The introduction of a drone-based mobile sink into wireless sensor networks (WSNs), which has flexible mobility to move to each sensor node and gather data with a single-hop transmission, makes cumbersome multi-hop transmissions unnecessary, thereby facilitating data gathering from widely-spread sensor nodes. However, each sensor node spends significant amount of energy during their idle state where they wait for the mobile sink to come close to their vicinity for data gathering. In order to solve this problem, in this paper, we apply a wake-up receiver to each sensor node, which consumes much smaller power than the main radio used for data transmissions. The main radio interface is woken up only when the wake-up receiver attached to each node detects a wake-up signal transmitted by the mobile sink. For this mobile and on-demand data gathering, this paper proposes a route control framework that decides the mobility route for a drone-based mobile sink, considering the interactions between wake-up control and physical layer (PHY) and medium access control (MAC) layer operations. We investigate the optimality and effectiveness of the route obtained by the proposed framework with computer simulations. Furthermore, we present experimental results obtained with our test-bed of a WSN employing a drone-based mobile sink and wake-up receivers. All these results give us the insight on the role of wake-up receiver in mobile and on-demand sensing data gathering and its interactions with protocol/system designs.

The location-based routing protocol has proven to be scalable and efficient in large wireless sensor networks with mobile sinks. A great challenge in location-based routing protocols is the design of scalable distributed location service that tracks the current locations of mobile sinks. Although various location services have been proposed in the literature, hierarchical-based location services have the significant advantage of high scalability. However, most of them depend on a global hierarchy of grids. A major disadvantage of this design is that high control overhead occurs when mobile sinks cross the boundaries of the top level grids. In this paper, we introduce Hierarchical Ring Location Service (HRLS) protocol, a practical distributed location service that provides sink location information in a scalable and distributed manner. In contrast to existing hierarchical-based location services, each sink in HRLS constructs its own hierarchy of grid rings distributively. To reduce the communication overhead of location update, sinks utilize the lazy update mechanism with their indirect location. Once a sensor node detects a target, it queries the location of a sink by sending request packets in eight directions. HRLS is evaluated through mathematical analysis and simulations. Compared with a well-known hierarchical-based location service, our results show that HRLS provides a more scalable and efficient distributed location service in scenarios with various network size, sink mobility and increasing number of source nodes.

We propose a novel scheme that aims to determine the optimal number of clusters based on the field conditions and the positions of mobile sink nodes. In addition, we merge algorithms of tree-based index structures to form an energy-efficient cluster structure. A performance evaluation shows that the proposed method produces highly-balanced clusters that are energy efficient and achieves up to 1.4 times higher survival rates than the previous clustering schemes, under various operational conditions.

Many methods have been researched to prolong the lifetime of sensor networks that use mobile technologies. In the mobile sink research, there are the track based methods and the anchor points based methods as representative operation methods for mobile sinks. However, most existing methods decrease the Quality of Service (QoS) and lead to routing hotspots in the vicinity of the mobile sinks. The main reason is that they use static mobile sink movement paths that ignore the network environment such as the query position and the data priority. In this paper, we propose a novel mobile sink operation method that solves the problems of the existing methods. In our method, the probe priority of the mobile sink is determined from data priority to increase the QoS. The mobility of sink used to reduce the routing hotspot. Experiments show that the proposed method reduces the query response time and improves the network lifetime much more than the existing methods.

In large-scale wireless sensor networks, in order to support group mobility of mobile sinks, this letter proposes a novel strategy for energy-efficient and robust data dissemination to the sinks based on cluster-based communication. The novel strategy is composed of two major mechanisms for reduction of structure construction overhead and routing state maintenance overhead: 1) a virtual infrastructure construction through grid-referred clustering and 2) inter-cluster communication by geographic routing relying on recursive location search. Based on the two major mechanisms, the strategy provides representative location management per sink group, distributed data collection, and per-cluster foot-print chaining in order to effectively adapt the traditional strategy for individual mobile sinks. Simulation results prove the proposed strategy shows better performances in terms of energy efficiency and robustness of data dissemination.

Wireless sensor networks present a promising opportunity for realizing many practical applications. Tracking is one of the important applications of these networks. Many approaches have been proposed in the literature to deal with the tracking problem. Recently, a particular type of tracking problem called on-site tracking has been introduced [15],[16]. On-site tracking has been characterized as the tracking in which the sink is eventually required to be present in the vicinity of the target, possibly to perform further actions. In this paper, first we propose two efficient on-site tracking algorithms. Then, we derive theoretical upper bounds for the tracking time and the number of messages generated by the sensor nodes during the tracking for our algorithms. Finally, we present a simulation study that we conducted to evaluate the performance of our algorithms. The results show that our algorithms are efficient as compared to the other existing methods that can solve the on-site tracking problem. In particular, the path adaptive nature of the sink in our algorithms allows the network to conserve the energy and the sink to reduce the tracking time.