# Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study
## 5 Lessons Learned and Recommendation  
This section consolidates the knowledge obtained from the simulation outputs and the theoretical information provided in the considered studies. At first, we list the lesson learned from the study as follows:  
Figure 11: Analysis of packet delivery and drops. Figure 10: Analysis of control packet consumption. * Sink Mobility vs. Delay The delay will increase significantly if the mobile agent does not follow any optimized trajectory. With an increasing area, if the delay is not addressed, the model will fail [71]. * Sink Mobility vs. Energy Consumption Energy consumption increases if the sink mobility is not adaptive and does not change based on the CH position [72]. Pre-assuming the mobility of a sink is not valid, and it will lead to a high number of packet drops. * Number of CHs vs. Energy Consumption If the number of CHs is too small compared to the number of CMs, the amount of energy consumed by the CHs will be higher owing to the volume of received data [73]. Even though the energy consumption of receiving data is less than that of transmitting it, receiving a significant volume of data will consume considerable energy. Conversely, if the number of CMs is too high compared to the number of CHs, the volume of transmitted data will also increase, thus consuming more energy. * Distributed Clustering vs. Control Packet Overhead A distributed clustering algorithm increases the number of exchanged control packets to form clusters. By contrast, the static infrastructure-assisted clustering algorithm is performed by the infrastructure itself, resulting in a lower number of exchanged control packets [74]. * Geographical Knowledge vs. Control Packet Overhead Prior knowledge of positional information creates extra pressure on buffer memory; however, the number of control packets is reduced. In the absence of GPS information, one way of gathering neighboring data is to estimate the distance of the neighboring node based on the received signal strength and angle of arrival. However, despite having flaws, the GPS is more accurate than the aforementioned mechanism. By contrast, the GPS does not provide good results in an indoor system, which may trigger other mechanisms. In such a scenario, the number of control packets can only be a secondary optimization parameter. * Sink Mobility vs. Number of Packets Dropped  
Sink mobility is directly related to the number of packets dropped. The sink speed can vary from very high to low--the sink may or may not have a variable speed for transmitting data to the CHs. For this reason, the CHs may not have enough time to transmit all of their data in a single round. Consequently, the data remains in the buffer of the CHs and may cause buffer overflows. In a mobile sink-based WSN data-collection protocol, none of the protocols have any kind of adaptive mobility for the sink's mobility [75]. * CH Position vs. Data-Collection Position In the investigated WSN data-collection mechanism, the CPDC protocol selects the CH based on a predefined sink position. This is a poor setup, as there is no mechanism adopted for the data-collection position to be adopted with any changed position of the CHs. * Planned Deployment Reality vs. Expectation The IoJHR protocol provides better results in terms of energy consumption and dead nodes compared to other protocols. However, the IoJHR protocol assumes that a node is the planned deployment. This is the biggest disadvantage of this approach. The clustering mechanism and CH selection mechanism are also heavily dependent on the planned deployment. Thus, in the case of random deployment and pattern less deployment of a real-life scenario, the IoJHR protocol will yield poorer results. Based on the lessons learned, the recommendations for designing a well-balanced data-collection mechanism in WSNs are as follows:  
* Adaptive Speed of the SinkThe mobile sink should exhibit adaptive speed by maintaining the amount of data to be transferred from a CH. The speed of a sink can reach up to 30 m/s.