| Summary: | The Internet of Things, the interconnection of all computing devices, is a concept that has become very popular nowadays and many companies try to achieve a leading role in shaping its future. Billions of devices are already connected to IoT cloud networks and this number is expected to rapidly increase in the near future. Devices in an IoT cloud network can be producers or consumers of data, while some can be processors. As data often needs processing in order to be transformed from lower to higher conceptual value, before being delivered to the consumers, this processing has to be done in an efficient manner. Ideally processing should take place in the proximity of data producers as opposed to having to transfer large volumes of data over the network in order to reach the processor. For this problem to be solved, scheduling algorithms require additional information that quantifies the "distance" between the different nodes in an IoT cloud network. Consequently, the main focus of this work is the development and the evaluation of an efficient mechanism that uses a heuristic technique to estimate this information, the latency between nodes, greatly reducing to linear the running time complexity that, if every device had to contact every other to calculate it, would be O(n^2).
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