Ocean-surface Wireless Sensor Networks (WSN) are essential in various thalassic applications, such as maritime communication, ocean monitoring, seawater examination, pollution detection, etc. Formed by simple structured sensor nodes, ocean-surface WSN can improve the data transmission rate, enhance the monitoring resolution, expand the geographical coverage, extend the observation period, and lower the cost compared to the vessel-based monitoring approaches. Despite the importance and the broad applications of ocean-surface WSNs, little is known about the stability of the wireless links among the sensors. Especially, research suffers from the lack of an accurate model that describes the environmnetal effects, including the ocean surface movements and the wind speed on the link stability. The inappropriate understanding of link stability can result in network protocols that are not robust to environmental interruptions. Such a shortcoming decreases the network reliability and degrades the accuracy of the network planning. To compensate for this shortcoming, in this dissertation, we provide a thorough analysis on the stability of the wireless links over the ocean. In particular, we investigate and capture the effects of ocean waves on the link stability through the following steps. First, we use the linear wave theory and obtain a novel stochastic model of Line-of-Sight (LoS) links over the ocean based on the realistic behavior of ocean waves. Second, we present and prove an important theorem on the level-crossing of Wide Sense Stationary (WSS) random processes, and combine that with our stochastic model of LoS links to study two important indicators of link stability, i.e., the blockage probability and the blockage and connectivity periods. The former indicates the probability that a LoS link is blocked by the ocean waves while the latter determines the duration of on/off periods of the LoS links over the ocean. The aforementioned stability parameters directly affect different stages of network design, such as choosing the antenna height, planning the sensors' deployment distances, determining the packet length, designing the retransmission and scheduling strategies in the Medium Access Control (MAC) protocols and transport layer protocols, selecting the fragmentation threshold in Internet Protocol (IP), etc., which will be discussed in the respective chapters. In the last part of our dissertation, we investigate the problem of linear prediction of ocean waves, which has special importance in the design of ocean-surface WSNs. In this regard, we first introduce a low-complexity metric for effectiveness of k-step-ahead linear prediction, which we refer to as efficiency curve. The significance of efficiency curve becomes evident when we decide upon the number of previous samples in the linear prediction model, and determine the extent to which the predictor forecasts the future. After efficiency curve, we formulate an adaptive Wiener filter to predict the ocean waves and adapt the prediction model according to the environmental changes. / Doctor of Philosophy / Covering almost three quarters of the earth and supplying half of its oxygen, oceans are vital to the support of life on our planet. It is important to continuously monitor different parts of the ocean environment for tracking climate changes, detecting pollution, etc. However, the existing monitoring approaches have serious weaknesses, which prevent us from constantly monitoring the state of ocean, and drastically limit the geographical coverage. For instance, the traditional ocean monitoring system using oceanographic research vessels is time-consuming and expensive. Besides, it has low resolution in time and space, which poses serious challenges to oceanographers by providing under-sampled records of the ocean. To compensate for these defects, one of the promising alternatives is to employ Wireless Sensor Networks (WSN) which has many advantages, such as real-time access to data for a longer period of time and a larger geographical coverage of the ocean, higher resolution of monitoring, faster processing of collected data and instantaneous transmission to onshore monitoring centers. With the benefit of simple structure sensor nodes, ocean-surface WSNs can also decrease the cost by at least one order of magnitude compared to the conventional approaches. Despite the advantages that ocean surface WSN have over traditional ocean monitoring methods, ocean surface WSN research suffers from the lack of an accurate model that describes the stability of wireless links among sensor nodes. While some of the existing literature has developed accurate models of the electromagnetic wave propagation over the ocean surface, they have failed to consider the environmental effects, such as ocean waves on the stability of the links. To fill this void, in this dissertation, we investigate ocean surface waves' effects on the Line-of-Sight (LoS) link between the sensors in an ocean-surface WSN. Specifically, we derive the blockage probability, and the blockage and connectivity periods of LoS links between a transmitter and receiver pair due to wave movements. In addition to the link stability analysis, we dedicate the last part of this dissertation to look into the problem of linear prediction of ocean waves, which has special importance in the design process of ocean-surface WSNs. In this regard, we present a low-complexity metric for effectiveness of k-step-ahead linear prediction, and formulate an adaptive Wiener filter to predict the ocean waves and adapt the prediction model according to the environmental changes.