Protocols for wireless sensor networks are generally designed following the layered protocol stack where layers are independent. Uncorrelated decisions coming from different layers may affect certain metrics such as the latency of communications, the energy consumption, etc. Cross-layer approaches overcome this problem by exploiting the dependencies between the layers. In this article, the authors propose latency and energy mac-aware routing for wireless sensor networks (LEMAR-WSN), a new cross-layer routing approach using information of the TDMA schedule and exploiting the information of the energy consumed by each node in order to optimize the latency of communications and the energy consumption when relaying information to the sink in a wireless sensor network. Simulation results show that the proposed approach improves the average latency of communications up to 20% and the average.

The Energy Internet (EI) has been proposed as an evolution of the power system in order to improve its efficiency in terms of energy generation, transmission and consumption. It aims to make the use of renewable energy effective. Herein, the energy router has been considered the crucial element that builds the net structure between the different EI components by connecting and controlling the bidirectional power and data flow. The increased use of renewable energy sources in EI has contributed to the creation of a new competitive energy trading market known as peer-to-peer energy trading, which enables each component to be part of the trading process. As a consequence, the concept of energy routing is increasingly relevant. In fact, there are three issues that need to be taken into account during the energy routing process: the subscriber matching, the energy-efficient path and the transmission scheduling. In this work, we first proposed a peer-to-peer energy trading scheme to ensure a controllable and reliable EI. Then, we introduced a new energy routing approach to address the three routing issues. A subscriber matching mechanism is designed to determine which producer/producers should be assigned for each consumer by optimizing the energy cost and transmission losses. This mechanism provides a solution for both mono and multi-source consumers. An improved ant colony optimization-based energy routing protocol was developed to determine a non-congestion minimum loss path. For the multi-source consumer case, an energy particle swarm optimization algorithm was proposed to choose a set of producers and to decide the amount of energy that should be collected from each producer to satisfy the consumer request. Finally, the performance of the proposed protocol, in terms of power losses, cost and computation time was compared to the best existing algorithms in the literature. Simulation results show the effectiveness of the proposed approach.

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