The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration.

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Wireless Sensor Networks are ad hoc wireless networks that present hardware and energy reserve restrictions. In general, this kind of network can be utilized as powerful tools in order to monitor and, eventually, control an environment. The routing protocols, for the WSN, must have self-configuration characteristics aimed at discovering which is the best way for transferring the information, with delivery assurance and with minimum energy consumption, among the nodes that compose the network. This article proposes a modification of the Directed Diffusion routing protocol so as to reduce the energy consumption in the network when there is an occurrence of failures. The proposal utilizes a Geocast approach to repair broken paths by constructing a new routing tree. The performed simulations demonstrated that our proposal is more efficient from the energy viewpoint.

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