Transcript Testing Tools for Converging Networks

29 October 2009
www.nethawk.fi
NetHawk EYE Network Monitoring System
Introduction
29 October 2009
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Content
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Service Assurance in Converging Networks
NetHawk Network Monitoring System Overview
Simplicity of Monitoring
Scalability
Scalability – Example
EYE Reporting Center
29 October 2009
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Technical Challenges with Converging Networks
- Complex network topologies and functionalities
– IP-RAN, HSPA...
– Load sharing MSS/SGSN pools, Direct Tunneling
– Multi-vendor network configuration
- Increasing IP traffic
– VoIP, Mobile TV, web, streaming and gaming services cause
enormous data processing and storage requirements
– Transport links 10Gbit/s,100Gbit/s..
- QoS measurement from end users’ point of view
– Throughput and latency on IP application level, HTTP, FTP, RTP
– Variety of SIP terminals
– SIP functionalities, IN services
- Global roaming and charging
– Charging based on QoS policy
– Pre- and post paid services
Conclusion: The real-time monitoring and troubleshooting system plays an ever
increasing role as operator's business enabler!
29 October 2009
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NetHawk EYE Network Monitoring System
Overview
- Highly scalable network monitoring and troubleshooting system for
small and mid-size mobile operators (up to 5M subscribers):
– Multi-technology platform covering 2G, 3G, 4G RAN and Core
domains
– Up to 1 year data storage capacity
- Multifunctional KPI dashboards and reporting capabilities for:
– Network operational status and performance
– Revenue management data
– User-level QoS measurements
- Cost-effective solution for troubleshooting signalling and user plane:
– Drill-down from high-level views to detailed protocol data
– Call correlation across multiple interfaces
– Next generation Signalling and IP User data analysis
29 October 2009
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NetHawk EYE – Monitoring Simplicity
Probes for Capturing
DB Servers for Processing
Reporting Center for
post-processing
Web access to
KPI Metrics/Dashboards
and reports
29 October 2009
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NetHawk EYE – Monitoring Simplicity
User actions
Real-time KPI
metrics and
dashboard
KPI trends,
advanced
reports
Call data records in database
Raw signaling repository
Protocol signaling in live network
Fast decision making
based on refined
information from the
network status and
performance, QoS
aspects, subscribers’
behaviour !
EYE Reporting Center
EYE DB Servers
EYE Probes
Telecom network
Multi-access RAN, CS and PS
Core, IMS...
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Scalability – User Groups
Management
Business and revenue control
Utilisation degree of new services
Roaming verification
Network infrastructure investments and follow-up
High level QoS reporting
Helpdesk
Customer service
Trouble analysis and trends
O&M
24/7 monitoring
Subscriber troubleshooting
Verification of HW upgrades and
new service roll-outs
-3GPP Rel6 -> Rel7
-New network subsystems
Engineering
Overall network monitoring and detailed status of network entities
Ïnteroperability verification in multivendor networks
New IP service launches
-QoS and IP throughput on E-EDGE, HSDPA, HSUPA
Input data for RAN optimization and new BTS installations
-Cell utilisation reports
-HO reports
HW upgrade verification
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Scalability – User Demands
NetHawk EYE
Utilisation
Live
Amount of users
Standalone user
Analysis and
reporting tools
EYE Reporting Center
Network O&M
Fraud detection
IP QoS and user plane analysis
Network optimization Business assurance Troubleshooting
Functional testing
Lab
Application
Server for
User group
ERC options
3rd party tools
Conclusions:
Several use areas from 24/7 O&M to revenue assurance
Expandable from standalone user’s tool to whole organization’s needs
Open system easy to integrate to external NMSs
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Scalability – Network Domains
NetHawk EYE
Protocol planes
Network and
protocol domains
CS
Signalling
CS Core
PS Core
PS
Flow Analysis
GERAN
IMS
UTRAN
eUTRAN
Conclusions:
Complete network coverage on one Monitoring System from RAN to CS/PS
Multi-technology and multi-manufacturer system platform with the most
comprehensive protocol support on the market!
29 October 2009
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Scalability – Capacity
NetHawk EYE
Data storage and
processing
capacity
Database Server
Physical link
capacity
Single Probe unit
Transport
technologies
Ethernet
Multiple Database Servers
Database Server cluster
Multiple Probe units
STM-1
Probe cluster
E1/T1
Conclusions:
Highly expandable data storage for different data retention requirements
All main transport technologies supported, Ethernet (SigTran), STM-1 and E1/T1
Easily scalable for increasing physical link capacity
29 October 2009
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Scalability – Example
Network Domains
Abis
Gb
BSC
- EYE System phase 1 (Year N)
– The main CS Core interfaces (Iu-CS, A + Reg)
– 1 Ethernet Probe for SigTran
– 1 DB Server
- EYE System phase 2 (Year N+1)
– PS Core added (IuPS, Gb + Reg.)
– 2 Ethernet Probes
Iub
– 2 DB Servers
RNC
- EYE System Phase 3 (Year N+2)
– 2G and 3G RANs are added (Abis, Iub)
– 1 STM-1 and 2 E1 Probes added
– 4 DB Servers
PS
Core
Gc,
Gr
A
Registers
Iu-PS
Benefits e.g.
• CAPEX low for the initial EYE system
• EYE system coverage can be built in optimal order
• Commissioning efficient due to user account specific licensing
C,D,F
Iu-CS
CS
Core
29 October 2009
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NetHawk EYE Reporting Center
Overview
- EYE Reporting Center provides operator organisation
instant sight to:
– Essential network status
– Performance figures
– Revenue management data
- With ERC the operator can:
– Resolve root causes for subscriber reported
problems
– Optimise network element utilisation
– Verify HW upgrades and new service roll-outs
– Make better business decisions via advanced reports
- Based on IBM Cognos platform, EYE Reporting Center is highly scalable product for
different size of operators:
– Easy access with any web browser
– High security with user accounts and authentication
– Customer defineable alarms for all KPI dashboards
– Automatic reporting on HTML, Word, Excel, PDF etc.
29 October 2009
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EYE Reporting Center
KPI Analysis
KPI metrics to near real-time (NRT) network status
 Instant sight to network operation
 Status updated in 15-30 minutes periods
 Aggregates NRT KPIs into one view
KPI Dashboard
 Charts for normal and abnormal transactions, e.g. call
drops, handovers, location updates etc.
 Multiple contexts for aggregating results (network element,
link, cell)
KPI history analysis
 Visualises the KPIs behaviour instantly over selected time
period
29 October 2009
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