# Pido: Predictive Delay Optimization for Intertidal Wireless Sensor Networks
## 1 Introduction  
The intertidal zone, i.e., the region between the low and high tide lines, serves as a key testbed for exploring the effects of climate change on the distribution and abundance of organisms [1]. Environmental conditions in this habitat are among the harshest on Earth: waves frequently exert forces equivalent to those produced by wind speeds of over 1000 km h\({}^{-1}\) on land, and organisms are exposed to highly fluctuating levels of temperature, salinity and pH. Moreover, intertidal organisms (e.g., mussels, seastars, kelps) are exposed to the terrestrial environment each day at low tide for periods of up to 6-8 h or more. As ectothermic organisms, these plants and animals have body temperatures that are driven primarily by exposure to solar radiation [2], thus fluctuations in animal temperature of 25 \({}^{\circ}\)C or more over the course of a few hours are common. Recent studies have begun to pair local records of temperatures relevant to intertidal organisms [3] with controlled laboratory experiments to better understand and predict climate change impacts on this model system. However, making continuous recordings of temperatures is extremely difficult,especially in real time given high rates of instrument loss and failure. The development of a robust sensor network has shown considerable promise as a mechanism for addressing a host of ecological problems [4; 5; 6]. We deployed intertidal wireless sensor network systems (IT-WSN), at intertidal sites in Boston, MA and Georgetown SC (USA); and Hong Kong and Zhoushan (China). Our experimental results based on field tests demonstrate that WSNs in intertidal zones suffer several unique challenges, such as extremely unstable link qualities, intolerable delays and low packet delivery ratios. For example, it can take hours or even days to deliver a packet in IT-WSNs when the sensors are submerged under-water, which is far longer than that in common WSNs for other environments. Furthermore, we found that the buffer condition also played as an important role in the delay problem. This paper addresses the issue of reducing end-to-end packet delivery delays in intertidal WSNs. After analyzing the data we collected from IT-WSNs, we find that, not surprisingly, the changeable node status (i.e., available or not available) and unstable link quality caused by the wave force are the main reasons for the long delay. We show that existing delay optimization protocols such as DutyCon (Dynamic duty cycle Control scheme) [7], EDAL (Energy-efficient Delay-Aware Lifetime balancing data collection protocol) [8], BCMN/ A (Broadcasting Combined with Multi-NACK/ ACK) [9] and ORW (Opportunistic Routing in WSNs) [10] used to minimize packet delivery delay are not applicable for IT-WSNs, as these protocols focus on selecting a routing path with less transmission delay in relatively stable networks. In contrast, routing protocols like CREST [11] and CSPR (Conditional Shortest Path Routing) [12] are specifically designed for intermittent WSNs, which have similar characteristics with IT-WSNs. However, these protocols fail to consider the node conditions, e.g., the node buffer and node availability, which may lead to buffer overflow and unnecessary delay. Thus, the delay problem for IT-WSNs is yet to be solved. In the IT-WSN, the key difficulties for delay optimization are (a) to predict a future link quality of a node, i.e., whether a node is available or how good the quality of a link is, and (b) to consider the dynamics of nodes and links caused by changes in the environment. With this in mind, we attempted to reduce the delay in IT-WSNs by designing a suitable routing metric. With the new routing metric, nodes can predictively choose routes with less delay. To this end, we propose Pido, a Predictive delay optimization framework for intertidal WSNs. The design of Pido faces several challenges. First, the sources of delays in the IT-WSN are complex and we need to take all delay components into account for delay metric design.