# Data Collection Based on Opportunistic Node Connections in Wireless Sensor Networks
## 2 Related Work  
In traditional WSNs, all sensor nodes including the sink nodes are static, sensor nodes near the sink have more traffic loads for they have to participate in forwarding sensing data from all other nodes to the sink, therefore they easily exhaust their limited energy, and which will cause network partition. This problem is called the hot-spot problem [16] and it has an adverse effect on the network lifetime. To address this problem, in recent years researchers have introduced the mobile sink concept to networks. By fully exploiting the mobility of the mobile sink, the nodes around the sink could change continually, therefore the energy consumption in routing is distributed more evenly in the network, and thereby it prolongs the network lifetime. According to the work of the previous researchers, the path design for mobile sinks can be classified into predefined paths [17], controlled paths [18], or uncontrolled (random) paths [19]. By employing these paths, the mobile sink can play an important role in scenarios where nodes suffer opportunistic connections. For example, in Reference [20], the authors considered that the WSNs deployed within hostile environments might suffer from large-scale damage where many sensors failed simultaneously and this would cause the WSNs to split into disconnected segments, and they proposed a two-step heuristic for connecting isolated segments through intermittent links, in which a set of mobile nodes served as mobile data carriers. In Reference [21], the authors considered that in mobile sensor networks, the connectivity between nodes was intermittent due to the blockage of radio signals and nodal mobility, and they proposed a reliable data delivery scheme for the networks with an enhanced delay technique, in which nodes estimated the connectivity and expected inter-encounter time with sink nodes. All these approaches can equalize the energy consumption of nodes, but they are not flexible enough to prolong the network lifetime because they have not considered designing different node operating statuses. Therefore, the working-sleeping cycle strategy was introduced to WSNs, in which researchers considered that the proper scheduling of sensor nodes to sleep or work could effectively reduce their unnecessary energy consumption, thus prolonging the network lifetime. According to the node operating status, the researches can easily be divided into two main categories. In the first category, the studies aimed at synchronous working-sleeping cycle strategy, for example, in Reference [22], the authors proposed an event-triggered sleeping energy mode for the synchronous working-sleeping cycle strategy of sensor nodes, in which nodes with no data packets immediately entered sleeping status after the synchronization phase and did not participate in media access contention. However, the synchronization process remains a significant contributor to the energy consumption. To solve the problem, [PERSON] et al. [23] proposed an energy-efficient synchronization algorithm that could reduce energy consumption by adaptively regulating the synchronization traffic and synchronization wakeup period based on the changing network neighborhood conditions through counter-based and exponential-smoothing algorithms. In the second category, the studies focus on asynchronous working-sleeping cycle strategy, in which each node could have an independent working-sleeping scheduling, by scheduling a certain number of nodes to work; they can achieve the coverage for a specific area and ensure the network connectivity in it. In Reference [24], the authors presented a novel algorithm that relied on learning automata to implement sleeping scheduling approaches, and it aimed to activate a minimum number of sensor nodes to achieve coverage of a certain area and guarantee connectivity between these nodes. [PERSON] et al.