# A Hybrid Unequal Clustering Based on Density with Energy Conservation in Wireless Nodes
## 2 Literature Review
This protocol improves the quality of the communication within the intracluster and intercluster by creating virtual clusters based on square grids and proper selection of the steps. This protocol divided the network into equally square-shaped grids so that in each grid one or more nodes might exist. According to the local information of the nodes' condition and grids, clustering was performed in a way that one cluster can occupy one or more grid. To reduce the overhead of CH, the multihop routing algorithm calculated the most efficient route between clusters; therefore, the source node does not need to transmit the data through the middle CHs to BS. In CH Competition stage of this method, it can be improved by considering the node's distance to the BS. An energy-efficient QoS routing for WSNs using a self-stabilizing algorithm was proposed in 2015 [28]. This paper presented a self-stabilizing hop-constrained energy-efficient (SHE) clustering and a multi-hop routing algorithm for declining the delay and improving the quality of packet transmission. This protocol performs as a hybrid clustering method. CHs are determined by the BS in a definitive and offline Method and routing is done as distributed and online. The advantage of this protocol is that clustering is initialized only once at the beginning of the network. This protocol is based on TDMA schedules using the clustering algorithm for transmitting the data within the cluster in a manner that the nodes of the cluster with a tolerable delay send their own data to CH. Also, an adaptable routing protocol was proposed for data transmission between CH and the BS. [PERSON] et al. [29] proposed an energy-aware distributed routing algorithm to tolerate network failure in WSNs. This protocol has specific routing schemes for better tolerating the network failure in the current position. This scheme includes three new algorithms. In a distributed energy-efficient heterogeneous clustering (DEEHC) network clustering is done according to the residual energy in order to minimize the energy required for data transmission. During clustering, each sensor node finds k-vertex disjoint paths for sending data to the CH according to the energy levels of neighbor nodes. In other words, the routing between nodes CH and BS is done based on the proposed k-vertex disjoint path routing (KVDPR) algorithm. In addition, the route maintenance mechanism (RMM) algorithm enables nodes and CH to keep a route, which is based on the neighbor nodes energy conditions and prevents failure. In DEEHC algorithm, for determining CH using computing time, distance to the BS, and node density are not considered. [PERSON] et al. [30] proposed a dynamic and cooperative clustering. Furthermore, a new technique called the neighborhood formation scheme is presented. This algorithm aims to distribute energy demand among nodes and optimize a number of sensors involved in detection and report of events. This algorithm is executed distributed and dynamically. Results show that the proposed framework improved network lifetime and reliability in data transmission. An energy-aware multi-hop routing (EAMR) protocol was proposed in 2017 [31]. This method aims to reduce overhead by reducing variations of CHs. In this method, a method similar to LEACH [3] is sued to select initial CHs to form clusters. EAMR allows a node to operate as a cluster head until its energy is not lower than a threshold; therefore, in this algorithm, CHs vary only when required. In order to improve network lifetime, this algorithm employs multi-hop routing. However, since membership of nodes in a cluster does not change until the end, in selecting the initial CHs, many of the important parameters like nodes density and distance from BS is not considered. To sum up, the above section has summarized some clustering protocols which were provided to increase wireless node lifetime and that also reviewed recent hybrid methods to reduce the overhead and increase the lifetime of wireless nodes.