Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Principles for Engineering Elastic IoT
Cloud Systems
Hong-Linh Truong
Joint work with Georgiana Copil, Schahram Dustdar, D...
Outline
 IoT cloud systems and engineering principles
 Models and techniques
 Tooling
 Demo
 Conclusions and Future W...
Elastic IoT Cloud systems and
engineering princinples
SummerSOC 2015 3
Scenario
SummerSOC 2015 4
Offers services for
handling IoT Data
Offers services for
handling IoT Data
Offers services for ...
Elasticity analytics – observations
 Elasticity of IoT elements
 Activate/change sensor deployment/configurations for
re...
IoT Cloud SystemIoT Cloud System
Our view on IoT Cloud Systems
 IoT cloud systems: IoT elements and cloud services
 A co...
Engineering perspectives
SummerSOC 2015 7
End-to-end
Engineering and
Optimization
Development
and
Production
Symbiosis
Ela...
Principles (1-2)
1. Enable virtualization and composition of IoT
components as unit
Selection, composition, pay-per-use
2....
Principles (3-5)
3. Enable dynamic provisioning of IoT and cloud
service units through uniform marketplaces and
repositori...
Principles (6-7)
6. Provide monitoring and analysis for an end-to-
end view on elasticity and dependability
properties
7. ...
Models & Techniques
11SummerSOC 2015
Programming frameworks
and languages for software-
defined elastic services
Programming frameworks
and languages for softw...
Software-defined Elastic Service
13
How to represent IoT elements and cloud services under
the same view?
SummerSOC 2015
Software-Defined IoT Units
 Virtualizing IoTs resources under “service
units” with software-defined API for
accessing, co...
Software-defined machines (SDMs)
for IoT
SummerSOC 2015 15
Hong Linh Truong, Schahram Dustdar: Principles for Engineering ...
Information for elastic configuration
SummerSOC 2015 16
Duc-Hung Le, Hong-Linh Truong and Schahram Dustdar, Managing Infor...
Elasticity primitive operations
17
For the cloud services
For IoT elements
SummerSOC 2015
Primitive operations: actions ca...
Elasticity Model for Cloud Services
Moldovan D., G. Copil,Truong H.-L., Dustdar S. (2013). MELA:
Monitoring and Analyzing ...
Specifying and controling elasticity
Basic constructs
Schahram Dustdar, Yike Guo, Rui Han,
Benjamin Satzger, Hong Linh Tru...
TOOLS
SummerSOC 2015 20
Monitoring, Controlling and Testing
IoT Cloud Systems
SummerSOC 2015 21
Check: http://tuwiendsg.github.io/iCOMOT/demo.html
Elasticity Information as a Service
SummerSOC 2015 22
https://github.com/tuwiendsg/ELISEhttps://github.com/tuwiendsg/ELISE...
SALSA- Multi-cloud, multi-stack,
complex topologies configuration
23
 Well-defined APIs for manipulating and provisioning...
High level elasticity control
#SYBL.CloudServiceLevel
Cons1: CONSTRAINT responseTime < 5 ms
Cons2: CONSTRAINT responseTime...
Elasticity space and pathway analytics
25
Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, "MELA: Ela...
rtGovOps – Governance
capabilities
 Governance capabilities:
 Any function that „manipulates“ an IoT cloud resource
 Bu...
iCOMOT -- Toolsets and actions for
IoT Cloud Systems
27SummerSOC 2015
http://tuwiendsg.github.io/iCOMOT/
Hong-Linh Truong,...
DEMO
http://tuwiendsg.github.io/iCOMOT/
SummerSOC 2015 28
Conclusions and Outlook
 Engineering IoT cloud systems
 Deal with complex IoT elements and cloud services
 Coordinating...
Thanks for your
attention!
Questions?
Hong-Linh Truong
Distributed Systems Group
TU Wien
dsg.tuwien.ac.at/research/viecom
...
Upcoming SlideShare
Loading in …5
×

Principles for Engineering Elastic IoT Cloud Systems

1,058 views

Published on

Published in: Education
  • Be the first to comment

  • Be the first to like this

Principles for Engineering Elastic IoT Cloud Systems

  1. 1. Principles for Engineering Elastic IoT Cloud Systems Hong-Linh Truong Joint work with Georgiana Copil, Schahram Dustdar, Duc-Hung Le, Daniel Moldovan, Stefan Nastic Distributed Systems Group TU Wien truong@dsg.tuwien.ac.at dsg.tuwien.ac.at/research/viecom SummerSOC 2015, Hersonissos, 2nd July, 2015 1
  2. 2. Outline  IoT cloud systems and engineering principles  Models and techniques  Tooling  Demo  Conclusions and Future Work SummerSOC 2015 2
  3. 3. Elastic IoT Cloud systems and engineering princinples SummerSOC 2015 3
  4. 4. Scenario SummerSOC 2015 4 Offers services for handling IoT Data Offers services for handling IoT Data Offers services for big, data analytics Offers services for big, data analytics Offers services for complex problem solving using human experts Offers services for complex problem solving using human experts IoT Cloud Platform Data Analytics Platform Expert Provisioning Platform Sensors <<send data>> <<analyze data>> <<notify possible problem>> <<control/configure sensors>> Predictive maintenance companyPredictive maintenance company <<monitor>> Chillers <<predict and solve problems>> <<control services>> <<control algorithms>>
  5. 5. Elasticity analytics – observations  Elasticity of IoT elements  Activate/change sensor deployment/configurations for required data; changing communication protocols; deploying new sensors  Elasticity of cloud platform services  Deploy/reconfigure cloud services handling changing data  Elasticity of data analytics  Switch and combine different types of data analytics processes and engines due to the severity of problems and quality of results  Elasticity of teams of human experts  Forming and changing different configurations of teams during specific problems and problem severity SummerSOC 2015 5
  6. 6. IoT Cloud SystemIoT Cloud System Our view on IoT Cloud Systems  IoT cloud systems: IoT elements and cloud services  A coherent view atop IoT elements and cloud services! SummerSOC 2015 6 Application Hong Linh Truong, Schahram Dustdar: Programming Elasticity in the Cloud. IEEE Computer 48(3): 87-90 (2015)Hong Linh Truong, Schahram Dustdar: Programming Elasticity in the Cloud. IEEE Computer 48(3): 87-90 (2015)
  7. 7. Engineering perspectives SummerSOC 2015 7 End-to-end Engineering and Optimization Development and Production Symbiosis Elasticity Coherence Hong Linh Truong, Schahram Dustdar: Principles for Engineering IoT Cloud Systems. IEEE Cloud Computing 2(2): 68-76 (2015)Hong Linh Truong, Schahram Dustdar: Principles for Engineering IoT Cloud Systems. IEEE Cloud Computing 2(2): 68-76 (2015)
  8. 8. Principles (1-2) 1. Enable virtualization and composition of IoT components as unit Selection, composition, pay-per-use 2. Enable emulated/simulated IoT parts working with production cloud services Symbiotic development and operation SummerSOC 2015 8
  9. 9. Principles (3-5) 3. Enable dynamic provisioning of IoT and cloud service units through uniform marketplaces and repositories for multiple stakeholders 4. Provide multi-level software stack deployment and configuration 5. Provide software-defined elasticity and governance primitive functions for all IoT units and cloud service units SummerSOC 2015 9
  10. 10. Principles (6-7) 6. Provide monitoring and analysis for an end-to- end view on elasticity and dependability properties 7. Coordinate elasticity to enable a coherent elastic execution through the whole IoT cloud systems SummerSOC 2015 10
  11. 11. Models & Techniques 11SummerSOC 2015
  12. 12. Programming frameworks and languages for software- defined elastic services Programming frameworks and languages for software- defined elastic services Deploying and configuring for elastic object Deploying and configuring for elastic object Controlling Elastic ObjectsControlling Elastic Objects Monitoring and Analyzing Elasticity Monitoring and Analyzing Elasticity Programming Elasticity in IoT Cloud Systems SummerSOC 2015 12  Conceptualizing elastic objects for IoT elements and cloud services  Programming „the world of elastic objects“  Developing elastic cloud software Hong Linh Truong, Schahram Dustdar: Programming Elasticity in the Cloud. IEEE Computer 48(3): 87-90 (2015)Hong Linh Truong, Schahram Dustdar: Programming Elasticity in the Cloud. IEEE Computer 48(3): 87-90 (2015) Testing ElasticityTesting Elasticity
  13. 13. Software-defined Elastic Service 13 How to represent IoT elements and cloud services under the same view? SummerSOC 2015
  14. 14. Software-Defined IoT Units  Virtualizing IoTs resources under “service units” with software-defined API for accessing, configuring and controlling units  Composing and creating gateways and virtual topologies (of multiple gateways)  Provisioning (atomic and composite) units dynamically and on-demand in cloud and edge computing environments Software-defined IoT Unit FunctionalAPI Utility cost-function IoT resource and functionality binding Late-bound policies Infrastructure capabilities GovernanceAPI Dependency units Provisioning API Runtime mechanisms Runtime controllers (e.g, elasticity) Non-functionalaspects Runtime composition Functionalaspects SummerSOC 2015 14 Stefan Nastic, Sanjin Sehic, Le-Duc Hung, Hong-Linh Truong, and Schahram Dustdar (2014). Provisioning Software-defined IoT Cloud Systems. The 2nd International Conference on Future Internet of Things and Cloud (FiCloud-2014), August27-29, 2014, Barcelona, Spain. Stefan Nastic, Sanjin Sehic, Le-Duc Hung, Hong-Linh Truong, and Schahram Dustdar (2014). Provisioning Software-defined IoT Cloud Systems. The 2nd International Conference on Future Internet of Things and Cloud (FiCloud-2014), August27-29, 2014, Barcelona, Spain.
  15. 15. Software-defined machines (SDMs) for IoT SummerSOC 2015 15 Hong Linh Truong, Schahram Dustdar: Principles for Engineering IoT Cloud Systems. IEEE Cloud Computing 2(2): 68-76 (2015)Hong Linh Truong, Schahram Dustdar: Principles for Engineering IoT Cloud Systems. IEEE Cloud Computing 2(2): 68-76 (2015)
  16. 16. Information for elastic configuration SummerSOC 2015 16 Duc-Hung Le, Hong-Linh Truong and Schahram Dustdar, Managing Information for Dynamic Configuration of Elastic IoT Cloud Systems, June 2015. On submission Duc-Hung Le, Hong-Linh Truong and Schahram Dustdar, Managing Information for Dynamic Configuration of Elastic IoT Cloud Systems, June 2015. On submission We must be able to capture different types of information Types of information Information model
  17. 17. Elasticity primitive operations 17 For the cloud services For IoT elements SummerSOC 2015 Primitive operations: actions can be performed on elastic objects to change their elasticity states Change communication protocols; change sensor frequency; activating/deactivating sensors, gateways configuration, etc. Change communication protocols; change sensor frequency; activating/deactivating sensors, gateways configuration, etc.
  18. 18. Elasticity Model for Cloud Services Moldovan D., G. Copil,Truong H.-L., Dustdar S. (2013). MELA: Monitoring and Analyzing Elasticity of Cloud Service. CloudCom 2013 Moldovan D., G. Copil,Truong H.-L., Dustdar S. (2013). MELA: Monitoring and Analyzing Elasticity of Cloud Service. CloudCom 2013 Elasticity space functions: to determine if a service unit/service is in the “elasticity behavior” Elasticity space functions: to determine if a service unit/service is in the “elasticity behavior” Elasticity Pathway functions: to characterize the elasticity behavior from a general/particular view Elasticity Pathway functions: to characterize the elasticity behavior from a general/particular view Elasticity Space SummerSOC 2015 18
  19. 19. Specifying and controling elasticity Basic constructs Schahram Dustdar, Yike Guo, Rui Han, Benjamin Satzger, Hong Linh Truong: Programming Directives for Elastic Computing. IEEE Internet Computing 16(6): 72-77 (2012) Schahram Dustdar, Yike Guo, Rui Han, Benjamin Satzger, Hong Linh Truong: Programming Directives for Elastic Computing. IEEE Internet Computing 16(6): 72-77 (2012) SYBL (Simple Yet Beautiful Language) for specifying elasticity requirements SYBL-supported requirement levels Cloud Service Level Service Topology Level Service Unit Level Relationship Level Programming/Code Level Current SYBL implementation in Java using Java annotations @SYBLAnnotation(monitoring=„“,constraints=„“,strategies=„ “) in XML <ProgrammingDirective><Constraints><Constraint name=c1>...</Constraint></Constraints>...</Programm ingDirective> as TOSCA Policies <tosca:ServiceTemplate name="PilotCloudService"> <tosca:Policy name="St1" policyType="SYBLStrategy"> St1:STRATEGY minimize(Cost) WHEN high(overallQuality) </tosca:Policy>... SummerSOC 2015 19 Runtime needs elasticity primitive opertations!
  20. 20. TOOLS SummerSOC 2015 20
  21. 21. Monitoring, Controlling and Testing IoT Cloud Systems SummerSOC 2015 21 Check: http://tuwiendsg.github.io/iCOMOT/demo.html
  22. 22. Elasticity Information as a Service SummerSOC 2015 22 https://github.com/tuwiendsg/ELISEhttps://github.com/tuwiendsg/ELISE Collecting configuration information from different phases Scalable and extensible runtime system Duc-Hung Le, Hong-Linh Truong and Schahram Dustdar, Managing Information for Dynamic Configuration of Elastic IoT Cloud Systems, June 2015. On submission Duc-Hung Le, Hong-Linh Truong and Schahram Dustdar, Managing Information for Dynamic Configuration of Elastic IoT Cloud Systems, June 2015. On submission
  23. 23. SALSA- Multi-cloud, multi-stack, complex topologies configuration 23  Well-defined APIs for manipulating and provisioning objects  Support different types of objects, e.g., VMs, OS containers, services, service containers, IoT sensors, and gateways Data center services Sensors https://github.com/tuwiendsg/SALSAhttps://github.com/tuwiendsg/SALSA SummerSOC 2015
  24. 24. High level elasticity control #SYBL.CloudServiceLevel Cons1: CONSTRAINT responseTime < 5 ms Cons2: CONSTRAINT responseTime < 10 ms WHEN nbOfUsers > 10000 Str1: STRATEGY CASE fulfilled(Cons1) OR fulfilled(Cons2): minimize(cost) #SYBL.ServiceUnitLevel Str2: STRATEGY CASE ioCost < 3 Euro : maximize( dataFreshness ) #SYBL.CodeRegionLevel Cons4: CONSTRAINT dataAccuracy>90% AND cost<4 Euro #SYBL.CloudServiceLevel Cons1: CONSTRAINT responseTime < 5 ms Cons2: CONSTRAINT responseTime < 10 ms WHEN nbOfUsers > 10000 Str1: STRATEGY CASE fulfilled(Cons1) OR fulfilled(Cons2): minimize(cost) #SYBL.ServiceUnitLevel Str2: STRATEGY CASE ioCost < 3 Euro : maximize( dataFreshness ) #SYBL.CodeRegionLevel Cons4: CONSTRAINT dataAccuracy>90% AND cost<4 Euro Georgiana Copil, Daniel Moldovan, Hong-Linh Truong, Schahram Dustdar, "SYBL: an Extensible Language for Controlling Elasticity in Cloud Applications", 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), May 14-16, 2013, Delft, Netherlands Georgiana Copil, Daniel Moldovan, Hong-Linh Truong, Schahram Dustdar, "SYBL: an Extensible Language for Controlling Elasticity in Cloud Applications", 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), May 14-16, 2013, Delft, Netherlands https://github.com/tuwiendsg/rSYBLhttps://github.com/tuwiendsg/rSYBL SummerSOC 2015 24
  25. 25. Elasticity space and pathway analytics 25 Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, "MELA: Elasticity Analytics for Cloud Services", International Journal of Big Data Intelligence, 2015, Vol. 2, No. 1 Daniel Moldovan, Georgiana Copil, Hong-Linh Truong, Schahram Dustdar, "MELA: Elasticity Analytics for Cloud Services", International Journal of Big Data Intelligence, 2015, Vol. 2, No. 1 https://github.com/tuwiendsg/MELAhttps://github.com/tuwiendsg/MELA SummerSOC 2015
  26. 26. rtGovOps – Governance capabilities  Governance capabilities:  Any function that „manipulates“ an IoT cloud resource  Building blocks of operational governance (GovOps) processes  Executed „inside“ software-defined machines (SDMs)  Governance processes/strategies  Functional configuration  Performance  Uncertainty study  Risk study 26 https://github.com/tuwiendsg/GovOps/ SummerSOC 2015 Stefan Nastic, Michael Vögler, Christian Inzinger, Hong-Linh Truong, Schahram Dustdar, "rtGovOps: A Runtime Framework for Governance in Large- scale Software-defined IoT Cloud Systems", The 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, 2015 Stefan Nastic, Michael Vögler, Christian Inzinger, Hong-Linh Truong, Schahram Dustdar, "rtGovOps: A Runtime Framework for Governance in Large- scale Software-defined IoT Cloud Systems", The 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, 2015
  27. 27. iCOMOT -- Toolsets and actions for IoT Cloud Systems 27SummerSOC 2015 http://tuwiendsg.github.io/iCOMOT/ Hong-Linh Truong, Georgiana Copil, Schahram Dustdar, Duc-Hung Le, Daniel Moldovan, Stefan Nastic, "iCOMOT – a Toolset for Managing IoT Cloud Systems", 16th IEEE International Conference on Mobile Data Management, 15-18 June, 2015, Pittsburg, USA. (Demo) Hong-Linh Truong, Georgiana Copil, Schahram Dustdar, Duc-Hung Le, Daniel Moldovan, Stefan Nastic, "iCOMOT – a Toolset for Managing IoT Cloud Systems", 16th IEEE International Conference on Mobile Data Management, 15-18 June, 2015, Pittsburg, USA. (Demo)
  28. 28. DEMO http://tuwiendsg.github.io/iCOMOT/ SummerSOC 2015 28
  29. 29. Conclusions and Outlook  Engineering IoT cloud systems  Deal with complex IoT elements and cloud services  Coordinating elasticity across IoT platforms and cloud platforms is needed  Engineering an end-to-end elasticity for IoT cloud systems needs a complex set of tools  Ongoing work  Coordinated elasticity control for people and data elasticity in IoT cloud systems (ICSOC submissions)  Using iCOMOT to support testing, privacy/risk and uncertainty studies for IoT cloud systems  Data elasticity management in IoT cloud systems SummerSOC 2015 29
  30. 30. Thanks for your attention! Questions? Hong-Linh Truong Distributed Systems Group TU Wien dsg.tuwien.ac.at/research/viecom SummerSOC 2015 30

×