Dynamic Complex Event Processing for Hybrid Telecommunication Networks and Smart Grids. September,

Transcription

1 Dynamic Complex Event Processing for Hybrid Telecommunication Networks and Smart Grids September,

2 Adding semantic data and dynamic complex event processing capability to BaseN platform Eurostars project between FHNW & BaseN 2012 onwards, 33 months,1me budget 1 PhD thesis September,

3 About BaseN BaseN Corporation Founded in 2001 Privately held Management team Internet-IT-networking veterans, with direct experience in high-scale, fault tolerant, complex, and real-time system management needs International technology company Headquarters in Finland, locally present also in Sweden, Netherlands, Switzerland, Spain, Czech Republic, Dubai, Hong Kong, USA: Atlanta and Bay Area International customer base: Telecom and Service Providers Governments ICT, manufacturing and processing industry Energy and environment sector 45+ customers in 80+ countries, and growing September,

4 BaseN s Expertise End-to-end (e2e) monitoring, analysis, correlation, display, reporting and storage of information, also used for forecasting and managing service maintenance, in public and private network infrastructures alike Software as a Service (SaaS) Turnkey solution: BaseN invests in hardware and infrastructure for the customer Powered by advanced grid computing technology: the BaseN platform provides unprecedented scalability, security, and built-in fault tolerance and robustness, capable of handling enormous amounts of data real-time Well over 4 million measurements per minute for complex devices such as routers * Well over 20 million measurements per minute for simple devices such as meters ** Can measure any network resource and/or service in an extraordinarily costeffective operating environment, is future-proof and easily extendable, and hence offers the customer a pay-as-you-grow model Data is instantly accessible anytime through multiple interfaces, such as Web 2.0, PCs, laptops, and mobile devices, all through easily customized customer portal (* Example based on ca 500 bytes per measurement) (** Example based on ca 100 bytes per measurement) September,

5 About FHNW September,

6 The Question The question DYNE answers Modern network contains from thousands to millions measurement targets Several measurements are connected Anomalies need to be detected immediately Q: How to process this all in human understandable way? September,

7 DYNE Infrastructure Measurements in massive scale Near real time processing of millions of scalar values per minute Network infrastructure, communications quality, smart grids Any level of protocol current signal to application level September,

8 DYNE Infrastructure Cloud computing Scalability Reliability Results available immediately September,

9 September,

10 Scale Medium telco: 5M+ measurements/minute, 500k+ alerts, 20k+ sites Power usage for end user sites of a small country City with smart housing Worldwide collection of PV installations September,

11 Problems with simple measurements Relative errors are not detected Combinatorial errors Overall picture Error analysis September,

12 DYNE Infrastructure Analysis via Dynamic Complex Event Processing (D-CEP) structure and relations separate relevant information Event processing agents (EPA) handling substreams September,

13 DYNE solution DYNE Architecture CEP Multiple CEP s deployed on service platform. Adaptor API layer CEP Logic Modularized design: logic engine communicates through adaptor API, allowing flexible development and deployment. Framework Configuration Runtime Configuration Input Output Compartmentalized API units - different data flow cases. Service framework adaptor Implementation CEP announces availability to ecosystem, provides service to client services. Service Platform ecosystem configuration Task configurations Data sources Subscribers (M2M) Subscribers (interactive) Several kinds of connecting services: Configure ongoing CEP tasks Provide (potentially high volume) input data Subscribe to processed complex events September,

14 Examples in Smart Grid A simple example of PV panel clusters All PV cells within parameters Single panel producing less A potential malfunction. September,

15 Examples in Smart Grid Powerline regulation September,

16 Examples in Smart Grid Cloud tracking September,

17 Contact Details Topi Mikkola, BaseN Prof. Dr. Stella Gatziu Grivas September,