INTENSYV - INTelligent wirEless NetworkS powered by energY harVesting

Autonomous and reliable operation is the holy grail of a wide array of wireless networking applications, where the ultimate goal is to operate for as long as possible under the quality of service requirements dictated by the application. In other words, given a system-level energy constraint, the problem to solve is that of energy efficiency. Yet, advances in energy harvesting (EH) technology in the last decade have shifted the viewpoint from energy efficiency to intelligent energy management: can wireless networks be designed to run virtually forever harvesting energy from the environment? Such a design would obviate the need for battery replacement or recharging, which is costly, inconvenient
and, in some cases, close to impossible.

Building on recent pioneering research on the design of intelligent EH wireless systems consisting of a single link or a few links, the goal of this proposal is to develop a framework for the study and design of general EH wireless networks Lwith an arbitrary number of nodes, taking into account complexity and physical constraints associated with the devices, the spatial and temporal characteristics of the harvested energy and the network topology. In particular, we will focus on the following main objectives: (a) the design and performance evaluation of resource allocation and cooperation policies for multi-user EH wireless communication networks; (b) the design and performance evaluation of distributed sensing algorithms based on EH sensors; and (c) the macroscopic performance analysis of EH wireless network taking into account the random topology of the network nodes and the random spatial characteristics of the ambient harvested energy. Through the proposed research, we expect to obtain analytical and simulation results on the performance gains obtained by optimizing the operation of an EH wireless network. These results will provide important guidelines for the design of EH wireless sensor and ad hoc networks in practice.