resource abstraction & virtualization
DESCRIPTION
Mobile Crowdsensing , Social and Big Data as Innovation Enablers for Future Internet Cloud-based Architectures and Services. Resource Abstraction & Virtualization. S. Kafetzoglou , C. Papagianni [email protected] Network Management & Optimal Design Laboratory - PowerPoint PPT PresentationTRANSCRIPT
S. Kafetzoglou, C. [email protected] Management & Optimal Design LaboratoryNational Technical University of Athens
Mobile Crowdsensing, Social and Big Data as Innovation Enablers for Future Internet Cloud-based Architectures and Services
Athens - March 18, 2014
Resource Abstraction & Virtualization
Virtualization technologies:• mechanisms for decoupling hardware and software resources
from their physical implementation.
Key point to resource virtualization: • introduction of an indirection layer below the execution
environment seen by applications and operating systems.
Virtualization is mainly applied and refers to network, storage and computing resources
Resource Virtualization
Advent of IoT conceptThe IoT vision: allow connectivity of anything from anywhere at anytime
Sensors and actuators play a vital role in this new digital ecosystem
Apply virtualization and abstraction techniques to sensing resources
new powerful applicationsImage source: http://www.nconnect.com
The need
Traditional sensors & WSNs
• Application specific, no reusability• Limited capabilities, • Heterogeneity in hardware, OS,
communication protocols.
Challenge• Allow heterogeneous sensors co-exist• Clean separation of services and infrastructure• Trading of sensor resources among several
service providers• Build innovative, cost-effective applications and
technical solutions
Solution• Abstraction and virtualization of sensing resources
The method
Virtual Sensor• Software sensor as opposed to a physical sensor.• Can be either an abstracted sensor in an overlay network, a WSN,
or an aggregated measurement of a group of heterogeneous physical sensors.
VSNs• Collaborative form of WSNs• Subset of sensor nodes of WSNs• Dedicated to a certain task• Can be easily reconfigured and re-purposed
Emerge of Virtual Sensor Nodes & Virtual Sensor Networks.
Introduction of Virtualization / Abstraction layer
Virtual Sensor NetworksSubset of sensor nodes of WSNs for specific applicationsSeveral challenges arise Isolation Manageability Scalability
Relevant Projects
VSNs VITRO FRESnel
Sensor Virtualization
Most common solution: introduction of a virtualization layer Provides abstraction for the programmers Mate VM one of the first virtualization approaches
sensor
Difficulties to integrate sensors due to heterogeneity issues
Sensor Data Modeling
• Sensor Model Language (SensorML)• Observations & Measurements (O&M)• Sensor Observations Service (SOS)
OGC Sensor Web Enablement framework (SWE)
• Ontology for sensor and sensor data (CSIRO)• Annotation framework for semantic metadata to
SWE framework
W3C Semantic Sensor Incubator Group
• SUMO• OntoSensor• LENS
Significant Research Work
Participatory Sensing
Resource rich
Support advanced
apps
Equipped with sensors
Communicate with external
sensors
Participatory sensing: deployed mobile devices form interactive, participatory sensor networks for enabling users to gather, analyze and share local knowledge
Applications: public health, urban planning, public transportation
Image source: http://complexitys.com/
Mobile Crowdsensing
Participatory sensing
Opportunistic sensing
Mobile Crowdsensing
Applications Environmental (eg. Common Sense) Infrastructure (eg. MIT’s CarTel) Social (eg. BikeNet and DietSense)
Image source: http://www.vimeo.com Participatory Sensing and Crowd Management in Public Spaces 2011 Lord Mayor's Show
References1. M.M. Islam, M. M. Hassan, G.W. Lee, & E.N. Huh, “A survey on virtualization of wireless sensor
networks”. Sensors, 12(2), 2175-2207.2. M. Iqbal, D. Yang, T. Obaid, T. J. Ng, H. B. Lim, "A Service-Oriented Application Programming
Interface for Sensor Network Virtualization", in Proc. of 10th International Conference on Information Processing in Sensor Networks, Chicago, USA, April 2011.
3. A. P. Jayasumana, H. Qi and T. H. Illangasekare, "Virtual sensor networks - A resource efficient approach for concurrent applications," in 4th International Conference on Information Technology-New Generations, ITNG 2007, 2007, pp. 111-115.
4. S. Alam, M. M. R. Chowdhury, and J. Noll, "SenaaS:An Event-driven Sensor Virtualization Approach for Internet of Things Cloud", in Proc. of the 1st IEEE International Conference on Networked Embedded Systems for Enterprise Applications, Suzhou, China, November 2010.
5. M. Navarro, M. Antonucci, L. Sarakis, and T. Zahariadis, "VITRO architecture: Bringing Virtualization to WSN world", in Proc. of the 8th IEEE International Conference on Mobile Ad-Hoc and Sensor Systems, Valencia, Spain, October 2011
6. C. Reed, M. Botts, J. Davidson, G. Percivall, “OGC® Sensor Web Enablement: Overview and High Level Architecture”, IEEE Autotestcon, pp. 372-380, 2007.
7. H. Neuhaus, and M. Compton, “The Semantic Sensor Network Ontology: A Generic Language to Describe Sensor Assets”, AGILE Workshop Challenges in Geospatial Data Harmonisation, 2009.
8. M. Eid, R. Liscano, A. El-Saddik, “A Universal Ontology for Sensor Networks Data”, IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, pp. 59–62, 2007.
9. C. Goodwin, and D. J. Russomanno, “An ontology-based sensor network prototype environment”, 5th International Conference on Information Processing in Sensor Networks, 2006.
10. X. Ju, H. Zhang, W. Zeng, M. Sridharan, J. Li, A. Arora, R. Ramnath, and Y. Xin, "LENS: Resource Specification for Wireless Sensor Network Experimentation Infrastructures", in Proc. of the 6th ACM International Workshop on Wireless network testbeds, experimental evaluation and characterization, Las Vegas, USA, September 2011.
11. S. Papavassiliou, C. Papagianni, S. Distefano, G. Merlino and A. Puliafito, "M2M Interactions Paradigm Via Volunteer Computing And Mobile Crowdsensing", in "Machine-To-Machine Communications - Architectures, Technology, Standards, and Applications" book, Taylor and Francis, edited by V. Misic and J. Misic, Ch. 11, March 2014.
12. N. Mitton, S. Papavassiliou, A. Puliafito and K.S. Trivedi, "Combining Cloud and sensors in a smart city environment", in EURASIP Journal on Wireless Communications and Networking Vol. 2012, (doi: 10.1186/1687-1499-2012-247), 2012.
13. A. Puliafito, N. Mitton, S. Papavassiliou, K.S. Trivedi: Editorial: Special Issue on Internet of Things: Convergence of Sensing, Networking, and Web Technologies. EURASIP J. Wireless Comm. and Networking 2012: 212 (2012)
Thank you