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Semantic Web Based Architecture for Managing Hardware Heterogeneity in Wireless Sensor Network

UNIVERSITY OF NOVI SAD FACULTY OF TEHNICAL SCIENCES SERBIA. Semantic Web Based Architecture for Managing Hardware Heterogeneity in Wireless Sensor Network. Authors : Sinisa Nikolić , MSc Valentin Penca , MSc Milan Segedinac , MSc Prof. Zora Konjović , PhD. Outline. Introduction

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Semantic Web Based Architecture for Managing Hardware Heterogeneity in Wireless Sensor Network

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  1. UNIVERSITY OF NOVI SAD FACULTY OF TEHNICAL SCIENCES SERBIA Semantic Web Based Architecture for Managing Hardware Heterogeneity in Wireless Sensor Network Authors: Sinisa Nikolić, MSc Valentin Penca, MSc Milan Segedinac, MSc Prof. Zora Konjović, PhD

  2. Outline Introduction Existing solutions GLOSENT architecture Case study Conclusion of 20

  3. Introduction WSN – a lot of sensor nodes(SN) SN – small size, low cost, battery-powered, processing, sensing, wireless communication WSN is not an isolated entity SWSN (System of WSNs) – user applications interact with heterogeneous WSNs of 20

  4. Introduction (2) Heterogeneity of WSN appears both in hardware and software Ontology based-model for solving hardware heterogeneity in SWSN Specific middleware that provides communication based on exchange of ontologies of 20

  5. Existing solutions Table 1 – Existing middlewares Specific based and generic (middleware) based of 20

  6. Existing solutions SOA Multi layer architecture of WSN, services for gathering data, xml description of hardware OX-Framework – using OGC standards (describe types and usage of WSN entities), without sematic description and technologies of 20

  7. Existing solutions Semantic Raw sensor data to reconstruct the context of event, hieratical organization semantic information and semantic services Ontologies for providing adaptive WSN Contextual ontologies to provide more flexible information processing of 20

  8. GLOSENT Architecture • GLObalSENsorneTwork • deals with hardware heterogeneity using semantic technologies of 20

  9. GLOSENT Architecture Figure 1 – The GLOSENT architecture of 20

  10. Application segment Figure 2 – Application segment Consist of Application proxy and Subapplications Subapplication – user application that uses appropriate communication methods and data formats Application proxy – bridge between sub placation and other parts of system of 20

  11. WSN segment Figure 3 – WSN segment Role of this segment is in gathering information and data representation from the sensor node network WSN modeled with metadata that describe: structure, method of use and control and data formats SN is a generalized notion related to any WSN device (base stations, rich uncles, routers, etc.) Uniform WSN representation relaying on ontology of 20

  12. Middleware segment Mediates in the communication of WSN segment and application segment in a SWSN Middleware is not physical part of system, it is consisted from data (ontologies) of all mentioned proxies of 20

  13. System Image Solving hardware heterogeneity in WSN consists of metadata models describing different WSN hardware platforms, metadata values describing particular devices and their relations, and sensor data (raw and/or aggregated sensor readings) current state of all WSN, represented with ontologies of 20

  14. System Image Figure 4 – WSN ontology of 20

  15. Central storage Figure 5 – Central storage • Implements the data persistency • Stores the System image data and the information about Subapplications of 20

  16. Case study: Modeling SN in GLOSENT Model of the WSN hardware platform SunSPOT SunSPOT is a WSN sensor node developed by Sun Microsystems. The device was developed based on IEEE 802.15.4 standard. SunSPOT can be used to measure light, temperature and acceleration, but its functionality can be extended with additional sensors of 20

  17. Classification of SunSPOT hardware components • Some basic functionalities of SunSPOT device • Extensible classification Figure 6 – Classification of components of 20

  18. Cental storage based on SunSPOT • contains the metadata that describe specific properties of SN • general properties of each hardware platform Table 1 – TypeSN Table 2 – TypeSNProperties of 20

  19. Conclusion We have proposed an ontologically-based approach for modeling SWSNs The topology of the WSN is represented by high-level ontology, while the semantics of WSN is represented by appropriate classifications The GLOSENT architecture successfully solves the problem of WSN hardware heterogeneity of 20

  20. Future work Dealing with other aspects of heterogeneity Using ontologies for representing Service Comand pattern based on ontologies Context-sensitive ontologies of 20

  21. Thank you for attention! Questions?

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