## 2 Background
### Communication
It allows devices with limited resources to take part by offloading complicated activities and distributing computation evenly between on-premise and remote resources. * Federated architecture with edge offloading: The process resembles cloud offloading, but its computations are offloaded to edge devices situated within the local network. This approach diminishes latency and decreases dependence on a remote cloud server. This technology is well-suited to use cases requiring real-time responses and minimal delay, frequently seen in IoT and edge computing environments. * Broadcast communication: The central server disseminates model updates to all participants concurrently, maintaining consistency across all devices. The broadcasting of updates, particularly when all participants require identical model parameters, conserves bandwidth and reduces time consumption. * Multicast communication: Model updates are distributed to distinct groups of participants, enabling selective broadcasting based on the degree to which two sets of data are comparable. When multiple groups of people work on similar activities, this pattern is helpful because it allows for the more efficient use of network resources. * Delayed communication: Participants gather updates on their local machines and deliver them in batches at regular intervals, thus decreasing the time spent communicating with the centralized server. This reduces the overhead of transmission and the delay, particularly in situations when real-time updates are not essential. The selection of a communication pattern substantially influences the effectiveness, scalability, and responsiveness of FLSs, rendering it a critical element in their design and execution. Every communication pattern possesses distinct advantages and trade-offs, making them appropriate for specific use scenarios. The selection of a particular pattern is contingent upon various aspects, including but not limited to the configuration of the network, the capabilities of the participants involved, the need for real-time features, and the need to maintain anonymity. A combination of these patterns is frequently utilized to achieve an ideal balance of various components. * Communication synchronization: In FLSs, \"communication synchronization\" refers to the process of coordinating and aligning the various communication activities that take place among the participating devices or nodes. It ensures that the processes of aggregation, exchanging data, and updating models happen in a structured and synchronized way. The devices must be synchronized correctly in order to maintain the reliability and precision of the collaborative model being trained across distributed devices. Communication in FLSs can be either synchronous or asynchronous [37]. * Synchronous communication: This type of communication involves individuals sending real-time updates on a predetermined timetable to the central server or other participants. Everybody synchronizes their communication so that aggregations and model updates happen simultaneously. This synchronous method creates an FLS with a coordinated and organized workflow. Synchronous communication is necessary for applications in autonomous vehicles because it ensures that the vehicle's model can adjust in real time to the constantly shifting conditions of the road and its surroundings. To take full advantage of the benefits of synchronous communication in FLSs, it is vital to properly manage network latency and bandwidth usage. * Asynchronous communication: This type of communication involves devices or nodes functioning autonomously without the requirement of precise time synchronization. In contrast to synchronous communication, which involves coordinating updates in rounds or at predetermined intervals, asynchronous communication enables participants to individually transmit their updates to the central server or other nodes according to their unique schedules [38].