A 40 Terabyte class DWH For Mobile Telecommunications Traffic analysis Using SAS Intelligence Storage

Transcription

1 A 40 Terabyte class DWH For Mobile Telecommunications Traffic analysis Using SAS Intelligence Storage Naoto Noguchi Manager au Engineering Division KDDI CORPORATION KDDI Proprietary Information 1

2 Agenda About KDDI - Japan s Cellular Market Growth History - Growth of 3G Subscribers Background of Development - About the Data - Development Requirements - Pros & Cons of RDB and SAS - Selected SAS System Overview - Usage Status - Usage Purpose - Sample Screen Results 2

3 About KDDI As of Mar KYOCERA 13.5% 11.7% TOYOTA Large Provider of Electronic Devices KDDI Total Employees: 13,500 1 KDDI Corp. : 9,000 Affiliates : 4,500 Largest Vehicle manufacturer in Japan Total Revenue : US$22.3 billion 2 Ordinary Profit : US$ 0.9 billion (Revenue) Mobile: US$17.1 billion(77%), Broadband Consumer(BBC)&Solution:4.8 billion(22%), Affiliate 3 :0.2 billion(2%) Mobile DDI Pocket Tu-Ka etc <53 Affiliated Companies > BBC & Solution KCOM K Solution JPIX etc Overseas KDDI America KDDI Europe KDDI Hong Kong etc 1:As of Jan :FY :TU-KA, POCKET are included in Mobile 3

4 About KDDI The Largest International Carrier in Japan - Global Service Provider - Big Corporate Customer Base - Long years of R&D experience au Merger / October 1, 2001 KDD The Largest New Carrier in Japan - Efficient Management - Strong Sales Force KDDI IDO Merger / October 1, 2000 services in Japan Comprehensive Service provisioning to any customer requirement 2. Robust and Sophisticated Network DDI Mobile Service Provider in Kanto/Tokai Area -Early adoption of CDMA 1. The only company that can provide Full-lineup telecommunications to meet Big Capacity Demands Optical Fiber Network expanding from Local to Global Area 3. Research & Development Capability to lead the industry Long years of contribution to the technical standards 4. High-Level Management Efficiency Revenue per employee : US$ 1.6 million (FY2002) 4

5 Japan s Celluar Market Growth History (Million) 90 CDMA1X, end of Mar Total No. of Subscribers: 81,519K x EV-DO, W-CDMA / 16,692K cdmaone / 3,449K PDC/61,783K 61,378K Analog / 0 (end of Srv.) (Remarks) ; Data for 2003 is based on Mar., (end of each fiscal year) Source: Telecommunications Carriers Association 5

6 Growth of 3G Subscribers ( 100 0) April 2002 CDMA2000 1x Service Started 84% 0 '02/4 '02/7 '02/10 '03/1 '03/4 '03/7 '03/10 '04/1 C D M A X FO M A (D oc om o) VGS(Vodafone) 6

7 Background of Development Corporate Expansion following mergers > Increase in customers, volume of calls, facilities Introduction of the 3G cellular phone > Increase in new types of data > Increase in volume and complexity of traffic data that must be analyzed in order to monitor, manage, and improve network quality 7

8 About the Data Traffic Data CDR Data CDL Data 8

9 Types of Data Source Network devices and data that ADIDAS collects (as of April 2004) Target Data Target Device Types Developing of Data Vendor CDR EMX 1 Motora Preservation ΣMSC 1 period 62 ΣGS 2 days GPS-D 1 HP Japan CDL Preservation period 10 days Traffic Preservation period 62 days (Partly vary) OMCR 1 Motora H OMC 1 HITACHI Apply to 2G and 800M F/S OMC(BSM) 1 Fujitsu/Samsung Integrated user interface on client terminals by sharing data base across different vendors development equipment Notes EMX 22 Motora ΣMSC 40 ΣGS/ΣSTP 38 OMCR 60 Motora Apply to PM Data, XC_sar and Eventlog H OMC 17 HITACHI F/S OMC 78 Fujitsu/Samsung Collected BSM TAN-BSM DLM SWM AccessNode 9 Motora PDSN 23 CTC SMS node 7 Fujitsu IMF IMFWeb ChatSV ChatGW ChatRadius CICP node 2 HP Japan Collected frfom audispatcher Integrated Dispatcher ANP 20 Converse OTA 16 Collected from PDS, Radius,SG 9

10 Development Requirements Processing of huge volume data generated periodically High-speed statistical analysis of the large quantities of data Reduced workload for system operation and data model changes 10

11 Pros & Cons of RDB and SAS Pros Cons RDB High-speed loading through parallel processing High-Speed Query (INDEX HASH RANGE functions) Reliability of DB for recovery and exclusiveness Used RDB in former system Rich experience in RDB in DWH Heavy administrative burden for data domain Time-consuming back up and deletion process Heavy maintenance and administrative burden (actual experience) SAS High -speed loading of large volume of data Ad hoc high-speed query Decreased DISK space compared with RDB Manage and control SAS data set on UNIX Easy addition of data items No recovery function No exclusiveness function Small number of references 11

12 Selected SAS Function Cost SAS RDB is more functional and common as DWH => This system does not use recovery and exclusiveness function so often (hardly at all) Provides enough functions => Easy date expansion and change => Reduction of operation work load is possibl (Data management) Reduction of DISK space VS RDB =>H/W cost reduction Data changes can be managed at user level => S/W cost reduction 12

13 System Architecture System architecture (H/W is all AlphaServer by HP Japan) ADIDAS Servers Facilities in 10 au Branches Base Station Radio control device Collection server DS10(*1) Traffic DB Server CDL DB Server UIF Server Analysis PC PBX : GS1280 GS160 DS10 2 ACTIVE-LAN au Branch 1 au Branch 2 au Branch 10 : : CDR Telephone # searching server ES40 2 Buck-up server CDL DB Server GS320 DB Function RPS Server DS10 Analysis PC OA-LAN Shared facilities DS20 ES45(*2) Collection server Back-up function Web Function 2 nd Fuchu NC *1 Numbers vary by branch (1-4 per branch) *2 Composed by ES45 DS10 and DS20 (total of 7) 13

14 System Architecture System architecture (H/W is all AlphaServer by HP Japan) ADIDAS Servers Facilities in 10 au Branches Base Station Radio control device 12TB Collection server DS10(*1) Traffic DB Server CDL DB Server 15TB UIF Server Analysis PC PBX : GS1280 GS160 DS10 2 ACTIVE-LAN au Branch 1 au Branch 2 au Branch 10 Shared facilities : : 6TB CDR Telephone # searching server ES40 2 Buck-up server DS20 ES45(*2) Collection server CDL DB Server GS320 DB Function Back-up function RPS Server DS10 8TB Web Function 2 nd Fuchu NC Analysis PC OA-LAN *1 Numbers vary by branch (1-4 per branch) *2 Composed by ES45 DS10 and DS20 (total of 7) 14

15 Usage Status 5% 35% Usage Usage Rate Rate 5% 5% 25% 25% Quantities Quantities Engineering(300) Operation(200) Quality(100) Sales(30) sales(30) Customer(20) Custmer(20) etc(20) 15

16 Usage Purpose 5% 5% 10% 25% 5% 50% Quality Engineering Operation Customer Sales etc 16

17 Sample Screen As ADIDAS is web based, all the PCs with web browser can be used as ADIDAS terminals (NN47 is recommended. IE is also available.) OA Terminal (need application) -Output: CSV file (exportable to Excel) -Can select Summary table or statistical table :Our put items could be arbitrarily set Through web screen: -Define Data (CDR, Traffic) -Define period -Define Region/device (Branch/Switch etc.) 17

18 Results 1 Reduced workload for system operation and data model changes OLD SYSTEM (RDB) NEW SYSTEM (SAS) => A big workload decrease 18

19 Results 2 High-speed statistical analysis of the large quantities of data GB Data Perform ance minute Add On H/W 2000 Initial Introduction 2002 CPU & DISK 2003 CPU & DISK 2004 H/W1Set

20 Memo 20