# Fuzzy-Logic Dijkstra-Based Energy-Efficient Algorithm for Data Transmission in WSNs
## 2 Related Work  
Several energy-efficient and energy-balanced routing protocols are developed in the literature with the objective of extending the network lifetime of sensor networks and improving the overall system performance. In Ref. [10], low-energy adaptive clustering hierarchy (LEACH), which is the most popular and self-organizing adaptive clustering routing algorithms for WSNs in the early times is proposed. It has the ability to increase the robustness and scalability of dynamic networks to a certain degree. The scheme proposes the generation of a random number between 0 and 1 that helps in electing the CH if the random number is less than a threshold value \(T(n)\), which is defined in Equation (1). \[T(n)=\left\{ \begin{array}{c}\frac{p}{1-p\left[r\ mod(1/p)\right]},n\ \in G\\ 0,others\end{array} \right. \tag{1}\]  
where \(p\) is the probability of the node to be selected as the CH during the election phase, \(r\) indicates the current election round, and \(G\) denotes the set of nodes that were not selected as CHs in the previous rounds. Each node has equal probability to become the CH. Once the CH is elected, each cluster member is provided a time slot to transmit the data to the CH in a time division multiple access (TDMA) manner. Although LEACH does not entirely take the communication energy consumption into account, and the random selection of the CH causes various deficiencies, it provides a good theoretical basis and design model for subsequent clustering techniques. A hybrid and energy-efficient distributed (HEED) clustering approach is presented in Ref. [15]. It initializes the CH selection phase by setting two parameters: primary and secondary. The primary parameter considers the residual energy of nodes and selects the node with highest residual energy as CH, whereas the secondary parameter reflects the nodes' density to compute the communication cost within the cluster. In HEED, the cluster formation occurs in a distributed manner, and it maintains a good distribution for the CH nodes. Moreover, it helps in improving the network lifetime by reducing the communication energy consumption within the cluster. However, in the cluster formation phase, several messages are broadcasted to exchange the network information, which results in additional energy consumption by the systems. Cluster-based event-driven routing protocol (CERP), in which cluster formation takes place based on different events, is proposed in Ref. [16]. The algorithm considers the distance between the neighboring nodes as a link cost while calculating the shortest path from the source to the sink node. Clusters are formed on the basis of event occurrence; therefore, the routing scheme may encounter less energy intermediate nodes owing to their random deployment. This may lead to the network isolation problem in some areas. Furthermore, a Dijkstra-based weighted sum minimization (DWSM) algorithm is proposed in Ref. [17] for wireless mesh networks (WMNs). It introduces a multi-objective function as the link cost between the nodes, which is influenced by the network parameters such as end-to-end delay and path capacity. This scheme analyzes the impact of these two factors on the network performance by minimizing a weight metric sum through [PERSON]'s algorithm. In Ref. [18], hierarchical unequal clustering fuzzy algorithm (HUCFA) is introduced to reduce the energy consumption of the network. It divides the network area into three horizontal layers based on its distance to BS and then splits each layer into grids. Furthermore, it includes a fuzzy-logic-based CH selection scheme which enhances the energy efficiency. An energy saving routing algorithm based on Dijkstra (ESRAD) is proposed in Ref. [11] for WSNs. This scheme considers an evaluation index of the node by considering the energy consumption of information processing at the node and energy consumption due to the transmission between two connected nodes. This index is then used as a link cost through [PERSON]'s algorithm to search the path with the least energy consumption.