# Challenges of Network Forensic Investigation in Fog and Edge Computing
## 2 Background  
### Networking in Edge and Fog Computing  
The shift to an edge-centric paradigm has various consequences to the network design of these infrastructures. The main idea of an edge-centric computing environment results in a computation on the edge of a network; in combination with fog computing, this change provides the possibility to take  
_the control of computing applications, data, and services away from some central nodes (the \"core\") to the other logical extreme (the \"edge\") of the Internet_[6]. Improved network techniques provide higher transmission rates in networks, and with the help of virtual networks, distributed devices can be interconnected like in an LAN. Therefore, edge and fog computing environments affect network design like content delivery networks, P2P and cloud architectures. Networking in edge computing involves establishing communication and connectivity between edge devices, edge servers, and other components within the edge infrastructure. Figure 1 shows a sample interconnection between the involved devices. Endpoints (shown in the yellow area) are called edge devices. These devices, such as sensors, IoT devices, or smartphones, generate data or consume services at the network edge. They are typically resource-constrained and may have limited processing power, storage, and network capabilities. Intermediate nodes (shown in the blue area) are called edge servers and provide computational and storage resources closer to the edge devices. They act as local gateways, and aggregate, process and and analyze data from the edge devices. Edge servers can also host applications and services that offload processing tasks from the cloud and provide low-latency responses. Edge servers can be connected with each other, creating a hierarchy within edge servers with various interconnections and assigned jobs. The edge network infrastructure (ENI) is responsible for connecting edge devices and edge servers. It may consist of wired and wireless connections, such as Ethernet, Wi-Fi, cellular networks, or specialized IoT protocols. The network infrastructure ensures reliable and efficient data transfer between edge devices and edge servers. For the communication between server and endpoints and for the communication inside the ENI, various protocols are used. These protocols can include TCP/IP, MQTT, Constrained Application Protocol (CoAP), Zigbee, Bluetooth, LoRaWAN, or custom protocols depending on the specific requirements of the edge environment [7]. When communicating with external destinations, the ENI provides a routing and traffic management platform. This can involve protocols like Border Gateway Protocol (BGP), routing tables, and Quality of Service (QoS) mechanisms to prioritize traffic and ensure efficient utilization of network resources. A specific configuration is the opportunity to combine edge and cloud computing. The idea is to process time-critical tasks on the edge side, but to outsource resource-intensive, time-consuming or storage-intensive tasks to a server in the cloud environment. On top of these servers, the fog network part starts. Fog computing softens the strict separation between edge and cloud computing by adding another area. Inside this area, computational power, storage, and networking are closer to the devices and sensors which generate the data. The summarization of the information of various sources reduces  
Figure 1: Edge and fog networking. the continuous communication with cloud servers from each device. Thus, latency and response times are reduced and real-time processing and low-latency communications are possible. In addition to this, more efficient bandwidth utilization is possible, which provides benefits for various fields like industrial automation [8], smart cities [9], autonomous vehicles [10], and healthcare applications [11]. Fog computing allows local processing and analysis of data, occurring near the source, which helps in making faster and more context-aware decisions.