a survey of recent advances in network planning/traffic engineering (te) tools
DESCRIPTION
Designing & managing operational IP networks is a complex, multi-dimensional task. A fundamental problem before carriers today is to optimize network performance by better resource allocation to traffic demands. This requires a systematic evaluation of options, a thorough scenario analysis, and foolproof verification of network designs, all of which are increasingly possible only with help from automated TE and planning tools. In the past few years, significant advances have been made in enhancing existing tools and developing new ones that help providers rapidly identify potential performance problems, experiment with solutions, and develop robust designs. Several techniques from optimization theory, linear programming, and models of effective bandwidth calculation have been incorporated in such tools, as have detailed models of several vendor systems. We present a comparative analysis and an overview of key features of some key commercially available network planning/TE tools, and outline how they could be leveraged by carrier network engineering/planning organizations to perform detailed network analysis, proactive/reactive TE, and network design. We first give an overview of the architecture, design philosophy, and canonical features of modern design tools, and then focus on new enhancements to some popular tools as well as key distinguishing features of some newly developed ones. In particular, we focus on decision support tools for IP network planning and network analysis, including the latest versions from WANDL, OPNET, Cariden.. We also present a perspective on current outstanding carrier requirements for TE/planning tools that was synthesized by our conversations with several leading Tier 1 and Tier 2 carriers.TRANSCRIPT
A Survey of Recent Advances A Survey of Recent Advances in Network Planning/TE Toolsin Network Planning/TE Tools
Vishal Sharma, Ph.D.Metanoia, [email protected]://www.metanoia-inc.com
Metanoia, Inc.Critical Systems Thinking™
© Copyright 2006All Rights Reserved
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Agenda
TE tools in network design process and tool workflow
Taxonomy of TE tools Architecture
Design
Functions/features
New enhancements (last 1-2 years)
A perspective on current carrier needs
Operation and key features of representative TE tools OPNET’s SP Guru and VNE Server
Cariden’s MATE
PARC’s Route Generator (now part of Cisco IPSC)
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Traffic Engineering Tools in the Overall Network Design Process
SS7 SignalingNetwork Design
Optical Link Configuration
Bandwidth Requirements
Link Requirements
Switch NetworkDesign
ATM NetworkDesign
IP/MPLS NetworkDesign
SONET/SDHNetwork Design
Optical RingNetwork Design
Optical MeshNetwork Design
Traffic DemandGeneration/Estimation
SONET/SDHSynchronization
We are here
Note: In a combined multi-layer network design, this strict division may not hold
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TE Tool Workflow: Control Exercised over Varying Timescales
Forecast traffic demandsTraffic requirements
Performance objectives
Traffic measurement dataObserved network statesForecast
Load
Load Uncertainties
Traffic Managementpkt. level processing,
routing control, congestionmanagement
Capacity Managementcapacity allocation, cap.planning, routing, design
management
Network Planning network dimensioning,modeling, perf. analysis,
what-if analysis
ms, sec, min
days, weeks
months, years
Controls(config/reconfig)
ActualLoad
Network
Datacollection
TE Tools
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Taxonomy of Modern Tools: Architecture
Centralized or distributed?
Obtaining network topology &
utilization info?
Inputs
Their formats?
Interface with n/w elements?
Outputs
Their formats?
Installing routes/LSPs in n/w?
Path route computation
On-line, dynamic?
Off-line, global?
Combination of above?
Route computation trigger
User? Administrator?
New request(s)?
Scalability
# of links & nodes handled?
# of flows, LSPs, circuits?
# of constraints handled?
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Taxonomy of Modern Tools: Design Philosophy
Control-centric
Long time scales
Large granularity flows
Verisimilitude-centric
Pkt. by pkt. sims. of elements & network
Traffic trace-based perf. simulations
Hybrids
Long time scale analysis for network perf.
Pkt. level sims. for element & flow performance
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Taxonomy of Modern Tools: Functions/Features by Task
Operations Engineering/Architecture Planning
Network design + opt.
Flow analysis
Simulation &experimentation
Network planning
Multi-protocolmodeling
Survivability analysis
Economic analysis
Monitoring
Diagnostics
Validation
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Taxonomy of Modern Tools: Recent Enhancements
IGP tuning – Layer 3 traffic engineering
Incorporation of FRR – bypass, detour
Routing of VoIP calls – with queueing delay and MOS
Diff-Serv aware TE – set pool boundaries
Coupling with physical layer topology
Multicast support – for multimedia apps.
Modeling new services – VPLS, PWs, L3 VPNs
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Canonical Structure/Organization
H/w DeviceModels
User Interface/GUI/Command Line
Simulate
Analyze
Design
InternalEngine
ModulesIGP
MPLS-TE
Protection
RerouteOutputs
Config.Files
Inputs
Inputs
(Topo, Cap., Failure)Analysis
Reports
Eco. AnalysisForecasting
NMS
EMS EMS
Vendor Data Extraction
EquipmentInventory
Network
Data ExtractionData Conversion
Element DataElement State/Stats
Measurements/Probes
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A Perspective on Some Current Carrier Requirements
Accurate planning models
IP n/w planning with peering
Useability and consistency
Obtain precise traffic matrices
Good interface with monitoring tools
Intelligent heuristics
Extensible architecture
Application-level performance monitoring
Multicasting for multi-media services support
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OPNET Technologies
Founded 1986, ex MIT experts in communication system modeling
Intelligent network management software
OPNET Modeler, original flagship product
Comprehensive, comunication network modeling tool
Allows for modeling nodes, links, physical characteristics
In-built models for common communication protocols
Flexible extensions possible via C-like language
Solution suites
Service Providers: SP Guru, WDM Guru, CapEx Optimizer
System vendors: SP Guru, Modeler, NetBiz
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OPNET SP Guru: Components & Features
ProcessInputs
Discovery via NMplatforms for topology
Simulate failure &overload to get:- Worst-case loading- % disrupted traffic- SLA violation
Config.Verification
FlowAnalysis
FailureAnalysis
NetworkDesign
NetworkSimulation
MPLSModule
Integrated topo.,config., util. datafrom VNE Server
Switch/routerconfig. filesTraffic & link util.
data from systems
Traffic matrix info. fromdata collection tools
- Family of design algos.- TE capability- Impact of new algos. ortechnologies, e.g. VPNs
- “What-if” scenarios- Reachability analysis- Arch. & cost for givenQos, delay, jitter, loss- Current n/w loading
- Distribution of trafficon network links
Network model: nodes, links,speeds, topology, metrics
Validate configs.Deploy validated config.
Export n/wconfig.
- Primary/sec. path layout- FRR backup tunnels
Network simulation and analysis
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OPNET SP Guru: Internal Operation
Operates in 3 flavors
Fully-detailed, event-driven simulations
Partially event-driven simulations
Analytic simulations
OnlyPackets
OnlyFlows
Packets, Flows, Loads
Discrete EventSimulations
FlowAnalysis
Hybrid Simulations
Useful fortransient events
Micro-simulations viaspaced tracer packets
For iterative design& failure analysis
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OPNET SP Guru: NetDoctor
Rule-based config. & performance verification component
Diagnoses problems from misconfigs. or protocol conflicts
NetDoctor
Series of specifiedconfig. changes
Near real-time n/wdata from VNE Server
Output of SP Gurusimulations
Verify networkoperation
Network levelconfig. verification
(150+ rules)
User-defined rule-basedconfig. verification
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OPNET SP Guru: VNE Server
Collect data from multiple sources
Merge to create a unified picture, useful for planning, engg., ops.
VNE Engine
VNE reports
- Identify changes- Merge and synchronize
VNEDbase
Device config.-NM tools
PM tools
Tables
SNMP MIBs
Asset info.
Adapters(extensible)
Many user I/Fs: console, mgt. I/F,n/w browser for assets, link util.info., protocols run, ...
JDBC compliant
Networktopology
H/Wconfig.
S/Wconfig.
Topo.
Util. data
From n/wdevices
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OPNET Solutions: Key Characteristics
NetDoctor for configuration & network operations analysis
VNE Server
Automated I/F to various network data components
Ability to build a complete network view
Hybrid simulation techniques
Provide balance between speed and resolution
Ability to add SP’s own rules, algorithms, modules
Facility to map actual IP addressing to internal network model
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Cariden Technologies
Founded 2001, ex Stanford, experts in OR, statistics, software
MATE: suite of tools for TE-related tasks
Data gathering: integrated module or plug-in
Simulation: OSPF/IS-IS, BGP, MPLS multicast, Diffserv, ...
Optimization: Offline MPLS LSPs, IGP tuning (unique), chageover
Control-centric architecture
Does IGP planning for IP networks
Emphasis on ease-of-use
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MATE TE Process
DataCollection
DemandEstimation
RoutingOptimization
ChangeoverPlanning
User-definedConstraints
ChangeoverExecution
UserMonitoring
MATE’s TE System Components
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MATE IGP Traffic Engineering
Problems
Uneven link utilization
Heuristic/ad-hoc planning
Coarse capacity upgrade rules (e.g. at 50 or 75%)
Above 60% utilization expected in 6 mo!
Sample network with projected traffic growth in 6 months
Original network state
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MATE Routing Optimization
[Reproduced with permission: Cariden Technologies]
Objectives
Max. headroom on failure
Max. normal headroom
Minimize latency
Constraints
Fixed intra-site metrics
Symmetric weights
Latency bounds
Results
Max. link util. 89% 59%
Max. link util. on failure 110% 92%
All links brought to below 60% utilization
under normal conditions
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MATE Resilience Capabilities
Before (worst case) After (worst case)
>> 95% utilization
Max. utilization under 92%
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MATE: Changeover ExampleExtract from a Changeover Plan
[Source: Cariden Technologies]
A step-by-step procedure to move network from current to new config.
Sequence of single metric changes to effect transition
At each step, continue to meet limits on latency, utilization
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MATE: Key Distinguishing Characteristics
Demand estimation & characterization Estimate p2p demands from aggregate node/intf. demands & routing
Estimate effective b/w per queueing class to meet QoS for demands
Robust routing changeovers Sequence of moves to transition network from one routing/LSP pattern to
another via a series of “make-before-break” operations
IGP metric-tuning based optimization in IP networks
Practical BGP simulations – peering, load balancing
Fully cross-platform – supports client/server or client-only model
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PARC Technologies1
Founded 1999, ex Imperial College, London, experts in OR and optimization
Funded March 2001, $23M from Cisco, CSFB, NTT
Acquired by Cisco circa July/Aug. 2004
Control-centric architecture
Had products in two areas
Network analysis: decision support for IP operators & planners
Route Generator: off-line tool for path computation in MPLS-TE n/ws
1 Now part of Cisco IPSC
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PARC IP Network Analysis: Modules & Operation
Collection of modules for key analysis functions in IP networks
Traffic FlowAnalyzer
ForecastAnalyzer
ResilienceAnalyzer
NetworkOptimizer
NetworkAnalyzer
LSP + I/Fcounters
Router I/F thputmeasurements
Routerconfig. files
Knowledge ofVPN structure
E2E traffic flows
Futuredemands
Currenttraffic flows
Forecastdemands
Combine info. from flowanalyzer & forecasts
Produce future utilizationreport
Identify link/nodefailure that network isnot resilient to
Consider current and futuretraffic loads
Recommend changes to n/wtopology — add nodes/links
Derive e2e trafficflows in the SP n/w
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PARC IP Network Analysis: Operation
Key idea
Observe SP network state ...
Predict how network reacts to a changed environment
Designed for
IP-only networks
IP/MPLS n/wks (with or w/o TE)
Network AnalysisModules
Classes of Change Analyzable
- Topology: link/node failure
- Planning: adding node/link
- Deltas to traffic matrix
Predictions
- Max. utilization under link/node failure
- Traffic flow change on adding a link(s)
- Impact of incremental TE in plain IP n/w
ObserveAnticipatedChange(s)
Carrier Network
Outputs
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PARC Route Generator: Features & Operation
DemandAdmission
Constraints
RepairScenarios
NetworkGrooming
NetworkResilience
ProtectionAudit
Primary Tunnel Routing
FRR Backup TunnelRouting
- Bandwidth- Delay- Protected elements- Affinity
ObjectiveFunctions
Minimize- Utilization- Metrics- Disruption- Delay
Maximize- Routed b/w- Spare b/w- B/w sharingUse Cases
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PARC Solution Performance: Bandwidth Sharing Efficiency
Average Shared Bandwidth per Link •
0
1
2
3
4
5
6
7
NET1 22
NET2
54
NET4
101
NET5
236
Network Size (Nodes)
Ave
rag
e S
har
ed
Ba
nd
wid
th
BRG
CSPF
NET3
38
Maximum Shared Bandwidth per Link
0
5
10
15
20
25
30
35
Network Size (Nodes)
Ma
x S
ha
red
Ba
nd
wid
th
BRG
CSPF
NET1 NET2
54
NET4
101
NET5
236
NET3
38
Same bandwidth reused across different failure cases
[Reproduced with permission: PARCTechnologies Ltd.]
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Key Characteristics of PARC’s Solutions Interacts w/ routers, creates a full model of n/w routing
Uses measurements to implicitly derive traffic matrices
Leads to very accurate bounds on aggregate flows
Tool for intelligent probe placement for n/w data collection
RG allows provisioning of bandwidth-on-demand services
Accounts for session duration and CAC
Advances in algo. hybridization + constraint programming
Prove problem infeasibility or solution optimality