One P agent at every node. Several M agents at every node (at the initial nodes of the LPs). M agents are subordinated to P agents.

Physical Link

Logical Path

M agent< LP2 >

P agentM

onito

ring

LP 1

Backup LP 4

LP 5

LP 4

LP 3

LP 2

< Physical Links >< Node Control >

< Partial Network view >

M agent< LP5 >

M agent< LP4 >

< bLP4 >

Contents

Motivation

Background

Objectives




Agent Distribution Monitoring Agents Performance Agents Collaboration & Partial

Network View Partial Net. View Ex.

Specific Mechanisms



Conclusions

Future Work


24

Proposal: Agent Distribution

Proximity to the managed elements. Distribution of the processing load. Software Agents – Node Control System communication:

Direct communication through an Application Programming Interface (API). Through an SNMP Agent (this allows the placement of the Software Agents

outside the network element). Enables the establishment of an independent control plane. Sometimes a network element could have a limited processing power.

P-Agent

MM

MNode

ControlSystem

API

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


25

Proposal: Agent Distribution

Proximity to the managed elements. Distribution of the processing load. Software Agents – Node Control System communication:

Direct communication through an Application Programming Interface (API). Through an SNMP Agent (this allows the placement of the Software Agents

outside the network element). Enables the establishment of an independent control plane. Sometimes a network element could have a limited processing power.

MIB

SNMPAgent

P-Agent

MM

MNodeControlSystem

Transport Plane

Control

MIBSNMPAgentMIB

SNMPAgent

MIBSNMPAgent

P-AgentM M

M

P-AgentM M

M P-AgentM M

M

Plane

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


26

Proposal: Monitoring (M) Agents

Simple reactive agents with a stimulus/response behaviour. There is one M agent per unidirectional working LP and they are under the

supervision of the P agents.

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


LP 5

M agent< LP5 >

Control a single LP on its origin (and its backup LP): Detecting congestion through periodic monitoring.

The decision of considering the LP congested or not can be made using several mechanisms.

Optionally : They implement the switchover mechanism Co-ordinate a bidirectional communication

Lightweight monitoring The monitored data should be few simple parameters. Lightweight processes (threads)

Usually the M agents’ execution is halted and they are only resumed when the monitoring period expires and when a failure is detected.

27

Proposal: Performance (P) Agents

More complex collaborative agents. There is one P agent per network node. Their main objective is to maximise the utilisation of the links’ bandwidth they

directly control. Minimise the Connection Blocking Probability (CBP) for all the LPs starting at

every particular node. Check different possibilities to increase a congested LP and decide the best

action to take. (by itself or in collaboration with other P agents)

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


Physical Link

P agent< Physical Links >< Node Control >

< Partial Network view >

M

To perform its tasks, a P agent: Control of the node status and the

outgoing physical links. Keeps track of the transit LPs. Maintain the status of reserved and

available bandwidth on the links. Maintain a “Partial Network View”.

The P agents’ decisions are based on it.

28

Proposal: Collaboration and Partial Network View

P agents’ decisions (distributed architecture) can be based on:

In order to find a trade-off between these two options we choose that:

P agent communications are restricted to its physical neighbours: Use of a signalling-type of communications (hop by hop). Direct collaboration is also restricted to the neighbours, but indirect collaboration with

farther P agents is possible.

The P agents decisions are based on a Partial Network View: Information which the P agent is sure about (directly controlled by itself). Information that could be out of date, received from other P agents. Asynchronously updated only when P agents exchange messages.

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


Local information only Limited High scalability

Whole network view Powerful decisions Low scalability

29

Proposal: Partial Network View Example

Requested Action

Pa1

M

Pa2

M

Node 2Node 1

Partial NetworkView of Pa1

ResponsePartial Network

View of Pa2

Message from Pa1 to Pa2

Message from Pa2 to Pa1

Pa5

M

Node 1 Node 2

Node 3

Node 4Node 5

LP 5LP 4

LP 6

LP 7

LP 8

Pa1

M

Node 2LP 1

LP 2LP 3

Node 1

Node 3

Node 4Node 5

LP 4

Asynchronous “Partial Network View” actualisation:

“Partial Network View” examples:

Contents

Motivation

Background

Objectives






Specific Mechanisms



Conclusions

Future Work


30

Proposal: Specific Mechanisms

In order to test the proposed architecture the required resource management mechanisms have also to be implemented.

We propose several mechanisms with the aim of simplicity and scalability.

Monitoring and congestion detection (Triggering Functions): Rejected CBP30

Load Bandwidth reallocation algorithms:

Free Bandwidth Only (FBO) First Node Only (FNO) Any Logical Path (ALP)

Rerouting algorithms. Protection and Spare Capacity management.

Contents

Motivation

Background

Objectives




Specific Mechanisms

Monitoring & Congestion Detection

Bandwidth Reallocation

LP Rerouting Restoration & Spare

Capacity Man.



Conclusions

Future Work


31

Proposal: Monitoring and Congestion Detection This is the main task of the M agents. The important factors are:

The monitoring period (not too fast, not too slow). How to decide whether an LP is congested. The size in which increase the bandwidth of a congested LP (the “step size”).

The monitored parameters for each LP are : The number of Offered Connections (OC). The number of Rejected Connections (RC). The LP Load (L) as a percentage of the bandwidth allocated to connections.

Triggering Function (TF) is the mechanism to decide whether an LP is congested or not. We propose 3 simple TFs:

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work


Rejected

CBP30

Load

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

1 155 10 302520

3/30 10% LP Congested

t012345

OC(t)0

1522344862

Counter(t)023036

RC(t)023369

Rejected(t,limit=5)LP OKLP OKLP OKLP OKLP OK

LP Congested

LP 90% allocated LP Congested

32

Proposal: Bandwidth Reallocation

Node 1

LP 2

Node 4Node 3Node 2LP 1

LP 3LP 4

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work


When an LP is detected congested, the P agent has to try to increase its initial bandwidth avoiding re-routing.

There are messages sent form P agents to their physical neighbours. We propose three mechanisms:

Free Bandwidth Only (FBO) The only possibility is try to increase the congested LP using available bandwidth

from the physical links First Node Only (FNO)

This case is similar to the previous one, but only in the LP origin node, it is also possible to decrease the bandwidth of another LP starting at the same node and use it. An LP bandwidth can only be decreased if it is unused and allowed (pre-emption)

Any LP (ALP) It is possible to use unused bandwidth of any other LP when it partially coincides in

the same route.

33


Node 1

LP 2


LP 3LP 4

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work








the same route.

34


Node 1

LP 2


LP 3LP 4

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work








the same route.

35


Node 1

LP 2


LP 3LP 4

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work








the same route.

36

Proposal: LP Rerouting (1/2)

Not possible to use the Bandwidth Reallocation algorithms? Try rerouting the congested LP.

No need for a fast re-routing. The LP already exists. It is possible to use any existing routing algorithm, e.g. a constraint based

routing algorithm. The selected routing algorithm is applied on every node in a hop-by-hop

manner to select just the next hop. This routing algorithm use the Partial Network View The calculated route and the Partial Network View is forwarded to the next hop

Node 1 Node 2 Node 3

Node 4Node 5

LP1 Congested

New route for LP1 calculated by Pa1

Pa1

M

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work


37



Node 4Node 5

LP1 Congested

Pa5

M New route for LP1 recalculated by Pa5

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work






38


Node 1

Node 2

Node 3

Node 4Node 5

LP1 Congested

It is not possible to follow any path form Node 2

Pa2

M

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work






39



Node 4Node 5

LP1 Congested

New route for LP1 calculated by Pa4

Pa4

M

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work






40



Node 4Node 5

LP1 CongestedPa1

M

Final New route for LP1

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work






41


However, we propose a simple routing algorithm which takes into account that the partial network view could be incomplete and/or out of date. First, all the possible routes with enough resources for a enlarged LP are listed. Second, this list is ordered giving a weight to each route. The best is selected.

The routes’ weight is a weighted mean which divide the importance of the route length and the available bandwidth in the route.

The farther the link the greater the possibility to have incorrect information on the Partial network view. The influence decreases with the distance.

1

01 2 1

0

( )1

max( ) ( )

H

ii

R H

ii

H i p

H p H i

1 2 3

45

LP1 Congested

Physical links bandwidth = 10 units

7 units3 units

2 units4 units

5 units

Alternative Routes for LP1 (5 units):

Ra = 1 2 4 3

Rb = 1 2 5 4 3

Rc = 1 5 4 3

10 8 10

5 6 10

10 10 6 10

Route

Ra

Rb

Rc

Hops (H)

3

4

3

Route weight (1=2=1)

a

1 10 3 8 2 10 11 1 1.263 10 (3 2 1)

b

1 10 4 10 3 6 2 10 11 1 1.174 10 (4 3 2 1)

c

1 5 3 6 2 10 11 1 0.953 10 (3 2 1)

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work


Best

Second

Third

La

rge

r w

eig

ht

42

Proposal: Preplaned Restoration & Spare Capacity

1 2 3

45

Link FailureLinkFailed

Link

Faile

d

LP1

LP2Backup LP1

Backup LP2

Preplaned Restoration:

Spare Capacity Management:

Contents

Motivation

Background

Objectives




Specific Mechanisms




Capacity Man.



Conclusions

Future Work


LP-1LP-2

LP-3

Cannot share: backup LP1 and backup LP2

Can share:backup LP1 with backup LP3backup LP2 with backup LP3

43

Dynamic bandwidth management clearly needs to be coordinated with protection/restoration mechanisms.

It is proposed that the P agents follow several coordination rules: Bandwidth management:

Decreasing the bandwidth assigned to an LP is always possible and straight. However when decreasing a backup LP it must be checked whether the spare bandwidth is shared or not.

In a LP increase the backup LP has to be accordingly increased. We select to start the increasing procedure of both simultaneously and if one of them cannot be increased by no means, then abort the procedure.

Due to the difficulties of a distributed scenario we select to not allow rerouting of the backup LPs. Rerouting option is only allowed for the working LPs, always through link disjoint paths.

Link failure: When a backup is used, it is considered a special situation and all the affected LPs

and backup LPs cannot be increased/decreased nor rerouted. This also helps to save coordination messages between P agents and thus they

can put all their attention into the failure situation.

Proposal: Putting Everything TogetherContents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


44

Analysis and Simulations

Difficult comparison with other proposals based on Software Agents: Lack of time to implement them. Few details in the literature.

Focus on the test of the proposed mechanisms and the coordination rules

The offered connections are designed to cause congestions.

Main parameters evaluated. Connection Blocking Probability (CBP) Number of P agents messages.

We used several network topologies depending on the test.

Contents

Motivation

Background

Objectives




Specific Mechanisms



Sim. Development Mon & Congestion Det. BW Reallocation LP Rerouting Everything Together Scalability Study

Conclusions

Future Work


45

Simulation Development

Simulation platform. Distributed connection level simulation (client/server, C++).

Software Agents implementation. Distributed agents (Java).

SimulatedNetwork

Multi-AgentSystem Processes

(Java)

P-Agent(Client)

MMM

SimulatorProcesses (C++)

Node Emulator(Server)




P-Agent(Client)

MMM

P-Agent(Client)

MMM

P-Agent(Client)

MMM

Java RMI

Traffic EventGenerator

(Client)


(Client)Traffic EventGenerator

(Client)


(Client)

Client/Serversocket

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


46

Exp. 1: Monitoring and Congestion Detection (1/2)

Test of the Triggering Functions behaviour: Detection of the congestion situations (function thresholds). Evaluation for different monitoring periods. Evaluation for different ‘step sizes’.

The simulated network is very simple: The number offered connections increase during the simulation time. The LP bandwidth increase is always possible. Homogeneous and heterogeneous connections.

Combination of many parameters:

LP1

1 2

200 Mbps

Parameter

Monitoring Period (s)

Step Size (Kbps)

Rejected Limit (#connections)

CBP Limit (%)

Load Limit (%)

Values

2

500

1

10

85

5

1000

3

30

90

10

2000

5

50

95

20

4000

7

70

99

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


47

Exp. 1: Monitoring and Congestion Detection (2/2)

Results grouped by monitoring period and by step size:

0

0,1

0,2

0,3

0,4

0,5

0,6

0 5 10 15 20 25


Co

nn

ectio

n B

lock

ing

Rat

io

0

0,1

0,2

0,3

0,4

0,5

0,6

0 5 10 15 20 25


Co

nn

ectio

n B

lock

ing

Rat

io

Homogeneous case

Heterogeneous case

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0 1000 2000 3000 4000

Step Size (Kbps)

Co

nn

ectio

n B

lock

ing

Rat

io

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0 1000 2000 3000 4000

Step Size (Kbps)

Co

nn

ec

tio

n B

loc

kin

g R

ati

o

Homogeneous case

Heterogeneous case

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0 1000 2000 3000 4000 5000

R1R3R5R7CBP10CBP30CBP50CBP70L85L90L95L99

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


48

Experiment 2: Bandwidth Reallocation

1

4

8 9 15

14

13

107

116

125

3

2

0,34

0,36

0,38

0,4

0,42

0,44

0 500 1000 1500 2000 2500 3000

Time (s)

Co

nn

ec

tio

n B

loc

kin

g R

ati

o

FBO FNO ALP

We detected, as expected, that at stationary situations there is few bandwidth reallocations although congestion is detected and the P agents keep trying bandwidth reallocations.

This test was about how well the bandwidth reallocation mechanisms adapt the logical network when the level of offered connections changes over time.

7 edge nodes and 8 core nodes. 24 unidirectional LPs. 1 hour simulation.

Algorithm

Free Bandwidth Only

First Node Only

Any Logical Path

# messages

5478

13339

21402

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


49

Experiment 3: Logical Path Rerouting

0

0,02

0,04

0,06

0,08

0,1

0,12

0,14

1 2 4 8 12 13 14

Source Node

Co

nn

ec

tio

n B

loc

kin

g R

ati

o

ALP with Rerouting ALP without Rerouting

1

4

8 9 15

14

13

107

116

125

3

2

Situation

ALP + Rerouting

ALP Only

# messages

1858

3814

Comparative of a bandwidth reallocation algorithm (ALP) with and without rerouting.

After the bandwidth reallocation mechanism initially adapts the logical network, the level of offered connections changes over time and there are several congested LPs that are rerouted.

7 edge nodes and 8 core nodes. 34 unidirectional LPs. 1 hour simulation. Less offered connections than in other experiments. The results are grouped by origin node.

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


50

Experiment 4: Putting Everything Together

Finally, we perform several simulations where the bandwidth reallocation and the rerouting mechanisms were tested together with the restoration and the spare capacity management ones.

The focus of these simulations was to test the coordination rules for the P agents.

7 edge nodes and 8 core nodes. 34 unidirectional LPs + 34 backup LPs. 1 hour simulation.

Simulation of a link failure. Coordination:

1

4

8 9 15

14

13

107

116

125

3

2

The bandwidth mechanisms accordingly increases / decreases the working and backup LPs.

The rerouting is only allowed for the working LPs.

When a failure occurs and the backup is active, bandwidth changes of the affected LPs are not allowed

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


51

Experiment 5: Scalability Study

0

0,5

1

1,5

2

2,5

0 50 100 150 200 250 Edge Nodes

Core Nodes

k = 3

k = 6

We present a mathematical model of the agents interactions. It is used for scalability evaluation based on the comparison of

successive increasing sizes [Jogalekar and Woodside, 98] of our proposed architecture (scalability factor k):

We defined k as “the length of the side of a squared network”. The logical network is the full meshed network with the edge nodes.

For instance k=100 means there are 10000 nodes and 156420 LPs

k

2 2 2

1 1 1

( , , )

( , , )P

F QoS C

F QoS C

( )F k QoSC

Contents

Motivation

Background

Objectives




Specific Mechanisms




Conclusions

Future Work


( ) 1

k

k C C

Scalable

52

Conclusions

This thesis addresses the need of automatic reconfiguration in communication networks.

In a dynamic environment, we detected the need of coordination between the different mechanisms that use the same resources.

After the analysis of different possibilities of performing this dynamic management, we propose a logical path management architecture based on software agents, which effectively performs in a coordinated way: Dynamic bandwidth management. Fault protection. Spare capacity management.

Results show the ability of carrying out these tasks, while the architecture achieves a suitable scalability degree. Many experiments tested all the proposed mechanisms and the coordination between them.

Several simple NRM mechanisms have also been proposed (lightweight monitoring, Triggering Functions, bandwidth reallocation algorithms, etc). However, other mechanisms can be used with our architecture.

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


53

Future Work

Interaction of the proposed architecture with a human network manager.

Extend the idea of LP congestion to the physical links. This could help to prevent congestion in the LPs and anticipate a readjustment.

Make the M agents automatically select the most suitable monitoring period, the TF limit, step size, etc. depending on the offered connections, statistics, predictions, etc.

Interaction of the proposed architecture with other management systems in the same network or in other networks.

Deeper analysis of the interactions between the proposed architecture and the connection admission control mechanisms.

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


54


Josep L. Marzo, Pere Vilà , Lluís Fàbrega, Daniel Massaguer, “A Distributed Simulator for Network Resource Management Investigation”, In Computer Communications Journal - Special issue on Recent Advances in Communications Networking, Volume 26, Issue 15 , September 2003, Pages 1782-1791

Pere Vilà, “Gestió dinàmica de recursos en xarxes de telecomunicacions utilitzant sistemes multi-agent” [in catalan]. In the ACIA Newsletter (www.acia.org), no.24 ISSN: 1577-1989, pages 7-32, September 2001

P.Vilà, J.L.Marzo, R.Fabregat, D.Harle “A Multi-Agent Approach to Dynamic Virtual Path Management in ATM Networks”. Chapter in “Agent Technology for Communications Infrastructure”, Edited by Alex L.G. Hayzelden and Rachel A. Bourne, John Wiley & Sons 2001, ISBN 0-471-49815-7, pages 167-184.Jo

urn

als

an

d

Bo

ok

Ch

ap

ters

Contents

Motivation

Background

Objectives




Specific Mechanisms



Conclusions

Future Work


Pere Vilà, José L. Marzo, Antonio Bueno, Eusebi Calle, Lluís Fàbrega, “Distributed Network Resource Management using a Multi-Agent System: Scalability Evaluation.”, Accepted in SPECTS'04. San Jose (USA), July 25th - 29th 2004.

P. Vilà, J.L. Marzo, E. Calle, L. Carrillo, “Lightweight Monitoring of Label Switched Paths for Bandwidth Management”, Accepted in IEEE ISCC'04, Alexandria (Egypt), June 29 - July 1, 2004

Santiago Cots, Teodor Jové, Pere Vilà, “A Call-level Network Simulator Framework based on a Standard Agent Platform”, In Proceedings of SPECTS 2003, Montreal (Canada), July 20-24, 2003.

Pere Vilà, José L. Marzo, Eusebi Calle, “Dynamic Bandwidth Management as part of an Integrated Network Management System based on Distributed Agents”, In Proceedings of IEEE GLOBECOM 2002, Taipei (Taiwan), November 17-21, 2002.

Pere Vilà, Josep L. Marzo, Lluís Fàbrega, “Using a Multi-Agent System for Network Management”, In Proceedings of CCIA 2002. October 24-25, 2002. Castelló de la Plana, Spain.

Pere Vilà, Josep L. Marzo, Antonio Bueno, “Automated Network Management Using a Hybrid Multi-Agent System”, In proceedings of AIA 2002, September 9-12, 2002. Málaga, Spain. ACTA Press.

Pere Vilà, Josep L. Marzo, Antonio Bueno, Daniel Massaguer, “Network Resource Management Investigation using a Distributed Simulator”, In proceedings of SPECTS 2002, San Diego, California (USA), July 14 - 18, 2002.

Josep L. Marzo, Pere Vilà, Lluís Fàbrega, Daniel Massaguer, “An ATM Distributed Simulator for Network Management Research”, In proceedings of 34th ASS'2001, Seattle, Washington (USA), April 22-26, 2001.

Pere Vilà, Josep L. Marzo, "Scalability Study and Distributed Simulations of an ATM Network Management System based on Intelligent Agents", In proceedings of SPECTS'2000, Vancouver (Canada), 16-20 July 2000.

Josep L. Marzo, Pere Vilà, Ramon Fabregat, "ATM network management based on a distributed artificial intelligence architecture", In proceedings of AGENTS'2000, Barcelona (Spain), 3-7 June 2000.

Pere Vilà, Josep L. Marzo, Ramon Fabregat, David Harle “A Multi-Agent Approach to Dynamic Virtual Path Management in ATM Networks”, In proceedings of IMPACT'99, Seattle (USA) 2-3 December 1999. In

tern

atio

na

l Co

nfe

ren

ces

55

Thank you for your attention

Author: Pere Vilà

Supervisor: Josep Lluís Marzo

Departament d’Electrònica Informàtica i Automàtica

Universitat de Girona, May 2004

PhD Thesis:

“Dynamic Management and Restoration of Virtual Paths in Broadband Networks based on Distributed Software Agents”

author: pere vilà supervisor: josep lluís marzo departament d’electrònica informàtica i...

Documents

logical network

network resources

physical network

network technology

virtual network concept

network management functions

resource reservations

dynamic management