proof-of-concept-by-infosys

Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

Proof of Concept: MATRIXX Online Charging & Policy Management Engine Submitted to:

MATRIXX Software

Version No. Authorized by

0.4 Ian Williams

© 2009 Infosys Technologies Limited. Strictly private and confidential.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

CONTENTS 1.

ABSTRACT ...................................................................................................................................................... 3

2.

EXECUTIVE SUMMARY ................................................................................................................................... 4

3.

MATRIXX SOLUTION OVERVIEW .................................................................................................................... 6

4.

POC METHODOLOGY ...................................................................................................................................... 8

5.

POC RESULTS OVERVIEW................................................................................................................................ 9 5.1

POC TEST RESULTS..............................................................................................................................................9

6.

CONCLUSION ................................................................................................................................................ 13

7.

APPENDIX..................................................................................................................................................... 14 7.1 TABLE 1: LIST OF SCENARIOS TESTED IN POC. ..........................................................................................................14 7.2 TABLE 3: PRICE PLANS USED ..............................................................................................................................15 7.2.1 Price Plan 1 – Simple SMS Rating Scenario ..........................................................................................15 7.2.2 Price Plan 2 – Moderate GPRS Rating Scenario ...................................................................................15 7.2.3 Complex Price Plan 3 – Complex Voice Rating Scenario ......................................................................15 7.3 HARDWARE USED .............................................................................................................................................16

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

1.

ABSTRACT

The business models for Telcos remain under unremitting pressure with the emergence of 21st Century Business Drivers that increase pressure on margin, delivery and customer service. We see three key challenges that need software driven solutions in a cost effective way.   

The explosion in the amount of mobile data traffic. Our customers are seeing year on year growth in excess of 100% in the transactions carried on their networks. Bill-shock and policy management. Legislation changes and customer expectations mean that it’s no longer acceptable to catch up with billable transactions at some point in the future. Telco 2.0 Business Models. Marketing departments must be able to monetize new services and compete with new entrants

It’s not realistic to just throw greater and greater amounts of hardware at these problems, smart solutions must be put in place. This paper describes our evaluation of the Matrixx Software and its ability to resolve these issues.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

2.

EXECUTIVE SUMMARY

Today when we look for a Next-Generation Telecom billing solution, then the key attributes we are looking are: 

Compliance to future technologies – Support for all industry standard protocols like RADIUS, DIAMETER, IPDR, HTTP for collection, which enables support for future technologies like WiMAX, 3G, CDMA 1.x,LTE etc.



Real time support for pre-paid capabilities – Multiple session management, quota management and balance management.



Post-paid – pre-paid convergence – Management of post-paid and pre-paid accounts under the same customer with balance transfer support.

With the number of quality telecom service providers increasing globally, acquiring new customers and retaining the existing base is the biggest challenge for service providers. So the understanding of customer usage patterns is the key for communication service providers in identifying the customer pain points and possible areas of enhancements. Statistics indicate that CSP’s may be losing an estimated 3% -11% of their revenue due to operation leakages from network failure to create records, corrupt Call Detail Record data, delays in processing, fraud, missing files, rating inaccuracy, collection problems, billing errors, prepay faults, interconnect problems, software updates, provisioning errors and Debt/write-off. Also with the advent of 3GPP, billing systems need to overcome the above problems as soon as possible. MATRIXX OC/PM engine is one such solution which is 3GPP compliant and performs online charging, account balance management, and rating and complies with the Diameter standard for authorization, authentication, and accounting. This whitepaper is an attempt in analysing the proof of concept carried out for this solution and provides the thorough analysis on the same. Various attributes for which the Engine has been tested under the POC include CPU utilization, latency, throughput and performance measured in terms of transactions per second.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

This whitepaper documents our evaluation of the MATRIXX OC/PM Engine against these key performance indicators and also measures it’s capability of supporting high volumes of prepaid and postpaid usage.

We have carried out our evaluation across a number of business scenarios, testing the scalability of the node based architecture of MATRIX OC/PM engine and it’s response to high volume of events for various subscriber bases with increasing levels of pricing complexity.

The results we achieved are very exciting. We have been able to demonstrate real-time rating in excess of 10,000 transactions per second, per blade, with linear scalability in terms of both rating complexity and hardware utilisation.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

3.

MATRIXX SOLUTION OVERVIEW MATRIXX OC/PM Engine is a 3GPP compliant modern online charging and policy management system designed to support high volumes of prepaid and postpaid usage. Built on our patentpending Parallel-MATRIXX™ Technology, it combines extremely efficient transaction processing with a highly flexible pricing, rating, and policy engine.

Key Functionality: MATRIXX OC/PM Engine encompasses the following functionality. 1. Real-time Rating and Charging: MATRIXX OC/PM Engine supports real-time authorizations, re-authorizations, and session management, and can rate events both online and offline. The prices defined in the pricing catalog are mapped to a multidimensional array of algebraic formulas that are implemented at the system level and isolated from the business logic, which makes processing extremely fast. The algebraic equations enable MATRIXX OC/PM Engine to rate complex pricing structures and still achieve ultra-high performance. 2. Pricing: The MATRIXX OC/PM Engine can handle complex charging and discounting structures so service providers are not limited to basic pricing plans. IT personnel can easily introduce new rating sequences, as frequently as needed, without requiring updates to the core system to incorporate the changes. MATRIXX OC/PM Engine provides an intuitive graphical user interface that allows you to easily create elaborate charging and discounting models and reuse them across products and services. There is no tradeoff between pricing complexity and performance, so more data can be processed

without

reducing

performance

or

decreasing

efficiency.

Pricing

administrators can use the templates to set up elaborate pricing structures and save the configurations for reuse across product catalogs. This provides a set up once, reuse anywhere approach that makes the MATRIXX Catalog Builder unique to other pricing applications. 3. Subscriber and Balance Management: MATRIXX OC/PM Engine provides a sophisticated set of balance management features so customers can share or allocate balances among devices and subscribers. Integrated balance reservations ensure risk-free balance sharing with zero exposure to revenue loss or leakage. You can set credit limits and Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

other thresholds on balances and trigger notifications to occur when a threshold is crossed. For example, you can trigger a threshold notification to warn subscribers about impending charges. 4. Policy Management: MATRIXX subscriber policy management enforces business rules set up by service providers or subscribers to control access to services and balances.

System Highlights: There are several system highlights that set MATRIXX OC/PM Engine apart from other online rating and charging systems. 1. Transaction Processing: The Parallel-MATRIXX transaction control architecture removes the overhead involved in tracking data throughout the commit process (including tracking any other processes that want to access that data). This allows it to rate thousands of events concurrently while guaranteeing data integrity. The ParallelMATRIXX Clustering architecture allows identical copies of data to be distributed across the MATRIXX OC/PM Engine and to be owned equally by each OC/PM blade in the blade enclosure. Shared ownership of all data removes the chance of a single point of failure, which is common in most distributed database management systems. MATRIXX OC/PM Engine is comprised of several identical OC/PM blades. Each OC/PM blade is fully contained on one blade server and is able to process events at full speed. The OC/PM blade redundancy creates a highly available system that can handle an incredibly large throughput without compromising performance. Adding more blades to MATRIXX OC/PM Engine further increases the processing power. 2. High Availability: MATRIXX OC/PM Engine is comprised of several blade servers that are identical in architecture and can process events independently. Each blade server contains the same data set, so if one blade server goes offline, the other blade servers take over processing for it. This guarantees high availability of MATRIXX OC/PM Engine. 3. Simple Configuration: You do not need to write complex code to configure MATRIXX OC/PM Engine behavior and functionality. Instead, to configure MATRIXX OC/PM Engine, you use XML specifications and a graphical user interface. This makes it extremely easy to change the current configuration, such as configuring system-wide parameters, network-to-MATRIXX data mapping, balance types, and pricing components.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

4.

POC METHODOLOGY

Our Proof of Concept for MATRIXX Online Charging & Policy Management Engine attempts to validate the behaviour of MATRIXX OC/PM engine for the following parameters: 

CPU Utilisation: This is defined as the percentage of available CPU processing cycles that are used for any reason during the benchmark run. We were looking to ensure that the benchmark ran at operational CPU loads (< 60%) to validate how realistic the results are.



Latency: We measured the elapsed time from receipt of the diameter request message at the MATRIXX diameter gateway and the transmission of the diameter response message by the MATRIXX diameter gateway. This covers the entire processing of the event, including the charge calculation, transactional balance updates, and full synchronous logging.



Performance (Transactions/sec): We recorded the number of diameter charge request messages that were fully processed and responded to per second averaged over the entire benchmark run.

Each test was carried out in real-time with synchronous logging of events and with full, ACID-compliant transactions. We created a number of business scenarios whereby we used a two dimensional based approach involving increasing pricing complexity and increasing numbers of subscribers. The scenarios had different numbers of subscribers and rate plans of 1, 5 and 10 dimensions. Each scenario was run with 1, 2 and 4 blades.

For each test, we pre-loaded all of the subscriber information, as we were not seeking to evaluate this part of the system. Using a SEAGULL diameter call simulator, we prepared random samples of data for each of the rating dimensions being tested and produced files containing the appropriate number of events for each test.

Once the file had been prepared, we started the charging mechanism and logging and used the log files to populate our test results.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

5.

POC RESULTS OVERVIEW

5.1

POC TEST RESULTS

5.1.1

LINEAR SCALABILITY OF MATRIXX OC/PM ENGINE

Figure 1 shows the graph depicting Linear Scalability of Matrixx OC/PM engine whereby for a particular price plan (Complex Voice Plan), Performance and CPU utilization are measured by varying the number of blades for various subscriber bases.

Key observations noted here are:  Performance (events per second) is directly proportional to the number of blades used.  Max CPU Utilization, which can also be taken as a measure of Peak Load goes up if we increase number of blades keeping other parameters constant.  Max CPU utilization is not increasing steeply and remains within our 60% threshold.

Figure 1. Linear Scalability

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

5.1.2

LATENCY VS. THROUGHPUT KEEPING OTHER PARAMETERS CONSTANT

Figure 2 shows the graph between Latency and Throughput variations keeping other parameters constant. Following are the key observations during our POC:  Latency decreases with increasing number of blades.  Also follows the Industry standard whereby 98% of calls have latency of around 15 ms. So, this shows that software is in compliance with existing standards.

Figure 2 Graph showing Latency vs Throughput

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

5.1.3

LATENCY VS. SUBSCRIBER BASE KEEPING OTHER PARAMETERS CONSTANT

Figure 3 shows the graph between Latency and Subscriber Base keeping other parameters constant. Following are the key observations during our POC:  Latency is proportional to subscriber base if number of blades is constant.

Figure 3 Graph showing Latency vs. Subscriber base

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

5.1.4

LATENCY VS. PRICING COMPLEXITY KEEPING OTHER PARAMETERS CONSTANT

Figure 4 shows the graph between Latency and Pricing complexity keeping other parameters constant. Following are the key observations during our POC:  There is very little change in the latency when there is increased complexity with the price

plans.

Figure 4 Graph showing Latency vs. Pricing Complexity

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

6.

CONCLUSION

Our results were very much in line with our expectations, matching Matrixx’s predictions. The headline result of 10,000 transactions per second, per blade, was achieved with all combinations of price plans and numbers of subscribers. This demonstration of linear scalability combined with high performance gives a new solution to the 21 st Century challenges we and our customers have identified. Also a key driver of this Engine is about maintaining latency at high loads as well.

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

7. 7.1

APPENDIX TABLE 1: SCENARIOS AND RESULTS IN POC.

100K Subs / 500K Events / Full Synchronous Logging 1 Blade M-1 C-1 Elapsed time (sec) 47.718 Elapsed time (sec) 47.751 Elapsed time (sec) 47.753 Events / Sec = 10,478 Events / Sec = 10,471 Events / Sec = 10,470 Average CPU Util. = 19.15% Average CPU Util. = 22.92% Average CPU Util. = 26.84% Max CPU Util. = 19.52% Max CPU Util. = 23.37% Max CPU Util. = 28.82% 100K Subs / 500K Events / Full Synchronous Logging 2 Blades E-1 E-2 E-Total Elapsed time (sec) 23.912 Elapsed time (sec) 23.913 Elapsed time (sec) 23.913 Events / Sec = 10,455 Events / Sec = 10,454 Events / Sec = 20,909 Average CPU Util. = 33.01% Average CPU Util. = 30.81% Average CPU Util. = 31.91% Max CPU Util. = 36.05% Max CPU Util. = 32.34% Max CPU Util. = 34.20% 100K Subs / 500K Events / Full Synchronous Logging 2 Blades M-1 M-2 M-Total Elapsed time (sec) Elapsed time (sec) 23.914 23.915 Elapsed time (sec) 23.915 Events / Sec = Events / Sec = Events / Sec = 10,454 10,453 20,907 Average CPU Util. = 31.65% Average CPU Util. = 30.29% Average CPU Util. = 30.97% Max CPU Util. = 32.33% Max CPU Util. = 31.87% Max CPU Util. = 32.10% 100K Subs / 500K Events / Full Synchronous Logging 2 Blades C-1 C-2 C-Total Elapsed time (sec) 23.914 Elapsed time (sec) 23.913 Elapsed time (sec) 23.914 Events / Sec = 10,454 Events / Sec = 10,454 Events / Sec = 20,908 Average CPU Util. = 35.09% Average CPU Util. = 28.54% Average CPU Util. = 31.82% Max CPU Util. = 37.45% Max CPU Util. = 30.10% Max CPU Util. = 33.78% 100K Subs / 500K Events / Full Synchronous Logging 4 Blades E-1 E-2 E-3 E-4 Elapsed time (sec) 12.008 Elapsed time (sec) 12.009 Elapsed time (sec) 12.009 Elapsed time (sec) Events / Sec = 10,409 Events / Sec = 10,408 Events / Sec = 10,408 Events / Sec = Average CPU Util. = 40.63% Average CPU Util. = 37.90% Average CPU Util. = 42.95% Average CPU Util. = Max CPU Util. = 43.16% Max CPU Util. = 40.32% Max CPU Util. = 45.16% Max CPU Util. = 100K Subs / 500K Events / Full Synchronous Logging 4 Blades M-1 M-2 M-3 M-4 Elapsed time (sec) 11.974 Elapsed time (sec) 12.009 Elapsed time (sec) 12.011 Elapsed time (sec) Events / Sec = 10,439 Events / Sec = 10,408 Events / Sec = 10,407 Events / Sec = Average CPU Util. = 32.58% Average CPU Util. = 38.73% Average CPU Util. = 39.41% Average CPU Util. = Max CPU Util. = 42.92% Max CPU Util. = 49.51% Max CPU Util. = 43.14% Max CPU Util. = 100K Subs / 500K Events / Full Synchronous Logging 4 Blades C-1 C-2 C-3 C-4 Elapsed time (sec) 12.002 Elapsed time (sec) 12.002 Elapsed time (sec) 12.002 Elapsed time (sec) Events / Sec = 10,415 Events / Sec = 10,415 Events / Sec = 10,415 Events / Sec = Average CPU Util. = 38.08% Average CPU Util. = 34.38% Average CPU Util. = 35.68% Average CPU Util. = Max CPU Util. = 38.42% Max CPU Util. = 35.48% Max CPU Util. = 41.22% Max CPU Util. = 1M Subs / 5M Events / FSL 1 Blade C-1 Elapsed time (sec) 476.322 Events / Sec = 10,497 Average CPU Util. = 22.54% Max CPU Util. = 23.35% 1M Subs / 5M Events / Full Synchronous Logging 2 Blades C-1 C-2 C-Total Elapsed time (sec) 238.309 Elapsed time (sec) 238.308 Elapsed time (sec) 238.309 Events / Sec = 10,490 Events / Sec = 10,490 Events / Sec = 20,980 E-1

Whitepaper by Infosys on POC: MATRIXX Online Charging & Policy Management Engine

12.009 10,408 38.77% 39.20%

E-Total Elapsed time (sec) Events / Sec = Average CPU Util. = Max CPU Util. =

12.012 10,406 48.11% 49.31%

M-Total Elapsed time (sec) Events / Sec = Average CPU Util. = Max CPU Util. =

12.002 10,415 37.79% 40.24%

C-Total Elapsed time (sec) Events / Sec = Average CPU Util. = Max CPU Util. =

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

7.2

PRICE PLANS USED 7.2.1

PRICE PLAN 1 – SIMPLE SMS RATING SCENARIO

This price plan charges subscribers based on the number of SMS messages consumed over the past month. The rate is a simple per-message flat fee.

7.2.2

PRICE PLAN 2 – MODERATE GPRS RATING SCENARIO

This price plan charges subscribers for GPRS service. Subscribers prepay for a megabytes allowance and a roaming megabytes allowance to which charges are applied. If they go over their allotment of megabytes, overage charges apply. The rates are based on the following 5 rating parameters.  Roaming or not roaming. If roaming, charges are based on the country in which the usage occurs (Zone A, B, C, D).  Content type – email, text message, or general Internet usage.  Device type – blackberry device or other smart phone.  Prepaid data balance – if gone, overage charges apply.  Prepaid roaming data balance – if gone, overage charges apply.

7.2.3

COMPLEX PRICE PLAN 3 – COMPLEX VOICE RATING SCENARIO

This price plan charges subscribers for Voice service based on the number of minutes consumed over the past month. The rates charge a different amount based on the following 10 rating parameter and the values that are valid at the time of rating.  Time-of-day – peak period, off-peak period, or weekend calling.  Calling zone – local, long distance, or international calling to Asia, Latin America, or Europe.  Monthly Usage Balance – if the balance is over the C$500 threshold, rates change.  Carrier ID – on network or off-network.  Friends and family – in calling circle or out of calling circle.  Discounted minutes balance – if available, subtract from this balance and charge a different rate.  Subscriber’s birthday – if it is a birthday, the subscriber is charged a different rate.  Holiday Rates – if it is a holiday, the subscriber is charged a different rate.  Roaming or not roaming rates.  The SMS usage total – if the subscriber has sent over 50 SMS, the call is charged a different rate.

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Proof of Concept: MATRIXX Online Charging & Policy Management Engine _____________________________________________________________________________________________

7.3

HARDWARE USED

HP

Qty 1 4 4 48 8 1 2 1

Product 507019-B21 507778-B21 507793-B21 500658-B21 507750-B21 455880-B21 AT004A J9145A

Description HP BLc7000 CTO 3 IN LCD ROHS Encl HP BL460c G6 X5550 1P Svr HP X5550 BL460c G6 FIO Kit HP 4GB 2Rx4 PC3-10600R-9 Kit HP 500GB 3G SATA 7.2K 2.5in MDL HDD HP BLc VC Flex-10 Enet Module Opt HP P4500 1.8TB SAS Storage System HP ProCurve 2910al-24G Switch

Plot No. 44 & 97A, Electronics City , Hosur Road, Bangalore - 560 100 Phone: +91 80 28520261 Fax: +91 80 28520362

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