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Björn Bjurling, [email protected] Daniel Gillblad, [email protected] Anders Holst, [email protected]
Swedish Institute of Computer Science
BIG DATA AND ANALYTICS
www.sics.se
AGENDA
• What is big data and analytics?
• and why one must bother
• Examples of big data for vehicles
• Summary and take away lessons
www.sics.se
BACKGROUND: PARADIGM SHIFTS • Advances in hardware and computer
systems • Cheaper storage, faster CPUs, and
faster networking • Parallel computing, Cloud computing
• Abundance of data • Sensor systems revolution • Internet services, Social media • Mobility and connectedness • Improved Data collection capabilities
• Data analysis • Scale and complexity
enable/require new algorithms • Success stories
• Facebook, Google, …
www.sics.se
BIG DATA: MANY CHALLENGES
• Computations and platforms • Hardware / Infrastructure / Data Centers • Storage/communication/networking • Programming concepts • Code/ Compilation/ Scheduling
• Algorithms • Scalability • Complexity • Decentralization • Time requirements
• Data analysis • Representation / Modelling • Domain knowledge • Visualization
• Deployment • Business models / Services • Security / Privacy / Legal aspects • Power / Environment
www.sics.se
Data cleaning
Representation
Validation
Deployment
Neural Networks
Logical Inference
Case-based
Statistical Methods
(BIG) DATA ANALYTICS IN PRACTICE
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BIG DATA PROMISES • Extraction of valuable information from
large data sets
• Increasing volumes of data lead to increasing value of extracted information
• Uncovering of otherwise hidden and valuable information
• Connected vehicles + big data analytics
• Novel services
• Improved efficiency and productivity
• Competitive edge
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TRENDS IN BIG DATA RESEARCH
• Strategies for surviving the data flood
• Learning Representation
• Taking advantage of structure:
• Graph Processing
• Big data transformed to Small data
• Platform/algorithm interplay
• Local vs global computation
• Streaming data
• Store and communicate models
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REAL TIME TRAFFIC AWARENESS
• High availability of traffic reports and collection of vehicle-based positioning data
• Allows modelling and prediction of traffic situation for individual vehicles
• Toyota will launch its Big data traffic information system for providing services for • optimal routes • predictions of travelling times
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FLEET MANAGEMENT
• ARI Fleet collect thousands of data types from each vehicle in its fleet (a million vehicles)
• Applying state-of-the-art big data analytics helps ARI Fleet make substantial savings through • timely and precise
maintenance scheduling
• improved transport scheduling
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MANUFACTURING
• Collecting and anlysing data from
• Driver behavior
• Vehicle behavior
• Service and maintenance cycles
• … can give manufacturers valuable insights into how to improve driving experience and security aspects already in design stage
• Range Rover’s Best Suv of the year (2012) model Evoque was designed taking into account extensive simulations based on analysis of collected data from the performance and behavior of earlier models
www.sics.se
Res
ourc
e m
anag
emen
t
THE DATA DRIVEN SYSTEMS STACK, EXAMPLES OF WORK AT SICS
Stream processing,
Pig
Information Centric Networking, SDN
HOPS as Platform As a Service
Scalable HDFS
SicsthSense Network Search SDN Monitoring
Text and Social Media
MapReduce Stratosphere Spark
Autonomous RAN
Ja Be Ja Graph
Clustering
Anomaly / change
detection
Traffic and mobility
modeling
Data collection
Networking
Storage
Computing
Frameworks
Domain specific
www.sics.se
TAKE AWAY LESSONS
• Big data analytics does not come out of the box
• Need domain knowledge for meaningful data analysis
• Every domain of application of BDA requires unique analysis, modelling, and deployment
• Paradigm change in ICT and Society
1. Information is power – extracting value from data is becoming the crucial competitive advantage
2. ICT is becoming data and service centric – Application driven; compute, storage and communication viewed as services
3. ICT is becoming an integrated part of products and services
