The technological paradigm of the Internet of Things has attracted the attention of the market, industry, and scientific community. The possibility of integrating wireless sensor network (WSN) devices to the Internet has prompted the Internet Engineering Task Force (IETF) to specify new standards and protocols, such as the Routing Protocol for Low-Power and Lossy Networks (RPL), designed to find stable routing paths via links that have considerable losses. Among the routing metrics, the expected transmission count (ETX) is notable because its implementation in RPL helps choosing reliable paths. However, the rapid exhaustion of battery energy at bottleneck nodes remains a problem. In this context, this study introduces the network interface average power metric (NIAP), a new metric based on the estimated average power consumption of the network interface, which contributes not only to the choice of reliable paths but also to load balancing and lifetime increasing of a wireless sensor network. The results of several experiments conducted in a simulated environment demonstrate that NIAP is a promising alternative to ETX due to its simple implementation without modifications of the RPL standard.

This article presents a strategy for channel assignment in Internet of Things (IoT) networks. The proposed strategy uses opportunistic spectrum access via cognitive radios. The originality of this work resides in the use of traffic history to guide the channel allocation in a distributed manner. The channel assignment algorithm mitigates the interference in links with higher traffic history. Our performance evaluation shows that using the historical network traffic as a decision criterion leads to better results when compared with the simple use of the network topology as a criterion.