# Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks  
[PERSON]  
1 Department of Computer Science and Engineering, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;  
[EMAIL_ADDRESS] (G.Y. ); [EMAIL_ADDRESS] (Z.P.) [PERSON]  
1 Department of Computer Science and Engineering, School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;  
[EMAIL_ADDRESS] (G.Y. ); [EMAIL_ADDRESS] (Z.P.) [PERSON]  
3 Public Experiment Center, University of Shanghai for Science and Technology, Shanghai 200093, China  
* Correspondence: [EMAIL_ADDRESS]; Tel. : +86-187-2102-371233123312331233  
the movement trajectory for the mobile sink, the hot-spot problem [4] in traditional networks can be avoided and the energy consumption of sensor nodes can be more evenly balanced, thus prolonging the network lifetime. To fully explore the role of mobile nodes, in Reference [5], the authors proposed a joint energy replenishment and data collection algorithm, in which a mobile charger is used to replenish the energy for nodes and it can function as a mobile sink when equipped with wireless transceivers. In Reference [6], the authors proposed a Wi-Fi-based passive cyber-physical social sensing approach for tracking people's behaviors by sensing Wi-Fi messages from mobile devices people carry with them. However, these studies did not further consider changing the node operating status to achieve a better network lifetime performance. To cope with this challenge, researchers have proposed the working-sleeping cycle strategy for sensor nodes, in which nodes can go to sleep to save energy while they are free of work. These studies usually focus on designing node-scheduling schemes to accomplish data transmission, in which the working-sleeping cycle strategy can be categorized into synchronous and asynchronous [7]. Therefore, the changeable node operating status in this strategy is an advantage of these studies, which can prolong the network lifetime. However, the working-sleeping cycle strategy for nodes may cause opportunistic node connections, which results in link instability and affects the data collection efficiency. In fact, the reasons why opportunistic node connections exist in WSNs can be summarized as follows: (1) WSNs are often deployed in harsh environments where wireless signals are susceptible to interference, which may cause link instability [8], further leading to opportunistic node connections; (2) the movement of nodes usually leads to intermittent connected links and creates some form of opportunistic node connections [9]; (3) due to the limited energy of the nodes, in some scenarios the sensor nodes adopt a working-sleeping cycle strategy to save energy, and accordingly, the adjacent nodes may not be able to communicate with each other continuously [10], thus bringing about opportunistic node connections. This work considers that all sensor nodes adopt an asynchronous working-sleeping cycle strategy to save energy and a mobile sink is used to collect data in the network, as shown in Figure 1, where the network works based on opportunistic node connections since they may not be able to communicate with each other continuously. In this case, how to model this kind of WSNs to design a scheme, and based on which to ensure the reliability of data transmission in the network becomes a meaningful challenge. Figure 1: Illustration of a Wireless Sensor Network (WSN) with opportunistic node connections, in which sensor nodes adopt an asynchronous working–sleeping cycle strategy to save energy. To deal with this problem, the random graph theory originated by the pioneering work of [PERSON] and [PERSON] [11] was adopted to model WSNs, in which all sensor nodes are represented by graph vertices while all wireless links are represented by edges. All edges have a probability to reflect the quality of wireless links.