End-To-End Service Monitoring For Converged Services Danny Itzigsohn Director of Solution Engineering TTI Telecom © 2007

Four Basic Questions Concerning Service Assurance Q1: Can we foresee service failures and avoid them? Q2: When affected: To what extent is the service disrupted? Which customers are being impacted? Q3: How fast can we restore the service? Q4: Can we prevent the recurrence of the failure?

Q1: Can we foresee service failures and avoid them?

Q2: When affected:

To what extent is the service disrupted?

Which customers are being impacted?

Q3: How fast can we restore the service?

Q4: Can we prevent the recurrence of the failure?

Effective Operations Approach For Managing Service Failures Service Failure Occurrence Failure Detection Root-cause Isolation Service Restoration Service Failure Closure Data Collection Service Impact & Affected customers Repair Procedures Observation & Usage Analysis

Proactive Approach To Managing NGN Services Shorten the time to detect a failure Leverage all available data feeds Real-time quality degradation detection Determine impact on services and customers Linking customers to the services Prioritize operations repair activities Optimized service management life-cycle Integrated SQM and fault management Monitor business operational aspects

Shorten the time to detect a failure

Leverage all available data feeds

Real-time quality degradation detection

Determine impact on services and customers

Linking customers to the services

Prioritize operations repair activities

Optimized service management life-cycle

Integrated SQM and fault management

Monitor business operational aspects

From Chaos To Structured Service Management Network Resource Management Resource Service Model Network Resource Network Domain Regional Area Service Application Service Control Customers Service Quality Management Fault Detection Service Impact Service Usage Traffic Analysis Assurance Solution Signaling Application NG Network Legacy Network Probes Probes SIP CDRs SIP CDRs SNMP SNMP Diameter Legacy

VOIP Carrier Example: End-To-End Service Monitoring View Access CDRs/IPDRs SIP Control PSTN Access Voice Probes Voice Probes Transport Probes Core Infrastructure Application & QoE Transport Signaling ASR NER Call Completion Rate Call Setup/Post-dial Delay Call Termination Cause Packet Loss Packet One-way/Round Trip Delay Packet Jitter Packet Burst R-Factor/MOS Echo Attenuation Codec Mismatch Device/Domain Availability Network Congestion Route Flapping CPU/Memory Usage

ASR

NER

Call Completion Rate

Call Setup/Post-dial Delay

Call Termination Cause

Packet Loss

Packet One-way/Round Trip Delay

Packet Jitter

Packet Burst

R-Factor/MOS

Echo

Attenuation

Codec Mismatch

Device/Domain Availability

Network Congestion

Route Flapping

CPU/Memory Usage

Being Proactive Starts with Minimizing Time to Detect Customer Complaint Network Trap Event Degradated Quality Event Service Impact Event Time to Detect a Failure Proactivity

Best Practice for Service Quality Monitoring Calculation of KPI and KQIs Derived from: Network devices, Active probing, Passive probing, CDR/IPDRs, TTs KQI aggregation based on user-defied rule sets Applying threshold rules From simple thresholds to advanced spikes and trends monitoring Quality of service alerts generation Drill down to isolate root cause

Calculation of KPI and KQIs

Derived from: Network devices, Active probing, Passive probing, CDR/IPDRs, TTs

KQI aggregation based on user-defied rule sets

Applying threshold rules

From simple thresholds to advanced spikes and trends monitoring

Quality of service alerts generation

Drill down to isolate root cause

Example: End-To-End SIP Performance Indicators Session initiation Session Progress Session Termination Registration Request Delay (RRD) Session Request Delay (SRD) Post-Dial Delay (PDD) Average hops/ INVITE (AHI) Session Duration Time (SDT) Call Hold-Time (CHT) Session Disconnect Delay (SDD) Session Disconnect Failure (SDF) Cut-off Calls Session Establishment Rate (SER) Answer Seizure Rate (ASR) Network Efficiency Rate (NER) Session Establishment Efficiency Rate (SEER) Ineffective Session Attempts (ISA) Session Defects/ million (SPM) Session Completion Rate (SCR) Session Success Rate (SSR) Call Completion Rate Call Success Rate (CSR)

Registration Request Delay (RRD)

Session Request Delay (SRD)

Average hops/ INVITE (AHI)

Session Duration Time (SDT)

Session Disconnect Delay (SDD)

Session Disconnect Failure (SDF)

Session Establishment Rate (SER)

Answer Seizure Rate (ASR)

Network Efficiency Rate (NER)

Session Establishment Efficiency Rate (SEER)

Ineffective Session Attempts (ISA)

Session Defects/ million (SPM)

Session Completion Rate (SCR)

Session Success Rate (SSR)

Call Success Rate (CSR)

Service Quality Degradation Detection Monthly usage of MobileTV service > 1.15*Usage in prior month Monthly calls on plan SummerTime <150% monthly calls to a destination during last 6 months Monthly average service availability SLO < 99.95% Session establishment success ratio < 95% Monthly average SMS Delivery time > 1.3* Monthly average delivery time last month Hourly short-duration calls >30% Total calls Monthly routed traffic to internet peering X <30% Total internet traffic First page success rate < 65% Increase of 30% in critical service alarms from last period Drop rate (period ‘n’) > 1.2*Drop rate (period ‘n-1’) Monitor Threshold Crossing Comparative Monitoring Monitor for Spikes Monitor for Trends Network Operations Center Engineering Marketing Management

Example: Applying Thresholds In 3G UMTS Network Multi-Severity Threshold MAS ASR initial threshold set to < 97.5%. Escalation steps of -2.5%. Service Quality Monitoring Solution Example: Data Source KPI TrafficGaurd Condition KQI TrafficGaurd Condition V ideo S ervice CDR UTRAN Cell RAB Establishment Successes (CS64) Comparative Condition: Current RAB Successes <97% Current RAB Attempts RNC Video RAB Success Rate: RAB Successes *100 /Current RAB Attempts Spike Condition: Daily RNC Video RAB success Rate +/- 20% (when RNC Video RAB Attempts > 100) CDR UTRAN Cell RAB Establishment Attempts (CS64)

Multi-Severity Threshold

MAS ASR initial threshold set to < 97.5%.

Escalation steps of -2.5%.

Service Quality Monitoring Solution Example:

Better Understanding Your Service Impact Impact Engine Determine service impact based on affected resources and business logic Availability Engine Measure of the probability that a service is available at any given time Service Alarms Report on service events as part of the fault correlation process What-if Scenarios Simulate operational activities to better understand their impact Impact Engine Availability Engine Service Alarm What-if Scenarios

Impact Engine

Determine service impact based on affected resources and business logic

Availability Engine

Measure of the probability that a service is available at any given time

Service Alarms

Report on service events as part of the fault correlation process

What-if Scenarios

Simulate operational activities to better understand their impact

Visualizing Service Model Defining relationship between service components Determining alarm filtering and service impact rules Linking customers to services Visualizing the root cause of the service Intuitive navigation to supporting assurance applications Network Resource Regional Domain Customers’ Groups MMS Service Monitoring Resource

Defining relationship between service components

Determining alarm filtering and service impact rules

Linking customers to services

Visualizing the root cause of the service

Intuitive navigation to supporting assurance applications

Determine Impact On Services And Customers

End-to-End Service Assurance Summary Service Assurance for NGN must conform with the following guidelines to provide added value: Maximize Proactively Optimize fault resolution cycles Calculate end-to-end metrics Evaluate the impact of events from a customer/service perspective

Service Assurance for NGN must conform with the following guidelines to provide added value:

Maximize Proactively

Optimize fault resolution cycles

Calculate end-to-end metrics

Evaluate the impact of events from a customer/service perspective

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