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Cloud Computing, or the Cloud, became one of the most used technologies in today's world, right after its possibilities had been figured out. It is a renowned technology that enables ubiquitous access to tasks that need collaboration or remote monitoring. It is widely used in daily lives as well as the industry. The paradigm uses Internet Technologies which rely on best-effort communication. Best-effort communication limits the applicability of the technology in the domains where the timing is critical. Edge Computing is a paradigm that is seen as a complementary technology to the Cloud. It is expected to solve the Quality of Service (QoS) and latency problems that are raised due to the increased count of connected devices, and the physical distance between the infrastructure and devices. The Edge Computing adds a new tier between Information Technology (IT) and Operational Technology (OT) and brings the computing power close to the source of the data. Computing power near devices reduces the dependency to the Internet; hence, in case of a network failure, the computation can still continue. Close proximity deployments also enable the application of Edge Computing in the areas where real-timeliness is necessary. Computation and communication in Edge Computing are performed via Edge Servers. This thesis suggests a standardized and hardware-independent software reference architecture for Edge Servers that can be realized as a framework on servers, to be used on domains where the timing is critical. The suggested architecture is scalable, extensible, modular, multi-user supported, and decentralized. In decentralized systems, several precautions must be taken into consideration, such as latencies, delays, and available resources of the neighbouring servers. The resulting architecture evaluates these factors and enables real-time execution. It also hides the complexity of low-level communication and automates the collaboration between Edge Servers to enable seamless offloading in case of a need due to lack of resources. The thesis also validates an exemplary instance of the architecture with at framework, called Real-Time Execution Framework (RTEF), with multiple scenarios. The tasks used are resource-demanding and requested to be executed on an Edge Server in an Edge Network comprising multiple Edge Servers. The servers can make decisions by evaluating their availabilities, and determine the optimal location to execute the task, without causing deadline misses. Even under a heavy load, the decisions made by the servers to execute the tasks on time were correct, and the concept is proven.