## 2 Green Routing Algorithms in WSNs
### Energy-Efficient Scheduling-Based Routing Algorithms
#### 2.2.2 Mobile Node Scheduling-Based Schemes  
In WSNs with static sensor nodes, energy distribution becomes uneven with the continuous communication of sensor nodes. The distance from the source node to the sink directly affects the communication energy cost. The greater the distance, the more the energy consumed. To reduce power consumption, source nodes or the sink must move toward the goal area in mobile node scheduling-based routing schemes. Mobile nodes can optimize the transmission path between the source node and the destination node and reduce the energy consumption of the network. In order to save power efficiently, a global energy balancing routing protocol (GEBRP) was proposed [57], which adopts the virtual grid-based network model. In GEBRP, node mobility scheduling includes two phases: the diffusion phase and supplementary phase. In the diffusion phase, as shown in Figure 5, the nodes in the higher coverage areas are scheduled to move to the low-coverage areas to balance the network coverage. In the supplement phase, those nodes that fail or have low residual energy are replaced by high residual energy nodes. GEBRP balances the distribution of nodes in the diffusing phase and improves network robustness in the supplement phase. Meanwhile, GEBRP assumes that only a few nodes need to stay awake, while other nodes can switch to sleep mode. When there are multiple nodes in a virtual grid, GEBRP significantly reduces energy consumption. To balance the energy load, a reliable and energy-efficient routing protocol for mobile sinks (REEMS) was proposed [58], which schedules the mobile sink group to improve power efficiency. As shown in Figure 6, REEMS constructs a virtual block including a sink group, and the virtual grid is considered a boundary of the mobile sink group. Figure 4: Sleep scheduling of CKN and GSS: (**a**) neighbors of node C; (**b**) ranking of CKN; (**c**) ranking of GSS [55]. Packets are first transmitted to the boundary nodes of the virtual grid, and when the sinks leave the virtual grid, the data are received by sinks from the boundary node. The sinks obtain the data packets by moving out from the virtual grid, which ensures the reliability of the data forwarding and avoids situations where the registering area is different from the actual area. The mobility of the sink makes the source only need to send data to the area where the sink group may pass. Meanwhile, sinks can receive data packets from the boundary nodes. REEMS reduces energy consumption and enhances the forwarding ratio of data packets. A comparison of different energy-efficient scheduling-based routing algorithms is shown in Table 2, which considers metrics including energy saving, balance of energy load, and delay. Reducing energy consumption and balancing the energy load can both prolong the lifetime of WSNs. Static node scheduling-based schemes have merits in energy saving. However, the fact that many nodes sleep in such schemes causes an issue of delay. CKN and GSS consider the delay issue and try to decrease transmission delay. Mobile node scheduling-based schemes have advantages in balancing the energy and load in WSNs. GEBRP optimizes energy distribution by moving the nodes to balance the node density of different areas. REEMS utilizes the sink and sink group to balance the energy and load.