On the Efficacy of Particle Swarm Optimization for Gateway Placement in LoRaWAN Networks

The efficacy of the Particle Swarm Optimization (PSO) in determining the optimal locations for gateways in LoRaWAN networks is investigated. A modified PSO approach, which introduces gateway distancing measures during the initialization phase and flight time, is proposed. For the ease of comparisons and the understanding of the behavior of the algorithms under study, a square LoRaWAN area is used for simulations. Optimization results on a LoRaWAN script, implemented in NS-3, show that the modified PSO converges faster and achieves better results than the traditional PSO, as the number of gateways increases. Results further show that the modified PSO approach achieves similar performance to a deterministic approach, in which gateways are uniformly distributed in the network. This shows that for swarm intelligence techniques such as PSO to be used for gateway placement in LoRaWAN networks, gateway distancing mechanisms must be incorporated in the optimization process. These results further show that these techniques can be easily deployed in geometrically more complex LoRaWAN figures such as rectangular, triangular, circular and trapezoidal shapes. It is generally difficult to figure out a deterministic gateway placement mechanism for such shapes. As part of future work, more realistic LoRaWAN networks will be developed by using real geographical information of an area.

Distance Aware Gateway Placement Optimization for Machine-to-Machine (M2M) Communication in IoT Network

In the research field, network performance for different smart applications plays an important role in the IoT network. Several factors, such as packet delay, network throughput, energy consumption, heterogeneity, proper gateway placement and load balancing, have a greater impact on network performance. In this article, two factors, such as optimal gateway placement and energy consumption, are investigated in order to improve the performance of the IoT network. Various methods are used to find the lo-cation of the Coordinating Devices (CDs) and to place constraint gateways in such a way that all CDs within the network should be covered by at least one gateway in order to allow the dissemination of data within the net-work. All of these CDs in the wireless network send their data to their near-by gateway based on Euclidean distance optimization. Euclidean distance performance is better than linear data transmission. During data transmission, nodes are unable to transmit data due to obstacles encountered in the path to the destination which result in a minimal energy efficiency improvement. Our proposed system solves the issue of gateway location optimization based on different distance-based approaches called Euclidean Distance (ED) and Manhattan Distance (MD) used in the wireless network to achieve the objective of reducing energy consumption.

Gateway placement and traffic load simulation in sensor networks

Because of the wide variety of possible application fields and the spread of smart devices, the research of wireless sensor networks has become an increasingly important area in the last decade. During the design of these networks, several important aspects have to be considered, for example the lifetime of the network, expected battery usage, or robustness of the installed system. In this paper a simulation environment is introduced that enables the testing of different information spreading methods on the network and provides suggestions for gateway placements with different objectives.