## 1 Introduction  
Traditional grids (TG), designed over 100 years ago, were built to supply electricity to communities [1]. Their centralised structure comprises generation, transmission, distribution, and end-users phases. However, they no longer meet the modern world's needs adequately due to increasing energy demands, increasing distributed energy resources (DER) deployments, and extreme-weather-related power outages. Smart grids (SG) are promising, resilient, efficient, and controllable solutions. SGs have various applications, including advanced smart metering infrastructure (AMI) [2], vehicle-to-grid (V2G) [3], electric vehicles (EV) [4], and networked microgrids (NMG) [5]. The main idea of SGs is to facilitate distributed power grids that provide a two-way exchange of information and electricity. We illustrate the transition from TGs to SGs to highlight the role of communication networks from generation to end-users in Figure 1. NMGs are defined in IEEE 2030.7-2017 as a group of interconnected loads and DERs with clearly defined electrical boundaries that act as a single controllable entity with respect to the grid and can connect and disconnect from the grid to enable operation in both grid-connected or off-grid modes [6]. They constitute a critical component of community electrification and may help to achieve net zero carbon emission targets. While NMGs and SGs employ similar technologies, such as photovoltaic (PV) panels, wind turbines, and battery storage, NMGs have the ability to operate independently, running as self-sufficient power systems [7]. Figure 2 represents the communication and power networks integration in NMGs. Communication networks are crucial for two-way control data exchange between NMG endpoints. Wired and wireless communication technologies are utilised to develop communication networks in the NMG configurations [8; 9]. The selection of communication technology depends on the requirements of NMG deployment. Integration of these technologies into NMGs enables system management, including power line monitoring, control data transmission, and supply-demand management [10]. The selected communication network needs to consider quality of delivery (QoD) requirements, including round trip time (RTT), packet loss, and throughput [11]. As various traffic types share the same communication network with NMG control data, large and variable RTTs become a QoD concern. Increased RTTs negatively impact control data transmission, potentially causing delayed control signal propagation. These challenges in the communication network compromise the effective operation of NMGs. Communication between NMG endpoints, \(i\) and \(j\), in Figure 3 consists of two types of messages: control data and acknowledgment (ACK) messages. At time index \(n\), sender endpoint \(i\) sends control data to receiver endpoint \(j\) at time \(t_{ij}[n]\). Once the control data are received, the receiver endpoint responds by sending an ACK message back to the sender endpoint. The sender endpoint receives the ACK message at \(t_{ij}[n+2]\). During this process, both the control data and the ACK message are subject to transmission \(t_{t}\) and propagation \(t_{p}\) delays. The total elapsed time between sending the control data and receiving the ACK message is defined as the RTT. The RTT between NMG endpoints \(i\) and \(j\) is denoted as \(r_{ij}\) and is measured as follows:  
\[r_{ij}(t_{ij}[n],t_{ij}[n+2])=2t_{t}+2t_{p}. \tag{1}\]  
One-way delay in NMGs is measured in [12; 13]. The RTT measurements are used to assess network performance and network congestion in the transmission control protocol (TCP) [14]. Given that NMGs allow bidirectional transmission of control data and ACK messages, RTT measurement provides a more comprehensive approach to understanding QoD measurement in NMGs. Few papers measure RTT as a QoD metric [15], while many papers employ simulation tools to represent NMGs in different areas of communication  
Figure 1: The SGs provide two-way communication for both electricity and information.