$FREE$ —Fine-Grained Scheduling for Reliable and Energy-Efficient Data Collection in LoRaWAN

Abstract

LoRaWAN promises to provide wide-area network access to low-cost devices that can operate for up to 10 years on a single 1000mAh battery. This makes LoRaWAN particularly suited to data collection applications (e.g. monitoring applications), where device lifetime is a key performance metric. However, when supporting a large number of devices, LoRaWAN suffers from a scalability issue due to the high collision probability of its Aloha-based MAC layer. The performance worsens further when using acknowledged transmissions due to the duty cycle restriction at the gateway. For this, we propose FREE, a fine-grained scheduling scheme for reliable and energyefficient data collection in LoRaWAN. FREE takes advantage of applications that do not have hard delay requirements on data delivery by supporting synchronized bulk data transmission. This means data is buffered for transmission in scheduled time slots instead of transmitted straight away. FREE allocates spreading factors, transmission powers, frequency channels, time slots, and schedules slots in frames for LoRaWAN end-devices. As a result, FREE overcomes the scalability problem of LoRaWAN by eliminating collisions and grouping acknowledgments. We evaluate the performance of FREE versus different legacy LoRaWAN configurations. The numerical results show that FREE scales well and achieves almost 100% data delivery and the device lifetime is estimated to over 10 years independent of traffic type and network size. Comparing to poor scalability, low data delivery and device lifetime of fewer than 2 years for acknowledged data traffic in the standard LoRaWAN configurations.

Short: Achieving Energy Efficiency in Dense LoRaWANs through TDMA

“…The possibility to use offline scheduling has also been investigated in [9] to reach realtime constraints with duty-cyle requirements, and in [10] by splitting the beacon window onto sub-periods with and without contention. In [11] and [12], Zorbas et al explore the solutions in which data is stored within the nodes and then collected in bulk. Clock-based synchronization has also been studied in [13] and [14], which additionally features a full scheduling mechanism built on top of Class A.…”

A Survey on the Viability of Confirmed Traffic in a LoRaWAN

“…An alternative approach to data collection and acknowledgement is suggested and compared with standard LoRaWAN in [42]. A scheduling scheme called FREE is proposed which requires that nodes store data in bulk and collection takes place periodically.…”

“…During their evaluations, nodes generated 20 bytes every 5 minutes, could potentially retransmit a packet up to 8 times and simulations considered 1 day's worth of data. For a standard LoRaWAN using confirmed traffic, the device lifetime drops quickly below two years due to the cost of retransmissions and for a network of 1000 devices, the number of transmissions increased 7.4 times the level of a similar network using unconfirmed instead [42]. LoRaWAN's overall Data Delivery Ratio (DRR) plummets sharply falling below 50 % at ≈ 200 devices as the number of collisions rise sharply.…”

“…Accurate network models are key when determining the impact of downlink traffic on network performance, and modelling should include the PHY and MAC layers. Due to their Aloha like MAC configuration and the DC limits imposed by operating in ISM bands, LoRaWANs suffer from scalability issues [42]. They do, however, perform better than pure Aloha networks, in part due to the capture effect [43], [44] and SF pseudo-orthogonality [13], [45].…”

“…LoRaWAN simulators have been developed used from a variety of existing WSN platforms such as ns-3, OMNET++ and SimPy. Publicly available LoRaWAN simulators that support downlink traffic are LoRaSim [49], the expanded version of LoRaSim used in [42], the ns-3 modules presented in [50] and [48], LoRaEnergySim [51] and FLoRa [52].…”