# Tracking Mobile Sinks via Analysis of Movement Angle Changes in WSNs
## 2 Related Work  
Since mobile sinks are flexible to move around and facilitate data gathering efficiency, they have been widely used in WSNs for data collection. To better benefit from mobile sinks' mobility, a lot of work has been done recently on the trajectories of mobile sinks in WSNs. These studies can be classified into three categories [8] based on the trajectory patterns of the mobile sinks: Controlled trajectory, random trajectory, and predicted trajectory.  
The first category of protocols requires mobile sinks to move along controlled trajectories [9; 10; 11; 12; 13]. In [9], a mobile sink moves along fixed trajectories and divides a monitored region into two parts, the Direct Communication Area (DCA) between the trajectories and the Multi-hop Communication Area (MCA) for far-off sensors, and the nodes within the MCA are assigned to the corresponding subsinks within the DCA according to the length of the communication time between the mobile sink and the subsinks. In [10], the authors developed a basic smooth path construction algorithm based on the traveling salesman problem, which can reduce the physical collection delay while achieving other performance improvements. In [11], [PERSON] and [PERSON] proposed a novel approach for mobile sink tracking based on a Hilbert Space Filling Curve which changes the curve order according to node density. These protocols can prolong network lifetime and reduce energy consumption, but have less flexibility due to the constrained trajectories of the mobile sinks. In our work, DAMST allows mobile sinks to move randomly.  
TTDD [14] is one of the protocols in the second category which uses randomly moving sinks to gather data. In TTDD, a grid structure is built among dissemination nodes and mobile sinks which constantly broadcast their location information and data queries along the dissemination nodes. SinkTrail [6] is another protocol in the second category, in which a mobile sink also needs to broadcast a trail message to each node, and a unique logical coordination of each node is updated according to the new trail message. In these two protocols, the continuous propagation of mobile sink location information throughout the whole network leads to high energy consumption and increased overhead. In DAMST, the trail message of a mobile sink is just sent along a path that is optimized via analysis of movement angle changes instead of broadcast to the whole network, which consumes less energy and has lower data overhead.  
Different from the aforementioned two categories of researches on mobile sinks, the third category focuses on predicting a sink's trajectory [15; 16]. In [15], [PERSON] and [PERSON] developed an approach for sending data to relay nodes along a predicted trajectory. In [16], routing states in the network are pre-computed and stored using a mobility graph. The predicted paths are however not accurate and may result in low data delivery rates.  
In our research, being aware of the fact that the movement angles could play important roles in tracking systems [17; 18], DAMST is designed to detect detours on the trajectory of a mobile sink by comparing movement angles between two sequential footprints, and reserve useful footprints by getting rid of those footprints on the detours. Furthermore, while constructing an appropriate data transition path among the useful footprints, it may happen that the distance between two adjacent useful footprints is greater than the node communication radius, in this case, DAMST tries to select appropriate relay nodes between the two unconnected adjacent footprints.