3.8 Proceedings Paper

Towards Energy-Fairness in LoRa Networks

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/ICDCS.2019.00083

Keywords

The Internet of Things; wireless networking; LoRa networks; energy fairness; resource allocation

Funding

  1. National Key Research and Development Program of China [2017YF-B1400102]
  2. National Natural Science Foundation of China [61602095]
  3. National Postdoctoral Foundation for Innovative Talents [BX201700046]
  4. EU FP7 CLIMBER project [PIRSES-GA-2013-612652]
  5. China Scholarship Council

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LoRa has recently become one of the most promising networking technologies for the Internet of Things applications. Distant end devices have to use a low data rate to reach a LoRa gateway, which can cause long in-the-air transmission time and high energy consumption. Compared with the end devices using high data rate, they will drain the batteries much earlier and the network may be broken. Such an energy unfairness can be mitigated by deploying more gateways, since it allows end devices to reach closer gateways with higher data rates. However, multiple gateways may not solve the energy unfairness problem efficiently due to the collision problem caused by the chirp spread spectrum modulation of LoRa networks. Spreading factors of LoRa links can determine both data rate and multiplexing of different transmissions. With more gateways, more end devices may choose low spreading factors and reach closer gateways, which increase the collision probability. In this paper, we propose a networking solution for LoRa networks named EF-LoRa that can achieve fair energy consumption among end devices by carefully allocating different network resources, including frequency channels, spreading factors and transmission power, to achieve fair energy consumption among end devices in LoRa networks. We develop a LoRa network model to study the energy consumption of all the end devices in a network by considering the unique features of LoRa networks, such as LoRaWAN MAC protocol, spreading factors, interference, and the capacity limitation of a LoRa gateway. We formulate the energy fairness problem as an optimization problem and finally propose a greedy resource allocation algorithm to achieve the max-min fairness of energy efficiency in the LoRa networks. Simulation results show that the proposed solution EF-LoRa can improve the energy fairness of legacy LoRa networks by 177.8%.

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