Internet-of-Things (IoT) Shortest Path Algorithms and Communication Case Studies for Maintaining Connectivity in Harsh Environements

摘要

Research on the shortest path in networks to maintain connectivity in the Internet of Things (IoT) remains an important issue for determining minimal routes, especially in terms of time and distance, between two devices at distinct points (i.e., nodes) of the network. Many constraints exist for IoT smart devices for transmitting a large amount of information and data, such as limited resources, energy, and time consumption, as well as the potential for overwhelmed communication traffic. Several algorithms were designed and implemented to address these problems that can be simulated and considered as information message passing. The search space is often modeled by a graph, where each node corresponds to a location of a smart device, and the edges represent the paths or links that carry messages, while the absence of a path between two nodes designates a communication breakdown or obstacle. Existing pathfinding algorithms are incorporated in applications, such as Google Maps, rescue people, video games, online packet routing, and rescue applications used in harsh environments. For these latter scenarios, the infrastructure for various technologies of communication becomes vulnerable and dysfunctional, so maintaining connectivity and finding the shortest path becomes a priority. Our goal is to remedy this problem by taking advantage of modernized peer-to-peer wireless technologies, such as Wi-Fi Direct, which can be improved through autonomous wireless technology kits like Lopy 4 of Pycom, and through two alternatives of moving devices (nodes) or service drones. This paper investigates several shortest path algorithms and identifies three case studies to maintain connectivity in harsh environments.