Low energy adaptive clustering hierarchy (LEACH) is one of the basic cluster-based routing algorithms [13]. LEACH has four phases, namely network deployment phase, neighbor discovery phase, cluster formation and CH selection phase, and communication phase. For CH selection, a different criterion needs to be considered. The main aim of the LEACH algorithm is energy consumption. In LEACH, CH is selected based on residual energy, node density, distance to the sink, or the average distance between a node and its neighbor. A single criterion is used for CH selection in real time. Having a single criterion is not enough for the head node chosen because if the residual energy of a head node is high and the distance to the sink of that node is also high, then we cannot say that it is energy-efficient communication. The same goes for the other criteria. Therefore, to solve such problems, in this work, the multi-criteria decision-making (MCDM) technique was considered for CH selection in a remote SC environment. The MCDM technique has been designed to identify the desired alternatives and arrange alternatives in a small number of categories; the rank of the alternatives gives the preference order. In the MCDM technique, decision matrixes have four major parts, namely alternatives, attributes, weight, and performance concerning attributes. In an SCE, we identified different criteria for CH selection and used the MCDM technique to calculate the rank from different criteria, sub-criteria, and their alternatives. In this technique, a pairwise comparison matrix was created from the criteria with respect to different alternatives, and the weight of the matrix was calculated from the matrix. The fuzzy analytical hierarchy process (AHP), the fuzzy analytical network process (ANP), and the technique for order preference by similarity to the ideal solution (TOPSIS) are popular MCDM techniques [14]. Another problem that occurs in the traditional LEACH algorithm is that the CHs are changed in every round and the process is continued till the last nodes have died. In this process, the energy utilization is greater and network lifetime is less. Therefore, to solve this problem, we used the threshold value for CH selection and the MCDM technique to calculate the threshold value. The LEACH is a hierarchical architecture; therefore, to solve this problem, in this paper, we considered two MCDM [15] algorithms: the fuzzy analytical hierarchy process (FAHP) [16] and the fuzzy analytical network process (FANP) [17]. The FAHP MCDM is used to solve tree- or hierarchy-like structures, but if the criteria and sub-criteria are increased, then it looks like network- or mesh-type architecture. This problem was solved by using the FANP MCDM technique. In the LEACH algorithm, we went further and modified the last two phases, these being the CH selection and the communication phase. The novelty of our method is that we used the FMCDM technique for CH selection in an SCE. Using this method, we reduced the consumption of energy and increased network stability and lifetime in inter-cluster and intra-cluster multi-hop communication models in WSNs.  
Figure 1: Sensor cloud environment architecture [1].  
This paper is organized as follows. Section 2 is a review of CH selection techniques for WSN. CH selection using the fuzzy MCDM techniques FAHP and FANP is discussed in Section 3, and so too is the CH selection algorithm. In Section 4, the result analysis of the proposed technique is discussed. The concluding remarks are discussed in Section 5.