## 5 Analysis of Prominent Clustering Routing Protocols in WSNs
### Cluster-Construction Based Clustering Routing Protocols
#### 5.1.3 Dwehc  
Distributed Weight-based Energy-efficient Hierarchical Clustering protocol (DWEHC), proposed by [PERSON] _et al_. [16], is a distributed clustering algorithm similar to HEED. The main objective of DWEHC is to improve HEED by building balanced cluster sizes and optimize the intra-cluster topology using location awareness of the nodes. Both DWEHC and HEED share some similarities including no assumptions about network size and density, and considering residual energy in the process of CH election. Every node implements DWEHC individually and the algorithm ends after several iterations that are implemented in a distributed manner.  
Different from LEACH and HEED, DWEHC creates a multi-level structure for intra-cluster communication and limits a parent node's number of children. Moreover, the only locally calculated parameter weight is defined for CH election in DWEHC. After locating the neighboring nodes in its area, each node calculates its weight according to:  
\[W_{\text{weight}}(s)=\frac{E_{\text{residual}}(s)}{E_{\text{initial}}(s)} \times\sum_{u}\frac{R-d}{6R} \tag{3}\]  
where \(E_{\text{residual}}(s)\) and \(E_{\text{initial}}(s)\) are respectively residual and initial energy at node \(s\), \(R\) is the cluster range that corresponds to how far from the CH to a node inside a cluster, and \(d\) is the distance between node \(s\) and the neighboring node \(u\). In a neighborhood, according to Equation (3), the node with largest weight would be elected a CH and the other nodes become members. At this stage, MNs are considered as 1-level nodes and communicate directly with the CH. A MN can progressively adjust such membership in order to reach a CH using the least amount of energy. Given the node's knowledge of the distance to its neighbors, it can assess whether it is better to stay a 1-level member or become a \(h\)-level one where \(h\) is the number of hops from the CH to itself. If a MN can save energy while reaching its CH with more than one hop, it will become a \(h\)-level member. The process continues until all nodes achieve the most energy-efficient intra-cluster topology. Energy consumption for communicate in a cluster can be computed according to node's knowledge of the distance to its neighbors. To limit the number of levels, every cluster is assigned a cluster range \(R\) within which MNs should lay. The structure of multi-level cluster in DWEHC is illustrated in Figure 3. After running DWEHC, a node either becomes a CH or becomes a child in a cluster, and a node is covered by only one CH.  
Intra-cluster communication is performed by TDMA. Each parent node polls its direct children and forwards the data to its parent node until the data reaches the CH. The parent node may aggregates several data packets from its children together with its own data into one packet. For inter-cluster communication, the CHs poll their first-level children, including their own data, and transmit to the BS.  
The following is the advantages of DWEHC: (1) Like HEED, it is a fully distributed clustering method that is based on a function of the sensor's energy reserve and the proximity to the neighbors for CH election; (2) Considering energy reserves in CH election, DWEHC generates more well-balanced CHs distribution and achieves significantly lower energy consumption in intra-cluster and inter-cluster routing than HEED; (3) The clustering process of DWEHC terminates in a few iterations, and does not depend on network topology or size.  
Some disadvantages of DWEHC are summarized as follows: (1) Similar to LEACH, single-hop inter-communication, directly from CHs to the BS, is performed in DWEHC. Thus DWEHC may result in significant amount of energy consumption, and is not applicable to large-region networks; (2) In the process of cluster formation, the iterative nature in both DWEHC and HEED produces a relatively high control message overhead compared to other protocols.  
Figure 3: The Structure of Multi-level Cluster in DWEHC.