Projects per year
Abstract
Long Range (LoRa) is a low-power wireless communication technology for long-range connectivity, extensively used in the Internet of Things. Several works in the literature have analytically characterized the performance of LoRa networks, with particular focus on scalability and reliability. However, most of the related models are limited, as they cannot account for factors that occur in practice, or make strong assumptions on how devices are deployed in the network. This article proposes an analytical model that describes the delivery ratio in a LoRa network with device-level granularity. Specifically, it considers the impact of several key factors that affect real deployments, including multiple gateways and channel variation. Therefore, the proposed model can effectively evaluate the delivery ratio in realistic network topologies, without any restrictions on device deployment or configuration. It also accurately characterizes the delivery ratio of each device in a network, as demonstrated by extensive simulations in a wide variety of conditions, including diverse networks in terms of node deployment and link-level parameter settings. The proposed model provides a level of detail that is not available in the state of the art, and it matches the simulation results within an error of a few percentage points.
Original language | English |
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Title of host publication | INFOCOM 2021 - IEEE Conference on Computer Communications |
Publisher | IEEE |
Number of pages | 10 |
ISBN (Electronic) | 978-0-7381-1281-7 |
DOIs | |
Publication status | Published - 10 May 2021 |
MoE publication type | A4 Conference publication |
Event | IEEE Conference on Computer Communications - Virtual Conference, Vancouver, Canada Duration: 10 May 2021 → 13 May 2021 Conference number: 39 |
Publication series
Name | Proceedings / IEEE INFOCOM |
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ISSN (Electronic) | 2641-9874 |
Conference
Conference | IEEE Conference on Computer Communications |
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Abbreviated title | INFOCOM |
Country/Territory | Canada |
City | Vancouver |
Period | 10/05/2021 → 13/05/2021 |
Fingerprint
Dive into the research topics of 'Modeling Communication Reliability in LoRa Networks with Device-level Accuracy'. Together they form a unique fingerprint.Projects
- 2 Finished
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Mission-Critical Internet of Things Applications over Fog Networks
Di Francesco, M. (Principal investigator), Premsankar, G. (Project Member), Ranjbaran, S. (Project Member), Jedari Ghourichaei, B. (Project Member), Montoya Freire, M. (Project Member), Corneo, L. (Project Member) & Kortoci, P. (Project Member)
01/01/2019 → 31/12/2021
Project: Academy of Finland: Other research funding
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Enabling a User-friendly and Dependable Internet of Things
Di Francesco, M. (Principal investigator), Bufalino, J. (Project Member), Palomäki, R. (Project Member), Premsankar, G. (Project Member), Ranjbaran, S. (Project Member), Montoya Freire, M. (Project Member), Toro Betancur, V. (Project Member) & Kortoci, P. (Project Member)
01/09/2016 → 31/08/2020
Project: Academy of Finland: Other research funding