Server-less computing has emerged as a very popular cloud technology. Together with its companionship with Function-as-a-Service (FaaS), this enables stateless function invocations from clients that are easy to handle and support scalability quite well. Driven by the unprecedented growth of data and IoT applications, recent years have seen a greater shift from cloud computing towards edge computing. The main feature of edge computing is to push cloud computing, network control and storage closer to the client at the edge of a network, supporting latency-critical and computation-intensive applications. The problem is, however, that mobile users frequently move from one place to another, changing their geographical location and making use of the current migration strategy exceedingly difficult. Hence, this leads to significant performance degradation by tampering with client session continuity, and no support for failures at the edge. Moreover, there is very little research on supporting stateful applications in the context of client mobility and using the FaaS paradigm.

This paper evaluates the current state-of-the-art state management techniques that support our specific use case. This use case involves a few characteristics, such as using the Function as a Service (FaaS) paradigm and supporting stateful server-less applications. It is important that the state management system is able to easily migrate or handle the state when the client moves from one place to another, ensuring continuity of the client session. Furthermore, it should prioritize handling the state, especially in light of potential edge failures, such as network issues or limited resources. This work further identifies two state management algorithms that have not yet been compared. It provides a detailed case study to decide which algorithm is better. Therefore, a methodology has been developed for comparing these different algorithms in both edge and cloud environments with different scenarios analyzing the performance of both the architectures using performance metrics like request-response latency, Throughput for reading and writing from the state. This study provides a systematic review of the current state of the art pertaining to state management techniques that support stateful server-less applications and a comparative study reviewing the challenges and benefits of the selected methodologies in real-time experimentation in the edge-cloud continuum. The paper offers valuable insights into the current state and future directions of Server-less Edge computing.