Graphs can be used to model the considerable structure of networks. For example, in computer networks, hubs, hosts, or servers. Graphs can represent vertices and edges represent links between them. In chemical networks, graphs can model atoms as vertices and bonds as edges. Metric locating parameters are used to locate an intruder, the nearest printer, malfunctioning node, damaged equipment, unauthorized connections, and robot positions.

Many problems in a network are challenging, costly, and, more importantly, time-consuming. They can be solved efficiently using metric locating parameters. In recent years, locating parameters have been widely applied in various fields of physical sciences, social sciences, engineering, and computer sciences. Due to the mathematical concepts, many new parameters are defined and used in solving metric-related problems. Among the most prominent metric parameters are edge resolvability, vertex-edge resolvability, multi-set resolvability, dominating resolvability, and their generalizations. These notions have applications in networking, facility location problems, master mind games, robot navigation, mathematical, and pharmaceutical chemistry. Moreover, it has been shown that these parameters are non-deterministic polynomial-time (NP)-hard.

The aim of this Special Issue is to solicit original research and review articles discussing metric locating parameters of networks. We hope to bring together research including new theoretical approaches that build on existing theories. We particularly welcome research involving graph theory models and their metric properties. Submissions must cover both identification and non-identification schemes.

Potential topics include but are not limited to the following:

• Localization in networks
• Locating number in networks
• Resolvability parameters in networks
• Accurate measurement in networks
• Robot navigation in networks
• Metric dimension in networks
• Edge metric dimension in networks
• Partition dimension in networks
• Complex networks with metric locating parameters
• Approximation algorithms in networks
• Fault-tolerant locating number in networks