The number of IoT devices and their respective data is increasing for each day impacting the traditional architecture model of solely using the cloud for processing and storage in a negative way. This model may therefore need a supporting model to alleviate the different challenges for future IoT applications. Several researchers have described and presented algorithms and models with focus on distributed architecture models. The main issues with these however is that they fall short when it comes to the implementation and distribution of tasks. The former issue is that they are not implemented on actual hardware but simulated in a constrained environment. The latter issue is that they are not considering sharing a single task but to distribute a whole task. The objective of this thesis is therefore to present the different challenges regarding the traditional architecture model, investigate the research gap for the IoT and the different computing paradigms. Together with this implementing and evaluating a future architecture model capable of collaboration for the completion of a generated task on multiple off-the-shelf hardware. This model is evaluated based on task completion time, data size, and scalability. The results show that the different testbeds are capable communicating and splitting a single task to be completed on multiple devices. They further show that the testbeds containing multiple devices are performing better regarding completion time and do not suffer from noticeable scalability issues. Lastly, they show that the completion time drops remarkably for tasks that are split and distributed.