Internet of Things Scalability

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  1. 1. Internet of Things Scalability: Analyzing the Bottlenecks and Proposing Alternatives Mrcio Miguel Gomes Rodrigo da Rosa Righi Cristiano Andr da Costa Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos - Unisinos Brazil Corresponding address: cac@unisinos.br
  2. 2. 2 Agenda Introduction Theoretical basis Research question Related works Methodology and justification Proposed model Proposed algorithms Conclusion and Future Works
  3. 3. 3 Introduction Internet of Things - IoT Objects, animals or people equipped with unique identifiers Ability to automatically transfer data over a network Without the need for human intervention
  4. 4. 4 Application of IoT on health area Internet Healthcareserver Caregiveror physician Emergencyservicesor Medicalresearcher Database ))) ))) ))) Information Assessment,assistance,treatment Inertialsensor Pulseand blood pressure sensor Oximetry Sensor Source: adaptated from Jiang et al (2008)
  5. 5. 5 Perspectives Study by IDC (International Data Corporation) - 2013 Digital universe is doubling in size every two years (4.4 trillion gigabytes in 2013) Might be multiplied by 10 to 2020 (44 trillion gigabytes in just 7 years) BRICs with the largest volume of data in 2020 30 billion devices connected to the Internet in 2020
  6. 6. 6 Typical architecture of an RFID system Usersand Applications DataStorage RFIDMiddlewares and LocalApplications RFIDReaders Antennas RFIDTags
  7. 7. 7 Theoretical Basis RFID Middleware Mediation of communication between business systems and RFID hardware infrastructure Collecting, filtering, aggregation, storage and availability of data in a standardized way Source: Al Jaroodi, Aziz and Mohamed (2009) ServiceManagement DataManagement DeviceManagement Typical structure of RFID Middlewares
  8. 8. 8 Theoretical Basis EPCglobal Architecture Framework Set of interrelated standards for hardware, software and data interfaces LLRP Low Level Reader Protocol ALE Application Level Events EPCIS Electronic Product Code Information Services Source: http://www.gs1.org/gsmp/kc/epcglobal
  9. 9. 9 Research Question How would be a computer architecture and algorithms for managing scalability of an Internet of Things EPCglobal middleware, in order to guarantee the performance from the dynamic demand of applications and RFID sensors?
  10. 10. 10 Related Work Study of RFID middlewares Listing the most important features, applications, and used technologies for identifying how they manage load balancing and scalability Middleware MARM Fosstrak WinRFID Hybrid RF2ID LIT REFiLL Scalability Multi-agents system Dedicated server, simulation mode and embedded in RFID reader Distributed modules Peer-to- peer multi- ring network Virtual paths between virtual and physical readers Readers management interface Light programmable framework Load Balance Not addressed Readers subscription Not addressed Peer-to- peer systems Path management State-based execution model Not addressed EPCglobal No Yes No No No Yes Yes Comparison between RFID middlewares
  11. 11. 11 Choosing the RFID middleware EPCglobal compliant Application for general use Availability of access to the source code Possibility of modular deployment, in a distributed way Chosen middleware: Fosstrak
  12. 12. 12 Methodology and Justification MIB: Micro Benchmark for Evaluating Internet of Things Middlewares Source: Developed by the author
  13. 13. 13 Methodology and Justification Is there any situation of system failure? What is the relation between the applied load and resource consumption? What is the system behavior when it reaches CPU usage, network or memory limits? Is it possible to identify overload or underutilization thresholds with this assessment methodology?
  14. 14. 14 Methodology and Justification Applying MIB in Fosstrak: this work focus in the current model and in the future in the proposed model RFID data load: 4 readers with 0, 1 or 4 active tags, resulting in 0, 4 or 16 data per cycle Parallel queries load: 1 to 512 threads (20 to 29 requests) Serial queries load: 1 to 16 queries (20 to 24 requests)
  15. 15. 15 Methodology and Justification ALE module average behavior Current model
  16. 16. 16 Methodology and Justification EPCIS module average behavior Current model
  17. 17. 17 Proposed Model Current model Proposed model Nuvem UserApplications App1 App2 Appn ALEmulticoremultithread RFIDReader1 RFIDReader2 RFIDReadern NoSQLP2P Database EPCISinacloud CaptureInterface(HTTP) oooVM VM QueryInterface(SOAP) oooVM VM CapturingApplications App1 App2 Appn
  18. 18. 18 Proposed Model Parallel processing for the ALE Module (multithreaded and multicore) Split EPCIS module to meet different demands (reading and writing operations) Scalability and elasticity of EPCIS module (scalability manager and virtual machines and templates) High availability and fault tolerance for the database (NoSQL P2P)
  19. 19. 19 Proposed Algorithms
  20. 20. 20 Proposed Algorithms
  21. 21. 21 Conclusion and Future Works Fosstrak presented a good scalability, although the results demonstrated that a higher load can present some performance issues. Opens the possibility of using multiple servers Future works include the implementation of the proposed algorithms and further evaluation using MIB methodology
  22. 22. Internet of Things Scalability: Analyzing the Bottlenecks and Proposing Alternatives Mrcio Miguel Gomes Rodrigo da Rosa Righi Cristiano Andr da Costa Applied Computing Graduate Program Universidade do Vale do Rio dos Sinos - Unisinos Brazil Corresponding address: cac@unisinos.br