Cost model for RFID-based traceability information systems

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  • 1. Cost model for RFID-basedTraceability Information Systems Miguel.Pardal@ .utl.pt Jose.Marques@ .pt September 16th, 2011
  • 2. Traceability• Where is my object? – Track• Where has it been? – Trace• What are its components? – Bill-of-materials
  • 3. Product recallFood, Medicines,... Emergency!
  • 4. HasData(M, x) HasData( D, x ) Directory 1. WhoHasData(x) 2.1 getEvents (x) 2.2 getEvents (x) Query Query QueryManufacturer M Distributor D Retailer R Repository Repository Repository Capture Capture Capture EPC x
  • 5. Estimating remote procedure call cost [Murthy and Robson, 2008] Transfer Send Receive Lookup Receive Send Transfer
  • 6. Decentralized Centralized unstructured P2P metadata integrationVirtual data integration GS1 PoC [3] Verisign DS [4] IBM PoC [5] ePedigree [1] Theseos [2] PTSP [6] EPCDS [7] ADS [8] Theseos has several distributed data stores. Queries are answered recursively. Each company can enforce data ownership. Afilias ESDS [9] BRIDGE Directory [10] BRIDGE Query Relay [11] BRIDGE Directory relies on centralized services to store data provider links. There are scalability and single point-of- failure issues to be considered. UniSalento DS SLS [12] [13] UniPR DS [14] IOTA [17] EPCIS caching [15] TraceSphere LoTR [18] [16]Materialized data integration UniKoeln DS [19] OIDA [20] ID @URI [23] OIDA relies on a Peer-to-Peer network with a ID@URI uses a product-agent architecture. hashing algorithm for data placement in nodes. It All data concerning the item is forwarded to a is fully decentralized and has potential for high central data store, managed by the product’s scalability. manufacturer. InnoSem [21] There are issues about response quality and timeliness. Query capabilities are limited to object ID matching. WWAI [22] structured P2P data integration
  • 7. Metadata integration:centralized, virtual data integration
  • 8. Data integration:centralized, materialized data integration
  • 9. Unstructured P2P:decentralized, virtual data integration
  • 10. Structured P2P:decentralized, materialized data integration
  • 11. Decentralized Centralized unstructured P2P metadata integrationVirtual data integration GS1 PoC [3] Verisign DS [4] IBM PoC [5] ePedigree [1] Theseos [2] PTSP [6] EPCDS [7] ADS [8] Theseos has several distributed data stores. Queries are answered recursively. Each company can enforce data ownership. Afilias ESDS [9] BRIDGE Directory [10] BRIDGE Query Relay [11] BRIDGE Directory relies on centralized services to store data provider links. There are scalability and single point-of- failure issues to be considered. UniSalento DS SLS [12] [13] UniPR DS [14] IOTA [17] EPCIS caching [15] TraceSphere LoTR [18] [16]Materialized data integration UniKoeln DS [19] OIDA [20] ID @URI [23] OIDA relies on a Peer-to-Peer network with a ID@URI uses a product-agent architecture. hashing algorithm for data placement in nodes. It All data concerning the item is forwarded to a is fully decentralized and has potential for high central data store, managed by the product’s scalability. manufacturer. InnoSem [21] There are issues about response quality and timeliness. Query capabilities are limited to object ID matching. WWAI [22] structured P2P data integration
  • 12. Chain parameters Number of companies Application parameters Average item records Message size Average length Item record sizeSystem parameters Bandwidth Product parameters Processing speed Average sub -components Seek time Average component depth Traceability cost model Report
  • 13. Auto supply chainShort and broad chain – 700 companies, 6 levels deep, 3 components per level
  • 14. Conclusion• Developed a cost model to quantitatively compare traceability systems• Future work – More detail – Address scale and security concerns – Validate model using actual systems
  • 15. Towards the Internet of Things... Sybase.pt Thank you! miguel.pardal@ist.utl.pt
  • 16. Bibliography• [Do06] – Hong-Hai Do and Jurgen Anke and Gregor Hackenbroich, Architecture Evaluation for Distributed Auto-ID Systems, Proc. 17th International Workshop on Database and Expert Systems Applications (DEXA), 2006• [Evdokimov10] – Sergei Evdokimov and Benjamin Fabian and Steffen Kunz and Nina Schoenemann, Comparison of Discovery Service Architectures for the Internet of Things, IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (SUTC), 2010• [MurthyRobson08] – Karin Murthy and Christine Robson, A model-based comparative study of traceability systems, Proceedings of the International Conference on Information Systems, Logistics and Supply Chain (ILS), 2008