1. Dynamic Complex Event Processing
for Hybrid Telecommunication
Networks and Smart Grids
November 25, 2014 September, 2012 1

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
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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…
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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 cost-effective
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)
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5. About FHNW
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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?
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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
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8. DYNE Infrastructure
Cloud computing!
• Scalability
• Reliability
• Results available
immediately
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9. November 25, 2014 September, 2012 9

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
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11. Problems with simple measurements
• Relative errors are not detected
• Combinatorial errors
• Overall picture
• Error analysis
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12. DYNE Infrastructure
Analysis via Dynamic Complex Event Processing (D-CEP)!
• structure and relations
• separate relevant information
• Event processing agents (EPA) handling substreams
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13. DYNE solution
DYNE Architecture!
CEP
Adaptor API layer
Framework
Configuration
Service
ecosystem
CEP Logic
Runtime
Configuration Input Output
Service framework adaptor Implementation
Platform
configuration
Task
Data sources
configurations
Subscribers
(M2M)
Subscribers
(interactive)
Multiple CEP’s deployed on service platform.
Modularized design: logic engine
communicates through adaptor API, allowing
flexible development and deployment.
Compartmentalized API units - different data
flow cases.
CEP announces availability to ecosystem,
provides service to client services.
Several kinds of connecting services:
• Configure ongoing CEP tasks
• Provide (potentially high volume) input
data
• Subscribe to processed complex events
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14. Examples in Smart Grid
A simple example of PV panel clusters!
• All PV cells within parameters
• Single panel producing less
A potential malfunction.
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15. Examples in Smart Grid
Powerline regulation!
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16. Examples in Smart Grid
Cloud tracking!
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17. Contact Details
Topi Mikkola, BaseN (topi.mikkola@basen.net)
Prof. Dr. Stella Gatziu Grivas (stella.gatziugrivas@fhnw.ch)
https://www.project-dyne.eu
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