Need of Wireless Sensor Network (WSN) is increasing day by day due to its exponential applications in unmanned monitoring situations. The sensor nodes are battery powered and energy starving in nature; this requires frequent recharging of batteries and loss of nodes in some cases [1–۴]. Improving network lifetime increases the monitoring duration and reduces the human intervention often. Typical sensor node consists of sensing unit, processing unit, transceiving unit and power unit [3–۷]. In some cases power unit will be having energy harvesting device which makes the network lifetime infinity based on the availability of resource to harvest energy. The transceiving unit acts as a Full Function Device (FFD) (i.e.) router and Reduced Function Device (RFD) (i.e.) end device. The increase in network lifetime can only be done either by limiting the data or the distance between the sender and receiver [8–۱۳]. The clustered architecture in WSN favours very large region to be monitored and also provides increased lifetime when compared to the layered architecture. The layered architecture suits small Region of Interest (RoI) in which all nodes are nearly one hop to the sink. The clustered architecture consists of nodes working either as participant or head [14–۱۸]. The duty assigned to the head is to collect data from all the members and send to the sink (i.e.) it acts as a router to the network [19–۲۳]. The other participant simply forwards the data to the CH to pass the same to the sink via other CH. Figure 1 illustrates the typical Clustering architecture of WSN. The data from the sensor device is aggregated in the CH and the same is transmitted to the sink via the nearby CHs. The CH near the sink is overloaded transmitting its own cluster data and the data from the far away cluster. So number of clusters near the sink is increased, thereby load is shared among more number of CHs resulting in reduction of energy holes.

۲ Related Works

Many of the routing protocols in WSN concentrate on increasing the lifetime and throughput of the network [2, 3, 13, 14]. The algorithm increases the lifetime by scheduling the communication module and limiting the number of bits sent through the communication module. The CH selection in the WSN mainly influences the network lifetime and throughput. The energy hole problem in WSN disables the communication to the sink, though the nodes far away from the sink are capable to do the same. The solution to the energy hole problem is given through multiple sink and mobile sink approach [15, 16]. However tracing the sink mobility and channel contention problem is an unsolved issue in the WSN. The Low Energy Adaptive Clustering Hierarchical routing protocol [12] provides better lifetime and throughput when compared with layered architecture. The CH selection is based on the random number in case of the LEACH algorithm, availing chance of energy holes and hotspot issue inside the network. The Battery recovery based lifetime enhancement algorithm addressed [15] provides solution to energy hole and hotspot problem by modelling the recovery effect of the battery. The Fail Safe Fault Tolerant algorithm addresses the fair CH selection based on the voltage level of the battery. The voltage level of the battery is a clear indicator to get knowledge on the residual energy of the node. The energy spent by the node is a factor of distance and number of bits sent by the sender to the receiver [13, 24, 25].