The issue of energy balancing in Wireless Sensor Networks is a pivotal one, crucial in their deployment. This problem can be subdivided in three areas: (i) energy conservation techniques, usually implying minimizing the cost of communication at the nodes since it is known that the radio is the biggest consumer of the available energy; (ii) energy-harvesting techniques, converting energy from not full-time available environmental sources and usually storing it; and (iii) energy transfer techniques, sharing energy resources from one node (either specialized or not) to another one. In this article, we survey the main contributions in these three areas and identify the main trending topics in recent research. A discussion and some future directions are also included.

Sunlight is one of the most frequently used ambient energy sources for energy harvesting in wireless sensor networks. Although virtually unlimited, solar radiation experiences significant variations depending on the weather, the season, and the time of day, so solar-powered nodes commonly employ solar prediction models to effectively adapt their energy demands to harvesting dynamics. We present in this paper a novel energy prediction model that makes use of the altitude angle of the sun at different times of day to predict future solar energy availability. Unlike most of the state-of-the-art predictors that use past energy observations to make predictions, our model does not require one to maintain local energy harvesting patterns of past days. Performance evaluation shows that our scheme is able to provide accurate predictions for arbitrary forecasting horizons by performing just a few low complexity operations. Moreover, our proposal is extremely simple to set up since it does not require any particular tuning for each different scenario or location.

The efforts to replace the successful, albeit aging, TCP/IP Internet architecture with a better suited one have driving research interest to information-centric alternatives. The Named Data Networking (NDN) architecture is probably one of the main contenders to become the network layer of the future Internet thanks to its inbuilt support for mobility, in-network caching, security and, in general, for being better adapted to the needs of current network applications. At the same time, massive satellite constellations are currently being deployed in low Earth orbits (LEO) to provide a backend for network connectivity. It is expected that, very soon, these constellations will function as proper networks thanks to inter-satellite communication links. These new satellite networks will be able to benefit from their greenfield status and the new network architectures. In this paper we analyze how to deploy the network caches of an NDN-based LEO satellite network. In particular, we show how we can jointly select the most appropriate caching nodes for each piece of content and how to forward data across the constellation in two simple alternative ways. Performance results show that the caching and forwarding strategies proposed reduce path lengths up to a third with just a few caching nodes while, simultaneously, helping to spread the load along the network.

TCP Vegas provides better performance compared to traditional TCP Reno schemes. However, backward traffic significantly degrades Vegas efficiency causing underutilization of the available bandwidth and unfairness. In this letter, we present an enhanced congestion control mechanism for TCP Vegas able to correctly remove the undesired impact of reverse traffic on bandwidth sharing. Furthermore, our proposal is easily deployable because it does not require neither clock synchronization nor any special support at the intermediate routers