# Energy-Efficient Region Shift Scheme to Support Mobile Sink Group in Wireless Sensor Networks
## 4 Performance Evaluation
If the number of member sinks increases, average delivery ratio of GMR significantly decreases because concentration of packets around a source due to location updates of all member sinks causes congestion and collision. RingRouting also shows drop of the ratio due to the congestion of the rendezvous area. In M-Geocasting, if the number of member sinks grows, it increases loss of location report due to congestion and collision possibility around LS when LS obtains location information of member sinks. Therefore, region miscalculation may occur and drops data delivery ratio. ERMG shows a relatively stable ratio due to the fact that hierarchical communication reduces collision probability, but it still has a hot spot around cell heads. On the other hand, in RSMGP, it rarely takes effect on congestion and collision because only a few sinks deviate group region report location information to the pivot node. Figure 11 depicts data delivery ratio for the speed of mobile sink group. If the speed increases, the data delivery ratio of GMR rapidly decreases. Every mobile sink in the group updates its own location to the source. Since all update messages are forwarded on a similar path, a number of message losses  
Figure 10: Data delivery ratio impacted by the number of member sinks. Figure 9: Energy consumption impacted by the radius of group area. occur by collision and congestion. RingRouting prevents long-distance communication of the location update, but the congestion around rendezvous area drops the delivery ratio. In M-Geocasting, while it recalculates a group region and updates to a source, some sinks could not receive since group location information that sinks know may not exactly correspond with new information. Accordingly, the data delivery ratio of M-Geocasting decreases slightly as the speed of the group increases. However, in RSMGP, data are delivered with high delivery ratio since new location information of sink group is reflected directly by overhearing. In addition, ERMG is almost not influenced by the moving speed. The reason is that movement in a cell is affected only by its cell, and it does not cause long-distance communication and means low congestion. Figure 12 shows the number of available nodes according to elapsed simulation time. In GMR, the nodes are depleted earlier than other schemes. This is because each of the member sinks updates its own location globally to a source and the traffic is concentrated around the source. In addition, as discussed above, the traffic concentration causes collision and congestion. Because of this, retransmission is frequently required and thus increases energy depletion more. RingRouting shows stable performance in the early stage, but the number of available nodes rapidly decreases due to detour paths after nodes around the rendezvous structure being depleted. On the other hand, M-Geocasting has one representative sink per group. Thus, the energy consumption of location update is trivial. However, region calculation based on flooding quickens the energy depletion of the nodes on the trajectory of a mobile sink group. ERMG reduces entire communication overhead, but it accelerates node depletion around cell heads. In RSMGP, only a few nodes participate in the region calculation and the intermediate nodes do not waste power on location updating. Thus, the scheme has an advantage over the network life time. Figure 11: Data delivery ratio impacted by moving speed of a sink group. Figure 13 compares the control overhead between various guard area size. We observe that small radius of the guard area is advantageous for caching, but is disadvantageous for region update. If the radius is too small, region departure reporting occurs too frequently in the case that a group moves fast. On the contrary, if the radius is too large, caching overhead increases in order to deliver data to member sinks in the guard area.