Parallel Implementation of a Sailing Assistance Application in a Cloud Environment

Abstract

Sailboat weather routing is a highly complex problem in terms of both the computational time and memory. The reason for this is a large search resulting in a multitude of possible routes and a variety of user preferences. Analysing all possible routes is only feasible for small sailing regions, low-resolution maps, or sailboat movements on a grid. Therefore, various heuristic approaches are often applied, which can find solutions within an acceptable time, sacrificing their optimality and accuracy. In this study, we propose a different approach based on the parallel implementation of an exact algorithm. Specifically, we present a Sailing Assistance Application (SAA) utilizing a deterministic approach and show how it can be parallelized in a cloud environment to reduce its execution time. The potential of the proposed parallelization method goes beyond the particular presented solution; it can be used to improve the performance of other weather routing tools such as collision avoidance and related applications.

Keywords

• Big data
• cloud computing
• constraint optimization
• decision support systems
• graph theory
• marine navigation