Data Gathering Solutions for Dense RFID Deployments - Inria - Institut national de recherche en sciences et technologies du numérique
Communication Dans Un Congrès Année : 2017

Data Gathering Solutions for Dense RFID Deployments

Résumé

The advent of RFID (Radio Frequency Identification) has allowed the development of numerous applications. Indeed, solutions such as tracking of goods in large areas or sensing in smart cities are now made possible. However, such solutions encounter two main issues, first is inherent to the technology itself which is readers collisions, the second one being the gathering of read data up to a base station, potentially in a multihop fashion. While the first one has been a main research subject in the late years, the next one has not been investigated for the sole purpose of RFID, but rather for wireless adhoc networks. This multihop tag information collection must be done in regards of the application requirements but it should also care for the deployment strategy of readers to take advantage of their relative positions, coverage, reading activity and deployment density to avoid interfering between tag reading and data forwarding. To the best of our knowledge, the issue for a joint scheduling between tag reading and forwarding has never been investigated so far in the literature, although important. In this paper, we propose two new distributed, crosslayer solutions meant for the reduction of collisions and better efficiency of the RFID system but also serve as a routing solution towards a base station. Simulations show high levels of throughput while not lowering on the fairness on medium access staying above 85% in the highest deployment density with up to 500 readers, also providing a 90% data rate.
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Dates et versions

hal-01521113 , version 1 (24-07-2017)

Identifiants

  • HAL Id : hal-01521113 , version 1

Citer

Abdoul Aziz Mbacké, Nathalie Mitton, Hervé Rivano. Data Gathering Solutions for Dense RFID Deployments. UIC 2017 - 14th International Conference on Ubiquitous Intelligence and Computing, Aug 2017, San Francisco, United States. ⟨hal-01521113⟩
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