# Sink-Type-Dependent Data-Gathering Frameworks in Wireless Sensor Networks: A Comparative Study
###### Abstract  
Owing to automation trends, research on wireless sensor networks (WSNs) has become prevalent. In addition to static sinks, ground and aerial mobile sinks have become popular for data gathering because of the implementation of WSNs in hard-to-reach or infrastructure-less areas. Consequently, several data-gathering mechanisms in WSNs have been investigated, and the sink type plays a major role in energy consumption and other quality of service parameters, such as packet delivery ratio, delay, and throughput. However, the data-gathering schemes based on different sink types in WSNs have not been investigated previously. This paper reviews such data-gathering frameworks based on three different types of sinks (i.e., static, ground mobile, and aerial mobile sinks), analyzing the data-gathering frameworks both qualitatively and quantitatively. First, we examine the frameworks by discussing their working principles, advantages, and limitations, followed by a qualitative comparative study based on their main ideas, optimization criteria, and performance evaluation parameters. Next, we present a simulation-based quantitative comparison of three representative data-gathering schemes, one from each category. Simulation results are shown in terms of energy efficiency, number of dead nodes, number of exchanged control packets, and packet drop ratio. Finally, lessons learned from the investigation and recommendations made are summarized. wireless sensor network; static sink; mobile sink; energy efficiency; routing protocol; data gathering; aerial sink; unmanned aerial vehicle; base station [color=orange!20,linewidth=0.5 em,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,title=,titletitle=,title=,title=,title=,titletitle=,title=,titletitle=,title=,titletitle=,title=,titletitle=,title=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitle=,titletitletitle=  
gathering all the data transmitted from the sensor nodes [24]. The sensor nodes disseminate data in a multi-hop or single-hop fashion. Compared to multi-hop methods, the single-hop approach consumes more energy [25] for a longer transmission distance. Moreover, the data generated from neighboring sensors are often redundant and correlated. Consequently, different multi-hop methods for data gathering have been examined in the literature such as clustering [26; 27], tree-based [28], and hybrid techniques [29]. Clustering techniques have gained more acceptance in the research community for achieving network scalability, and several such techniques have been reported in the literature [30]. In multi-hop data transmission in WSNs, where the sink node is static, the sensor nodes close to it are more likely to run out of energy in comparison to other nodes because of the concentration of data traffic toward the sink; this is also known as the hotspot problem [31]. To solve this problem, a mobile sink has been used--the hotspot around the sink changes with the mobility of the sink--to provide load balancing in WSNs [32]. Mobile sink-based data gathering is relatively new compared to traditional data-gathering schemes using static sinks [33]. The mobile sink is responsible for entering a ROI and collecting data from the sensor nodes. In such frameworks, the consistent presence of a mobile sink in a ROI is not guaranteed. Utilizing a mobile sink helps to reduce the number of hops where the data are disseminated to the sink as it moves closer to the sender node. Although mobile sink-based solutions enable data gathering from remote places, in such applications, continuous monitoring is not possible without the help of a static infrastructure [34]. Aerial robots, such as unmanned aerial vehicles (UAVs), can play a significant role in mobile sink-based WSN data-gathering scenarios [35].