Development of energy-efficient protocols and algorithms requires in-depth understanding of the power consumption characteristics of real world devices. To this aim, energy efficiency analysis is performed by the research community, mainly focusing on the development of power consumption models. However, recent studies [1] have highlighted the inability of existing models to accurately estimate energy consumption even in non-composite scenarios, where the operation of a single device is analyzed. The inability of such models is further highlighted under real life scenarios, where the impact induced by the simultaneous operation of several devices renders the application of traditional models completely inappropriate. As a result, energy efficiency evaluation under complex configurations and topologies, needs to be experimentally investigated through the application of online monitoring solutions. In this work, we propose the innovative NITOS Energy consumption Monitoring Framework (EMF) able to support online monitoring of energy expenditure, along with the experiment execution. The developed framework is built on a distributed network of low-cost, but highly accurate devices and is fully integrated with the large-scale wireless NITOS testbed. Framework evaluation is performed under both low-level experiments that demonstrate the platform's high-level accuracy, as well as through high-level experiments that showcase how online and distributed monitoring can facilitate energy performance assessment of realistic testbed experiments.

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LTE and LTE-A have dominated as a 4G enabler protocol, adopted by the majority of the network providers worldwide. The efficient performance of an LTE network relies on the selected frequency within an operating band that the cell operates, by taking into account all the potential factors that can affect it. Since cognitive radio is targeting towards the maximization of spectrum utilization, it is crucial that it is adopted in the spectrum allocation process. In this work, we propose an efficient scheme for cell planning by employing spectrum sensing techniques. By exploiting spectral information collected by several sensing devices, we appropriately select the center frequency inside the operating band, towards maximizing the quality of the end user experience. Our algorithms are implemented for the downlink channel, considering a variety of configurations and topologies. Finally, our implemented mechanism is evaluated in the real world deployment of the NITOS Future Internet facility, using commercial LTE enabled femto cells and UEs, while USRP sensing devices are employed for high quality spectral information provisioning.