Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, data collection becomes one of the major issues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage-especially Unmanned Aerial Vehicles (UAVs)-is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern.

Wireless Sensor Networks consist of battery-limited sensor nodes which have the ability of sensing the environment, communicating with other nodes and processing the data. Large number of sensor node deployment over a geographical area imposes some constraints on the retrieval of the data. The use of mobile sinks (e.g., Unmanned Aerial Vehicle, UAV) is an effective solution method for such large-scale networks. However, depending on the path and altitude of the UAV, and the type of radios in use, coverage problem arises where some nodes cannot get connected to the UAV. In this paper, the coverage problem is examined where UAV is used as mobile sink node. On the basis of our analysis, a dynamic and distributed clustering approach is proposed. Evaluations are performed with a realistic simulation environment. Performance results show that proposed approach reduces the energy-consumption and construct more stable and well balanced clusters that connect the uncovered nodes to the UAV.

A novel source-initiated geographical data flow technique, called Stateless Weighted Routing (SWR), is presented in this paper. Nodes keep only their own virtual geographical position and require no local topological information. Each node calculates the weight of its own. Initially, this value is its relative distance to the sink. Each node decides to retransmit or to drop the packet received by comparing its own weight to the weight of the sender and the weight of the sink, i.e, destination, which are contained in the received packet. The comparison actually provides the mean for stateless routing. Although the weight parameter includes only the distance information for the time being, it may also include QoS (Quality ofService) parameters such as the energy left at the node. QoS will definitely help to increase the lifetime of the system. Having had the feature of being stateless, the technique is made free from the use of excessive communications to handle the routing tables. The SWR provides braided-paths ifnot multi-paths, naturally which is essential to improve reliability and to serve for the time-critical data. The use of thresholds in retransmissions provides the system with a flexible and energy-efficient data flow. Moreover, to the best of our knowledge, the SWR is known to be the first stateless routing technique running independent of the MAC-layer underneath.

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