TUW-ASE Summer 2015: IoT Cloud Systems
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This document discusses Internet of Things (IoT) cloud integration and IoT cloud systems. It begins with an overview of cloud computing and the IoT. There are several common models for integrating IoTs and clouds, including using cloud platforms for data analytics and storage from sensors. Effective engineering of IoT cloud systems requires techniques like virtualization, composition and orchestration of services, and the ability to deploy across private, public and hybrid clouds. The integration of IoTs and clouds enables many application domains and helps connect physical things to online services.
TUW-ASE Summer 2015: IoT Cloud Systems
- 1. IoT Cloud Systems Hong-Linh Truong Distributed Systems Group, Vienna University of Technology truong@dsg.tuwien.ac.at http://dsg.tuwien.ac.at/staff/truong 1ASE Summer 2015 Advanced Services Engineering, Summer 2015 Advanced Services Engineering, Summer 2015
- 2. Outline Cloud computing Internet of Things (IoT) IoT and Cloud integration models IoT Cloud Systems Principles of Engineering IoT cloud systems ASE Summer 2015 2
- 3. IoT Cloud Platform Data Analytics Platform SCU Provisioning Platform Sensors <<send data>> <<analyze data>> <<notify possible problem>> <<maintain evaporator>> CRITICAL CLEAN CHILLER EVAPORATOR CRITICAL CLEAN CHILLER EVAPORATOR <<monitor>> <<establish SCU to predict and solve problems>> Recall: Predictive Maintenance 3ASE Summer 2015
- 4. 4 NIST Cloud definitions “This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.” Source: NIST Definition of Cloud Computing v15, http://csrc.nist.gov/groups/SNS/cloud-computing/cloud-def-v15.docSource: NIST Definition of Cloud Computing v15, http://csrc.nist.gov/groups/SNS/cloud-computing/cloud-def-v15.doc ASE Summer 2015 Data-as-a-Service? Human-as-a- Service?
- 5. 5 Some enabling techniques On-demand self- services Self-*, automatic service composition Resource pooling Virtualization, Cluster/Grid techniques, data center management Broad network access SOA, mobile, Internet technologies, interoperability APIs Rapid elasticity Self-*, resource management, performance monitoring Measured service Service contract, monitoring, billing ASE Summer 2015
- 6. Key engineering techniques Virtualization Compute resources (VMs, containers), networks, data, etc. Composition and orchestration REST/SOAP services, scalable protocols and rich sets of connectors for integration Private, Public and Hybrid clouds Complex topologies of resources/services On demand and pay-per-use Dynamic and runtime features (for virtualization, composition, and orchestration) Hot deployment techniques, fine-grained monitoring Elasticity engineering Resources, quality and cost based on customer-specific runtime constraints ASE Summer 2015 6
- 7. 7 Virtualization of machines using hypervisors Source: Kernel-based Virtual Machine (http://www.linux-kvm.org/page/Main_Page) Source: Kernel-based Virtual Machine (http://www.linux-kvm.org/page/Main_Page) Source: The XEN Hypervisor (http://www.xen.org/)Source: The XEN Hypervisor (http://www.xen.org/) Virtualization is a powerful concept: we can apply virtualization techniques virtually for everything! ASE Summer 2015
- 8. 8 Hybrid and Multi Clouds NIST on Hybrid clouds: “The cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds).” ASE Summer 2015 Multi-cloud environments/federated clouds Switch and combine multiple clouds May or may not be “bound together by standardized or proprietary technology”
- 9. Engineering your services atop hybrid/multicloud clouds 9 Interoperability protocols for multiple level of abstractions Virtual machines, networks, cloud management APIs Security cross multiple domains Complex data governance policies and service contracts Complex billing and monitoring Which resource models you need? Cloud bursting Multi-cloud distributed services ASE Summer 2015
- 10. Examples ASE Summer 2015 10 Source: Bahman Javadi, Jemal Abawajy, Rajkumar Buyya, Failure-aware resource provisioning for hybrid Cloud infrastructure, Journal of Parallel and Distributed Computing, Volume 72, Issue 10, October 2012, Pages 1318-1331, ISSN 0743-7315, Source: Bahman Javadi, Jemal Abawajy, Rajkumar Buyya, Failure-aware resource provisioning for hybrid Cloud infrastructure, Journal of Parallel and Distributed Computing, Volume 72, Issue 10, October 2012, Pages 1318-1331, ISSN 0743-7315, Source: Steven Abramson, William Horka, and Leonard Wisniewski. 2014. A Hybrid Cloud Architecture for a Social Science Research Computing Data Center. In Proceedings of the 2014 IEEE 34th International Conference on Distributed Computing Systems Workshops (ICDCSW '14). IEEE Computer Society, Washington, DC, USA, 45-50 Source: Steven Abramson, William Horka, and Leonard Wisniewski. 2014. A Hybrid Cloud Architecture for a Social Science Research Computing Data Center. In Proceedings of the 2014 IEEE 34th International Conference on Distributed Computing Systems Workshops (ICDCSW '14). IEEE Computer Society, Washington, DC, USA, 45-50
- 11. Hybrid cloud process ASE Summer 2015 11 Source: Neal Leavitt. 2013. Hybrid Clouds Move to the Forefront. Computer 46, 5 (May 2013), 15- 18. Source: Neal Leavitt. 2013. Hybrid Clouds Move to the Forefront. Computer 46, 5 (May 2013), 15- 18.
- 12. INTERNET OF THINGS (IOT) ASE Summer 2015 12
- 13. Internet of Things (IoT) Things and Objects Home Official Business, Hospital Factory Infrastructure How to make such things and objects being connected and interacting each other? To be part of the Internet? Why do we need this? ASE Summer 2015 13 http://www.control4.com/blog/2014/03/the- internet-of-things-and-the-connected-home
- 14. Smart Object Encapsulating Thing ASE Summer 2015 14 Smart Object Physical Embodiment/ Physic Features Communicati on capabilities Computing capabilities Identifier Addresses Sensing and or Actuating capabilities Daniele Miorandi, Sabrina Sicari, Francesco De Pellegrini, Imrich Chlamtac, Internet of things: Vision, applications and research challenges, Ad Hoc Networks, Volume 10, Issue 7, September 2012, Pages 1497-1516
- 15. Key properties Diversity Networks: Bluetooth, Ethernet, GPRS, LoRa, ZigBee, Wi-Fi, NFC/RFID, GPS, LonWorks, Modbus, RS-232, RS-485, etc. Application protocols (HTTP, MQTT, CoAP, etc.) Scale Network scale: Body Home City Internet- scale! Vertical/horizontal domain objects to be studied/managed Complexity Software stack, Network topology ASE Summer 2015 15
- 16. Management versus Service Offering ASE Summer 2015 16 Thing datacontrol Thing interaction datacontrol IoT ?Management of Things Management of Things Services from ThingsServices from Things
- 17. Connecting Things to Services ASE Summer 2015 17 Source: Luigi Atzori, Antonio Iera, Giacomo Morabito, The Internet of Things: A survey, Computer Networks, Volume 54, Issue 15, 28 October 2010, Pages 2787-2805, ISSN 1389-1286 Source: Luigi Atzori, Antonio Iera, Giacomo Morabito, The Internet of Things: A survey, Computer Networks, Volume 54, Issue 15, 28 October 2010, Pages 2787-2805, ISSN 1389-1286 Conceptual view Where is the boundary between IoT and clouds?
- 18. Application domains ASE Summer 2015 18 Source: Luigi Atzori, Antonio Iera, Giacomo Morabito, The Internet of Things: A survey, Computer Networks, Volume 54, Issue 15, 28 October 2010, Pages 2787-2805, ISSN 1389-1286 Source: Luigi Atzori, Antonio Iera, Giacomo Morabito, The Internet of Things: A survey, Computer Networks, Volume 54, Issue 15, 28 October 2010, Pages 2787-2805, ISSN 1389-1286
- 19. IOT + CLOUD INTEGRATION ASE Summer 2015 19
- 20. Connecting data centers to IoTs 20 Data Center: Processing, Storage, Networking, Management, Distribution IoT devices: Gateways, Sensors, Actuators, Topologies of Gateways SOCloud 2015 Source: http://www.control4.com/blog/2014/03/the- internet-of-things-and-the-connected-home Source: http://www.infoescola.com/wp-content/uploads/2013/01/datacenter-google.jpg
- 21. Example (1) ASE Summer 2015 21 Source: Eric D. Simmon; Kyoung-sook Kim; Eswaran Subrahmanian; Ryong Lee; Frederic J. de Vaulx; Yohei Murakami; Koji Zettsu; Ram D. Sriram, A Vision of Cyber-Physical Cloud Computing for Smart Networked Systems, August 26, 2013, http://www.nist.gov/manuscript- publication-search.cfm?pub_id=914023 Source: Eric D. Simmon; Kyoung-sook Kim; Eswaran Subrahmanian; Ryong Lee; Frederic J. de Vaulx; Yohei Murakami; Koji Zettsu; Ram D. Sriram, A Vision of Cyber-Physical Cloud Computing for Smart Networked Systems, August 26, 2013, http://www.nist.gov/manuscript- publication-search.cfm?pub_id=914023
- 22. Example (2) ASE Summer 2015 22 Source: SWEEB: Semantic Web-enabled Energy Efficient Buildings Niccolo' De Caro (Vrije Universiteit Brusse sensys.acm.org/2013/sensys13DC/decaro.pdf Source: SWEEB: Semantic Web-enabled Energy Efficient Buildings Niccolo' De Caro (Vrije Universiteit Brusse sensys.acm.org/2013/sensys13DC/decaro.pdf Source: Aqeel H. Kazmi, Michael J. O'grady, Declan T. Delaney, Antonio G. Ruzzelli, and Gregory M. P. O'hare. 2014. A Review of Wireless-Sensor-Network-Enabled Building Energy Management Systems. ACM Trans. Sen. Netw. 10, 4, Article 66 (June 2014), 43 pages. DOI=10.1145/2532644 http://doi.acm.org/10.1145/2532644 Source: Aqeel H. Kazmi, Michael J. O'grady, Declan T. Delaney, Antonio G. Ruzzelli, and Gregory M. P. O'hare. 2014. A Review of Wireless-Sensor-Network-Enabled Building Energy Management Systems. ACM Trans. Sen. Netw. 10, 4, Article 66 (June 2014), 43 pages. DOI=10.1145/2532644 http://doi.acm.org/10.1145/2532644 Your examples?
- 23. Example – Look at the Internet ASE Summer 2015 23 Xively Platform in Cloud http://www.ptc.com/File%20Library/Axeda/whitepapers/Axeda_ WP_Platform_TechOverview_011714_singles_PRINT_no_cro ps.pdf https://www.google.at/search?q=IoT+cloud+integration Read: Alessio Botta, Walter de Donato, Valerio Persico, Antonio Pescapè: On the Integration of Cloud Computing and Internet of Things. 23-30:
- 24. IoT + Cloud integration models What are common network structures? What are common data and control flows or interactions between IoT and clouds? What are common types of applications? What are common data models for IoT? ASE Summer 2015 24
- 25. IOT CLOUD SYSTEMS ASE Summer 2015 25
- 26. IoT Cloud Platform Data Analytics Platform SCU Provisioning Platform Sensors <<send data>> <<analyze data>> <<notify possible problem>> <<maintain evaporator>> CRITICAL CLEAN CHILLER EVAPORATOR CRITICAL CLEAN CHILLER EVAPORATOR <<monitor>> <<establish SCU to predict and solve problems>> Recall: Predictive Maintenance 26ASE Summer 2015
- 27. Our view on IoT Cloud System But we do not want a separation! How to build a coherent view! ASE Summer 2015 27 IoT Cloud SystemIoT Cloud System Application
- 28. Example of an application model atop IoT Cloud ASE Summer 2015 28 Source: Kirak Hong, David Lillethun, Umakishore Ramachandran, Beate Ottenwälder, and Boris Koldehofe. 2013. Mobile fog: a programming model for large-scale applications on the internet of things. In Proceedings of the second ACM SIGCOMM workshop on Mobile cloud computing (MCC '13). ACM, New York, NY, USA, 15-20. When we need to run application components across IoT and clouds
- 29. Lifting IoT software stack Virtualization Virtualization of software components for certain requirements: e.g., for a single application/domain Composition and orchestration Complex topologies of IoT components Software-defined capabilities Management done via APIs at runtime Cloud connectivity Hide low level network stuffs ASE Summer 2015 29
- 30. Example of composition and virtualization techniques ASE Summer 2015 30 Atomic software-defined IoT units Custom proc. logic IoT data storage Communication In-memory image VPN Messaging Sand box Network overlay ProtocolVolatile History Key/Value store Security Data quality Outliers filter IoT compute GW runtime Data point controller CEP Component -model Elasticity Auto scaling group controller Functional capabilities Non-functional capabilities ... ... Monitor. Config. Stefan Nastic, Sanjin Sehic, Duc-Hung Le, Hong Linh Truong, Schahram Dustdar: Provisioning Software-Defined IoT Cloud Systems. FiCloud 2014: 288-295 Stefan Nastic, Sanjin Sehic, Duc-Hung Le, Hong Linh Truong, Schahram Dustdar: Provisioning Software-Defined IoT Cloud Systems. FiCloud 2014: 288-295
- 31. Abstract software-defined machines (SDMs) for IoT ASE Summer 2015 31
- 32. ASE Summer 2015 32 Can be build SDM with current technologies? with e.g. Raspberry Pi, docker, routers? If we have virtualization and composition and software- defined capabilities in both IoT and Cloud
- 33. IoT Cloud System as a continuum environment ASE Summer 2015 33 Enable a continuum execution environment across IoT and clouds Utilize similar techniques to deal with composition, provisioning, deployment, control, etc
- 34. IOT CLOUD ENGINEERING PRINCIPLES Hong-Linh Truong, Schahram Dustdar, Principles for Engineering IoT Cloud Systems, Cloud Magazine, 2015 (To appear) ASE Summer 2015 34
- 35. Engineering perspectives ASE Summer 2015 35 End-to-end Engineering and Optimization Development and Production Symbiosis Elasticity Coherence
- 36. 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 ASE Summer 2015 36
- 37. 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 ASE Summer 2015 37
- 38. 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 ASE Summer 2015 38
- 39. Development Tools and Actions ASE Summer 2015 39 Hong Linh Truong, Georgiana Copil, Schahram Dustdar, Duc-Hung Le, Daniel Moldovan, Stefan Nastic : On Architecting and Developing Elastic IoT Cloud Platforms -- The iCOMOT Approach, Working paper, 2015 Hong Linh Truong, Georgiana Copil, Schahram Dustdar, Duc-Hung Le, Daniel Moldovan, Stefan Nastic : On Architecting and Developing Elastic IoT Cloud Platforms -- The iCOMOT Approach, Working paper, 2015
- 40. iCOMOT – IoT Cloud Monitoring, Control and Testing ASE Summer 2015 40 Check: http://tuwiendsg.github.io/iCOMOT/
- 41. Exercises Read papers mentioned in slides Check services mentioned in examples Use iCOMOT to design your IoT Cloud System ASE Summer 2015 41
- 42. 42 Thanks for your attention Hong-Linh Truong Distributed Systems Group Vienna University of Technology truong@dsg.tuwien.ac.at http://dsg.tuwien.ac.at/staff/truong ASE Summer 2015