LoRaWAN for Smart Campus: Deployment and Long-Term Operation Analysis
Abstract
:1. Introduction
2. LoRaWAN Technology at a Glance
2.1. The Physical Layer
2.2. The Network Components and Medium Access Control Layer
3. Smart Campus Monitoring Planning and Deployment
3.1. The Methodology of Deployment
3.2. Initial Planning
3.3. Predeployment Network Analysis
- Each packet has constant length since every node has sensors measuring five parameters and data payload size are fixed for each sensor [58]; therefore, all the nodes require a fixed number of bytes to convey their measurements to the network server (NS).
- No interference from external third party networks is present. This was validated through the experimental measurements before the experiments by the measurements carried near to the desired gateway position.
- No acknowledgments, adaptive data rate, or regular downlink transmissions are present, since these are neither obligatory nor required for our application, thus implying “best-effort” delivery on the one hand, and may compromise the uplink delivery probability due to half-duplex architecture of the gateway [59].
- The start-up time for each node is random, as no specific procedure for powering them up or connecting them to the network is implied.
3.4. Deployed Network Elements and Configuration
4. Network Performance Evaluation
4.1. Network Performance from October 2017 to October 2019
4.1.1. Short- and Long-Term Temporal Fluctuations of Performance
4.1.2. Frequency Bands and Radio Channel
4.2. Network Today
5. Discussion and Conclusions
- It is conventionally implied that the wireless channel is the only place where the packets may get lost in an LPWAN. However, our results showed that packet losses in the IP-based backbone network (in our case composed of the pan-university local area network, the third-party commercial MQTT broker, and IoT server) also happen. Moreover, these can cause that no packets are delivered for periods of a few minutes to a few hours. This fact calls for the development of efficient solutions for detecting and managing such situations (e.g., through periodic heartbeat messages or use of packet buffering).
- Another conventional implication relative to LoRaWAN networks is that collisions primarily cause packet losses in a wireless channel. After extensive analysis of the data for over an 18-month period, we identified that the primary reason for packet losses in our network was interference from an external system, which has been affecting one of the default LoRaWAN frequency channels. Unfortunately, we were not able to track this external system since it has stopped its operation. However, our results may be significant for the other practitioners, allowing them to speed the diagnosis of their networks. This observation also calls for investigating and developing the novel solutions to detect and mitigate the interferences affecting the LoRaWAN networks.
- Next, in the data collected within our networks, we witnessed several interesting temporal effects. The most notable of these is the nonuniform distribution of the transmissions from the sensors within a single report period. In our opinion, this effect and the potential reason for it need to be explored in more detail, and this will be one of the directions for our further studies.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Data Rate (DR) | Configuration Setup | Bit Rate (kb/s) 1 | Sensitivity (dBm) 1 |
---|---|---|---|
DR0 | LoRa: SF12, 125 kHz | 0.25 | −137 |
DR1 | LoRa: SF11, 125 kHz | 0.44 | −134.5 |
DR2 | LoRa: SF10, 125 kHz | 0.98 | −132 |
DR3 | LoRa: SF9, 125 kHz | 1.760 | −129 |
DR4 | LoRa: SF8, 125 kHz | 3.125 | −126 |
DR5 | LoRa: SF7, 125 kHz | 5.470 | −123 |
DR6 | LoRa: SF7, 250 kHz | 11.00 | −122 |
DR7 | FSK: 150 kHz | 50.00 | −122 |
Configuration Setup 1 | Bit Rate (kb/s) 1 | Duty Cycle Restriction [30] | Time-on-Air (ms) [40] | Back-off Time, s |
---|---|---|---|---|
SF12, 125 kHz | 0.25 | 1% | 1482.75 | 146.79 |
SF11, 125 kHz | 0.44 | 1% | 823.30 | 81.51 |
SF10, 125 kHz | 0.98 | 1% | 370.69 | 36.70 |
SF9, 125 kHz | 1.760 | 1% | 205.82 | 20.38 |
SF8, 125 kHz | 3.125 | 1% | 113.15 | 11.20 |
SF7, 125 kHz | 5.470 | 1% | 61.70 | 6.11 |
SF7, 250 kHz | 11.00 | 1% | 30.85 | 3.05 |
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Yasmin, R.; Mikhaylov, K.; Pouttu, A. LoRaWAN for Smart Campus: Deployment and Long-Term Operation Analysis. Sensors 2020, 20, 6721. https://doi.org/10.3390/s20236721
Yasmin R, Mikhaylov K, Pouttu A. LoRaWAN for Smart Campus: Deployment and Long-Term Operation Analysis. Sensors. 2020; 20(23):6721. https://doi.org/10.3390/s20236721
Chicago/Turabian StyleYasmin, Rumana, Konstantin Mikhaylov, and Ari Pouttu. 2020. "LoRaWAN for Smart Campus: Deployment and Long-Term Operation Analysis" Sensors 20, no. 23: 6721. https://doi.org/10.3390/s20236721
APA StyleYasmin, R., Mikhaylov, K., & Pouttu, A. (2020). LoRaWAN for Smart Campus: Deployment and Long-Term Operation Analysis. Sensors, 20(23), 6721. https://doi.org/10.3390/s20236721