Bus*: An efficient algorithm for finding Moving K-Nearest Neighbors (MKNNs) with capacity constraints

Abstract

The large-scale and increasing use of transportation systems in various applications is expected to become an important component of communications networks beyond 5G and 6G in the next decade. To effectively support the massive deployment of transportation systems, reliable, secure, and cost-effective wireless connectivity is required. Communication networks are very important for vehicles that act as mobile user equipment. Although communications networks offer a promising way for cars to stay connected, it isn't easy to make transportation work well. This paper aims to present a new and interesting problem: the finding of the moving K-nearest neighbors (MKNNs), where each neighbor has a capacity limit. Specifically, considering a set of moving objects with different capacity constraints distributed in the road network, query objects with a certain load, find the optimal set of neighbors where the total available capacity is equal to or greater than the load of the query object, and the total travel time of the optimal set to reach the query object is minimized. This problem has significant applications in our lives. For example, it can help bus operating companies find other optimal bus trains in operation to move to the location of the damaged bus and transport its passengers to their destinations. In contrast, the total travel time of the optimal train is minimized. This paper uses previous research methods with a qualitative descriptive approach from sources that researchers found. The results of this research serve as material for proposing new algorithms that are effective for solving problems in real-time when using real data sets