Burst-MAC: A MAC Protocol for Handling Burst Traffic in LoRa Network

While LoRa networks typically handle very infrequent communications, they can occasionally encounter sudden data bursts in response to unpredictable events such as a forest fire or volcanic eruption. LoRaWAN, the MAC protocol for LoRa, lacks a collision avoidance mechanism due to the severe energy constraints of the nodes. Burst traffic can result in substantial collisions, retransmissions, and packet loss when dealing with burst traffic, leading to rapid depletion of node batteries, increased network latencies, and significantly degraded throughput. In this paper, we propose Burst-MAC, a low-overhead MAC protocol for LoRa networks to efficiently handle burst traffic. When the network traffic is light and infrequent, Burst-MAC operates just like LoRaWAN. Upon detecting a data burst, it switches to burst mode that functions as follows: (i) nodes with bursty data are organized into virtual groups based on channel and spreading factor, and (ii) nodes within each group transmit in a semi-distributed TDMA fashion with each node determining its transmission time slots using a hash function to eliminate the need for centralized schedule distribution. Hash function collisions are resolved through piggybacking with acknowledgements from the gateway, ensuring bounded latencies for transmitted packets. We evaluate Burst-MAC through both physical experiments on LoRa devices and NS-3 simulations under various burst scenarios. Our results demonstrate that Burst-MAC significantly outperforms LoRaWAN and other baselines in several aspects, including a $4.5 \times$ improvement in packet reception rate, up to $6 \times$ reduction in energy consumption, and up to $2.5 \times$ decrease in latency.

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Publication Details

Published
2024-12-10
DOI
https://doi.org/10.1109/rtss62706.2024.00022
Citations
5
Primary Topic
IoT Networks and Protocols
Type
article
Field-Weighted Citation Impact
1.04
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article

Burst-MAC: A MAC Protocol for Handling Burst Traffic in LoRa Network

Abusayeed Saifullah, Md Ashikul Haque, Haibo Zhang, Aakriti Jain
5 citations
IoT Networks and Protocols
1.04
article

Burst-MAC: A MAC Protocol for Handling Burst Traffic in LoRa Network

Abusayeed Saifullah, Md Ashikul Haque, Haibo Zhang, Aakriti Jain
article en
5 citations

Abstract

While LoRa networks typically handle very infrequent communications, they can occasionally encounter sudden data bursts in response to unpredictable events such as a forest fire or volcanic eruption. LoRaWAN, the MAC protocol for LoRa, lacks a collision avoidance mechanism due to the severe energy constraints of the nodes. Burst traffic can result in substantial collisions, retransmissions, and packet loss when dealing with burst traffic, leading to rapid depletion of node batteries, increased network latencies, and significantly degraded throughput. In this paper, we propose Burst-MAC, a low-overhead MAC protocol for LoRa networks to efficiently handle burst traffic. When the network traffic is light and infrequent, Burst-MAC operates just like LoRaWAN. Upon detecting a data burst, it switches to burst mode that functions as follows: (i) nodes with bursty data are organized into virtual groups based on channel and spreading factor, and (ii) nodes within each group transmit in a semi-distributed TDMA fashion with each node determining its transmission time slots using a hash function to eliminate the need for centralized schedule distribution. Hash function collisions are resolved through piggybacking with acknowledgements from the gateway, ensuring bounded latencies for transmitted packets. We evaluate Burst-MAC through both physical experiments on LoRa devices and NS-3 simulations under various burst scenarios. Our results demonstrate that Burst-MAC significantly outperforms LoRaWAN and other baselines in several aspects, including a $4.5 \times$ improvement in packet reception rate, up to $6 \times$ reduction in energy consumption, and up to $2.5 \times$ decrease in latency.

Wayne State University (US), University of Otago (NZ)
Openalex Percentile: Top 22%
IoT Networks and Protocols
1.04
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