# A Novel Connectivity-Based LEACH-MEEC Routing Protocol for Mobile Wireless Sensor Network
## 2 Related Work  
A heterogeneous mobile LEACH protocol is proposed in [34]. It contains static sensor nodes with mobile base stations where CL is selected based on probability function and data are transferred to base station based on energy function. A mobility factor parameter is introduced for the CL election by initial mobile LEACH-Mobile-Enhanced (LEACH-ME) routing protocol [16]. However, this protocol increases complexity and energy depletion but performs well at a high mobility. Another mobility-based clustering (MBC) protocol was proposed by [PERSON] et al. [35], who used two metrics for the selection of CL, i.e., remaining energy and node speed. It has applications for large-scale networks but there is a rapid change in distance between nodes due to the high mobility. CL node may select a member node that has maximum remaining energy and mobility factor, but it may have a maximum distance from the CL node as well. Consequently, it drains CL energy. A mobile LEACH algorithm for large-scale networks was proposed by [PERSON] et al. [36], where energy is considered as the main component, defining three levels of energies with round time length. However, it has applications for only small scale static sensor network. A energy efficient LEACH-1R was proposed by [PERSON] and [PERSON] [37], where the CL selection is performed after the first round, only if the remaining energy is less than the threshold value. However, the author did not specify the mobility model. Similarly, LEACH-Centered Cluster-head (LEACH-CCH) was proposed by [PERSON] and [PERSON] [38], where the energy utilization is reduced by predicting the positions of mobile sensor nodes and reconstructing clusters accordingly. However, the nodes distribution is performed randomly and the mobility model is not mentioned. A LEACH-Mobile Average Energy (LEACH-MAE) based routing protocol is proposed in [39], which selects CL based on remaining energy metric. Here, a CL can add member nodes in a cluster that may have maximum remaining energy, but their distance from the CL node may also be maximum. Hence, CL node may lose a lot of energy to aggregate data from member nodes. LEACHDistance-M [40] is proposed for MWSN, where the selection of CL is based on remaining energy, lower-upper threshold distance and minimum mobility. However, it only assumes 30% of sensors nodes are mobile, while remaining sensor nodes are static.  
Those above-mentioned approaches [35; 36; 37; 38; 39] elect CL based on residual energy. The importance of energy metric in MWSN is vital, however, relative position, radio coverage and spatial density of mobile sensors are also important metrics for stability, consistency, and reliability of the CL, respectively. Connectivity in MWSN is a function of three important factors: transmission range, sensor speed and spatial density [41; 42]. Therefore, connectivity among nodes achieves robust communication, energy efficiency, reduced communication overhead and network scalability. The concept of connectivity in WSN is used in different perspectives. In [43], [PERSON] et al. improved connectivity using potential field theory and local virtual force to calculate mobility and location among mobile neighbor nodes. The conditional connectivity based algorithms were discussed in survey article [44], where the radio range were considered larger than twice of sensing range, consequently they achieved high connectivity at the cost of energy efficiency. To the best of our knowledge, connectivity as a metric for CL selection in mobile LEACH is unexplored, however, connectivity is discussed in MWSN in different perspectives. Hence, the motivation of this work is to combine connectivity with remaining energy in CL selection.