Toward a Delay Tolerant Internet of Things

Internet of Things (IoT) is widely spread to reach many application domains (industry 4.0, eHealth, smart city...). However, smart objects in IoT environments are facing communication challenges because of their mobility, and limited resources (capacities in computing, storage and energy). The use of Delay Tolerant Network (DTN) as basis for communication in IoT is promising but needs more development. In this paper, we present a preliminary scheme that enables Delay tolerance for IoT environments. With respect to IoT constraints, the new solution based on reinforcement learning allows to continuously enhance the proposed model to increase the delivery ratio while optimizing resources consumption.