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Monitoring and Adaptation of Future Internet Apps
- 1. 1
© Prof. Dr. Klaus Pohl
©paluno
Cockpits:
Real-time Monitoring and
Adaptation of Future Internet
Applications
Prof. Dr. Klaus Pohl
CAiSE – June, 2013
©paluno
2
paluno
The Ruhr Institute for Software Technology
2
www.paluno.uni-due.dewww.paluno.uni-due.de
©paluno
1. The Future Internet
2. Use Cases & Cockpits
3. Pro-Active Responsiveness
4. Summary
Agenda
©paluno
Focusing on infrastructure and communication,
i.e., worldwide connectivity, bandwidth, speed, …
e.g., e‐mail, gopher, WWW, …
1990 …
Access to contents and information from
everywhere and by everyone
e.g., Google, Yahoo, youtube, facebook, …
2000 …
The Internet connects the world…
- 2. 2
© Prof. Dr. Klaus Pohl
©paluno
The Internet in 2010
Internet of Services
Internet of Things
Internet of Content
NEW
NEW
©paluno
Internet of Services
6
• Globally accessible software functions (services)
• IT-mediated access to human-provided capabilities
• Servicification of products
• Cloud services
• Cross-organizational alignment of IT systems
• Value-add services through seamless composition and integration
• …
©paluno
Internet of Services
Growth
7
Source: S. Ried und H. Kisker, „Sizing the Cloud“, Forrester Research, Inc.,
Apr. 2011., p. 9
Public Cloud Market Size
2020
$160 Billion
$20 Billion
2011
Infrastructure as a
Service: Compute,
Storage, Network
Platforms as a
Service
Applications/
Software as a Service
Business Processes
/ Workflows as a
Service
©paluno
Internet of Things
8
• Network connected devices
“connecting the world to the Internet”
• Digitization of real-world through
connected sensors and actuators
• Uniquely identifiable objects
Sources: data-directions.com; xively; DHL
- 3. 3
© Prof. Dr. Klaus Pohl
©paluno
Internet of Things
Growth
9Sources: GSMA und Machina Research, „The Connected Life: A USD4.5
trillion global impact in 2020“, GSMA, Feb. 2012., p. 3
Internet-connected Devices
24 Billion
(50% of which mobile)
9 Billion
2011
2020
(Smart-)Phones
Connected Things /
Sensors / Actuators
©paluno
Smart Energy
E ‐ Mobility
Enabler for novel types of
software‐intensive systems:
Future Internet Applications
Logistics
E ‐ Health
The Future Internet
Convergence of Services and Things
Internet of Services
Internet of Things
Internet of Content
Future
Internet
©paluno
On-demand
Garbage
Transport
Future Internet Applications
Example
Energy reduction: 20% (estimated)
[urbiotica.com]
©paluno
12
Future Internet Applications
Example
Water reduction: 60% (estimated)
Smart
Watering
Source: urbiotica
- 4. 4
© Prof. Dr. Klaus Pohl
©paluno
FP7 IP
Operational Trustworthiness
Enabling Technologies
FP7 IP
FI PPP
Core Platform
FP7 IP
Global Transport
and Logistics
(FI PPP Phase 1)
13
Future Internet FP7 projects @ paluno
FP7 IP
AgriFood, Transport
and Logistics
(FI PPP Phase 2)
FP 7 NoE
Secure Software Services & Systems
FP7 STREP
Safe Wireless High
Mobility Industrial
Systems
FP7 STREP
Adaptive Middleware for
Autonomous Services
FP7 STREP
Electricity and
Monitoring
System
FP7 STREP
Pervasive Computing
in Embedded
Systems
FP7 STREP
Smart Grid Key
Neighborhood
Indicator Cockpit
FP7 IP
Platform for Heterogeneous
Networked Cooperating Objects
FP 7 NoE
Software, Services & Systems
FP 7 NoE
Cooperating Objects
©paluno
1. The Future Internet
2. Use Cases & Cockpits
3. Pro-Active Responsiveness
4. Summary
Agenda
©paluno
Facts:
Duration: 04/11 – 03/14
Total cost: 54 Million EUR
Facts:
Duration: 04/11 – 03/14
Total cost: 54 Million EUR
Platform for cost-effective creation
and delivery of services, providing high
QoS and security
The Future Internet
FI-WARE Core Platform
©paluno
TrustandSecurity
Functionality
Apps &
Services
Internet of
Things
Data &
Context
Cloud
Interface
to Network
& Devices
FI-
CoDE
(Tools)
FI-WARE
Generic Enablers
VM
Management
GE
Service
Marketplace
GE
VM
Management
GE
IoT Broker
GE
VM
Management
GE
VM
Management
GE
VM
Management
GE
Online
Testing
GE
VM
Management
GE
Cloud Proxy
GE
VM
Management
GE
BigData
Analysis
GE
Security & Trust
VM
Management
GE
Identity
Management
GE
> 30 GEs:
http://catalogue.fi-ware.eu/
> 30 GEs:
http://catalogue.fi-ware.eu/
- 5. 5
© Prof. Dr. Klaus Pohl
©paluno
17
Future Internet Public Private Partnership
FI-WARE
Expansion of
Use Cases
FIspace
FITMAN
XIFI
INFINITY
ENVIROFI
2011 2012 2013 2014 2015
Phase 3 (Expansion)Phase 1 (Use Cases) Phase 2 (Trials)
FI-CONTENT
OUTSMART
SAFECITY
FINSENY
SMARTAGRIFOOD
INSTANT MOBILITY
FINEST
TF Extension and Usage
FI-CONTENT 2
Finesce
FI-STAR
Technical Coordinator
Research Partner (1 of 5)
Technical Architect
©paluno
FP 7 IP FInest
Use of Generic Enablers
• 4 GEs integrated into the proof-of-concepts (demos)
• 15 GEs considered for FInest technical specification
18
www.finest-ppp.euwww.finest-ppp.eu
©paluno
Future Internet Applications
Logistic Use Cases
1 4
3
5
2
6
8
7
Farming in the Cloud
1. Crop Protection Information Sharing
2. Greenhouse Management & Control
Perishable Goods Logistics
3. Fish Distribution and (Re-)Planning
4. Fruit & Vegetables Quality Assurance
5. Flowers/Plants Supply Chain
Monitoring
Distribution & Consumption
6. Meat Information Provenance
7. Import & Export of Consumer Goods
8. Tailored Information for Consumers
Robust Transport Chains
8. Parcel and package pre-run
9. Multi-modal container transport
8
9
©paluno
• Common solution for specific
application areas, e.g.,
• Emergency
• Disaster management
• Chemical plants
• Production automation
• Human-in-the-Loop
• Monitoring
• Analysis
• Decision-making
• Adaptation (execution of)
Monitoring & Adapting Operational Processes
Cockpits and Control Centres
Sources: npc.org, parabolicarc
20
- 6. 6
© Prof. Dr. Klaus Pohl
©paluno
Cockpits for Future Internet Applications
Cockpits /
Control Centre
P
D
A
Sensor
Effector
Software
Service
Software
Service
IoS
IoT
21
©paluno
Cockpits for Future Internet Applications
Multi-modal Container Transport
22
http://www.youtube.com/watch?v=hySGKbEEsyo
Monitoring Information
Adaptation Guidance
©paluno
Cockpits for Future Internet Applications
Functional Building Blocks
Future‐Internet‐Cockpit
Human
Operator
Know-
ledge
Plans, Models, …
Changes
Past Events
Alarm/
Monitor
Analyze
Execute
Cockpit Front End
IoT & IoS Gateway
Info Alternatives
Plan
Observation
Event
Decision
Action
Adaptation Need
Selection
23
Service
IoS
IoTMAPE
LOOP
Suitable
Abstractions to
support
Human
Interactions
Dynamically
mapping of
monitoring
information to
Application
Models
23
Incl.
Predictive
Capabilities
Incl.
Predictive
Capabilities
+ Fault
Prediction
+ Failure
Prediction
©paluno
1. The Future Internet
2. Use Cases & Cockpits
3. Pro-Active Responsiveness
4. Summary
Agenda
- 7. 7
© Prof. Dr. Klaus Pohl
©paluno
Fault
Machine or environment (incl. third-party services)
do not behave as expected
Failure
Experienced violation of requirement of service-based
application
Assume that a fault is observed
e.g., violation of service contract
Three possible cases
All Requirements are still valid
• no adaptation needed
Some Requirements violated + violation experienced in real world
• Failure detection reactive adaptation
Some Requirements violated, but violation not experience yet
• Failure prediction proactive adaptation
25
Future Internet Cockpits
Proactive Responsiveness
Source: Carlo Ghezzi; Keynote @ ServiceWace 2010, Ghent
©paluno
• Reactive Adaptation
• Repair/compensate failure
already visible for end-user
• Proactive Adaptation (Case 1)
• A fault occurs and will lead to a
failure?
• Repair/compensate fault to
prevent failure
• Proactive Adaptation (Case 2)
A fault is imminent, but did not yet
occur
• Modify system before fault
actually occurs
26
FailureFault!
Fault?
Failure
Future Internet Cockpits
Proactive Adaptation
©paluno
Time Series Prediction:
extrapolate future quality based on past observation
Online Testing:
complement monitoring data with testing data
Machine Learning/Data Mining:
prediction models trained using historic monitoring
data
Run-time Verification: formal analysis to
ascertain predefined properties hold
Static Analysis: infer properties of artifact
Simulation: execute dynamic models
Predictive Event-Processing:
extends complex event processing
with fault/failure prediction capabilities
Future Internet Cockpits
Pro-Active Failure Prediction
©paluno
28
Failure Prediction
Example: Predictive Complex Event Processing
• Extension of Complex Event Processing
Y. Engel, O. Etzion, “Towards proactive event‐driven
computing,” DEBS 2011
Fault Prediction
Failure Prediction
Proactive
Adaptation
Monitoring
- 8. 8
© Prof. Dr. Klaus Pohl
©paluno
Use Case - Airfreight
• Focus: High Shows / Low Shows
• Discrepancy between booked weight
and actual weight delivered
• Can result in
• Over-loaded flights
• Under-loaded flights
Inefficient use of transport assets
Transport delays, additional transports
Failure Prediction
Example: Predictive Complex Event Processing
©paluno
• Empirical Validation
• IATA Cargo 2000 Monitoring Standard
• Cargo 2000 Monitoring data of a large forwarding company
• Five months of operational data
• Approximately 151,000 transport processes
(80% for training; 20% test data)
Failure Prediction
Example: Predictive Complex Event Processing
Airline (Carrier)
Import
Forwarder
Export
Forwarder
BKD
PUP
REW
DEH
FWB
DOC
RCS
DEP
ARR
RCF
NFD
AWD
DLV
REH
OFD
POD
Shipper (Customer)
Consignee
DEH: Truck Departure to Airline
FWB: Master Airway Bill Creation
DOC: Truck Arrival at Departure Airline
BKD: Freight Booking by Shipper
PUP: Pick up from Customer
REW: Freight Received Forwarder
RCS: Freight Checked in at Airline
…
©paluno
Results
• 586 over-loaded flights
532 under-loaded flights
• Predictive CEP fosters early warning
Failure Prediction
Example: Predictive Complex Event Processing
Accuracy over-load warnings:
Precision: 99%
Recall: 70%
Accuracy under-load warnings:
Precision: 80%,
Recall: 95%
Z. Feldmann, F. Fournier, R. Franklin, and A. Metzger, “Proactive
event processing in action: A case study on the proactive
management of transport processes,” DEBS 2013
Mean Warning time:
58 hours (before departure)
©paluno
1. The Future Internet
2. Use Cases & Cockpits
3. Pro-Active Responsiveness
4. Summary
Agenda
- 9. 9
© Prof. Dr. Klaus Pohl
©paluno
Future‐Internet‐Cockpit
Cockpits: Real-time Monitoring and
Adaptation of Future Internet Applications
Know-
ledge
Plans, Models, …
Changes
Past Events
Alarm/
Monitor
Analyze
Execute
Cockpit Front End
IoT & IoS Gateway
Info Alternatives
Plan
Observation
Event
Decision
Action
Adaptation Need
Selection
33
Service
IoS
IoT
33
+ Fault
Prediction
+ Failure
Prediction
©paluno
34
Challenges for Future Internet Applications
High Complexity
Source: L. Northrop, Keynote, ICSE 2013
©paluno
Ultra Large Scale Systems
Cyber Physical Systems
Socio-technical Systems
Challenges for Future Internet Applications
High Complexity
Sources: umd.edu; Acatech; libelium
Smart Grids Multimodal Transport
Smart Cities
©paluno
Sources: NESSI; IFIP; Forester
2020
$160 Billion
$20 Billion
2011
Challenges for Future Internet Applications
Servicification of Products
Physical goods and products are
Enhanced and extended by services
Even fully turned into services, e.g.,
car sharing, washing-machine-as-a-
service, drilling-as-a-service, …
Immaterial products
Business processes (BPaaS)
Software (SaaS)
Platforms (PaaS)
Infrastructure (IaaS)
Content/Data (CaaS, DaaS)
…
- 10. 10
© Prof. Dr. Klaus Pohl
©paluno
37
Data Flood (Tsunami)
Contents, Media, Documents
Source: IDC´s Digital Universe Study, sponsored by EMC, December 2012
Global Data Volume
2020
2011
40.000 Exabyte
1.000 Exabyte
• 1 Exabyte = 1 million Terabyte
= 12 stacks of books from earth to Sun
• 4.000 Exabyte
= 160 stacks of books from earth to Pluto
Basically all this information has been produced
in the last 20 years
©paluno
38
Challenges for Future Internet Applications
Fast-paced Technology and Societal Changes
Sources: facebook, Ben Foster; dreamgrow.com
2004
2011
900 Million
Launch of
Facebook
March 2013
# of Users
1.11 billion
March 2013
# of Users
1.11 billion
©paluno
39
Challenges for Future Internet Applications
Fast-paced Technology and Societal Changes
©paluno
40
Summary – Radical Change / Revolution
- 11. 11
© Prof. Dr. Klaus Pohl
©paluno
Further Information:
www.paluno.eu
www.sse.uni-due.de