# Energy-Efficient LoRa Routing for Smart Grids
## 2 Literature Review
Reference [45] presented an energy-efficient multi-hop LEACH (EEM-LEACH) protocol, which allows sensor nodes to send the data directly to the BS if the distance between the sensor nodes is less than that of the CHs. The EEM-LEACH protocol can be applied efficiently in small areas. However, if the source and destination nodes are far apart, the data are transmitted with the help of intermediate devices, and for this purpose, the lightweight on-demand ad hoc distance vector routing (LOADng) protocol was proposed, which works efficiently in a low-power noisy environment. The LOADng algorithm has a reactive functionality, which builds a path between the nodes only when the data packets need to be exchanged. As a result, a source (SRC) node that wishes to send a data packet must initiate a route discovery process to locate and build a path to the destination (DEST) node. However, this algorithm is affected by route construction delays and difficulties caused by inefficient flooding, which consumes much energy, with much overhead and many packet collisions [46]. Based on LOADng's restrictions in MP2P settings [47], a collection tree extension for the protocol has been proposed. This proposal, known as LOADng-CTP, adds proactive capabilities to LOADng and assists nodes in creating a routing tree to send data packets from the source node to the destination node. The performance of LOADng-CTP and RPL was also evaluated in an AMI [48]. In addition, the performance of LOADng with various routing metrics was investigated in [49]. In this work, the Cum_LEACH protocol was used for CH selection, whereas the LOADng algorithm was used to transmit the data between the CH and the BS when the distance between them is large. There may be multiple paths existing between the CH and BS when the distance between them is very large. Therefore, this requires using an optimisation algorithm in conjunction with the LOADng algorithm, which is a path planning algorithm. Below are a few cases of optimisation techniques used along with LEACH to find the optimal path. Particle swarm optimisation (PSO) [50] optimises the LEACH protocol, most commonly used in WSN routing protocols. Here, it was used for optimal communication paths in the LEACH protocol. PSO defines the optimal CH location by optimising an objective function based on the node degree, headcount, residual energy, and intra-cluster distance of the possible CH [51]. Centralised-PSO [52] is a new clustering algorithm based on PSO developed for CH selection by formulating the CH selection problem as a single-objective optimisation problem. This objective function considers the residual energy of each sensor node when each CH is close to other sensor nodes. In the present work, African buffalo optimisation (ABO) [53] was used in association with the LOADng algorithm, called QKE-ABO, to find the optimal path to transmit the data between the CH and BS, and it was compared with other existing optimisation techniques such as the pelican optimisation algorithm (PAO) [54] and the ant lion optimisation method (ALO) [55] in terms of the convergence value for the optimal solution. To discover multiple routing paths in between the source node and the destination node, the routing path must be consistent, have high energy efficiency, and be the shortest to obtain the minimum transmission delay and energy consumption. In an SG communication network, an essential area to be covered is choosing the appropriate routing path. By utilising the SMAx algorithm, the optimal routing path is discovered and compared with the sparrow search algorithm (SSA) [56] and Mexican axololts optimisation (MAX) [57].