In consumer products market, supply chain management (SCM) is a complex and significant issue in the governance of organizations, people with their activities, technology, information and resources involved in transferring a product or service from a supplier to a final customer. To this aim, radio-frequency identification (RFID) is a promising wireless technology allowing to link an object with its “virtual counterpart”, i.e., its representation within information systems. In this context, a SCM system has to face a huge amount of RFID data, generated in the tracking of supply chain resources. In particular when RFID installations become larger and more physically distributed, efficient and scalable analysis of such data becomes a concern. Currently, state of the art approaches provide hard-coded solutions where the processing of RFID data occurs in a central location; as the amount and distribution of data grow, the workload requires significant consumption of resources, and quickly outpaces the capacity of a centralized processing server. In this paper, we consider the problem of distributing the RFID processing workload—possibly huge—proposing the physical design of a scalable and distributed system. Such system is built on top of a general framework for SCM, based on the first principles of linear algebra, in particular, on tensorial calculus. We consider challenges in instantiating such a system in large distributed settings, and design techniques for distributed real time query processing. Experimental results, using large traces, demonstrate the efficiency and scalability of our proposal with respect to competing approaches.

DE VIRGILIO, R., Milicchio, F. (2016). Physical design for distributed RFID-based supply chain management. DISTRIBUTED AND PARALLEL DATABASES, 34(1), 3-32 [10.1007/s10619-015-7178-x].

Physical design for distributed RFID-based supply chain management

DE VIRGILIO, ROBERTO;MILICCHIO, Franco
2016-01-01

Abstract

In consumer products market, supply chain management (SCM) is a complex and significant issue in the governance of organizations, people with their activities, technology, information and resources involved in transferring a product or service from a supplier to a final customer. To this aim, radio-frequency identification (RFID) is a promising wireless technology allowing to link an object with its “virtual counterpart”, i.e., its representation within information systems. In this context, a SCM system has to face a huge amount of RFID data, generated in the tracking of supply chain resources. In particular when RFID installations become larger and more physically distributed, efficient and scalable analysis of such data becomes a concern. Currently, state of the art approaches provide hard-coded solutions where the processing of RFID data occurs in a central location; as the amount and distribution of data grow, the workload requires significant consumption of resources, and quickly outpaces the capacity of a centralized processing server. In this paper, we consider the problem of distributing the RFID processing workload—possibly huge—proposing the physical design of a scalable and distributed system. Such system is built on top of a general framework for SCM, based on the first principles of linear algebra, in particular, on tensorial calculus. We consider challenges in instantiating such a system in large distributed settings, and design techniques for distributed real time query processing. Experimental results, using large traces, demonstrate the efficiency and scalability of our proposal with respect to competing approaches.
2016
DE VIRGILIO, R., Milicchio, F. (2016). Physical design for distributed RFID-based supply chain management. DISTRIBUTED AND PARALLEL DATABASES, 34(1), 3-32 [10.1007/s10619-015-7178-x].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/299322
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 5
social impact