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Driven by the Internet of Things vision, recent years have seen the rise ofnew horizons for the wireless ecosystem in which a very large number of mobilelow power devices interact to run sophisticated applications. The mainhindrance to the massive deployment of low power nodes is most probably theprohibitive maintenance cost of battery replacement and the ecotoxicity of thebattery production/end-of-life. An emerging research direction to avoid batteryreplacement is the combination of radio frequency energy harvesting and mobilecomputing (MC). In this paper, we propose the use of simultaneous informationand power transfer (SWIPT) to control the distributed computation process whiledelivering power to perform the computation tasks requested. A real-time MCsystem is considered, meaning that the trade-off between the information rateand the energy harvested must be carefully chosen to guarantee that the CPU mayperform tasks of given complexity before receiving a new control signal. Inorder to provide a system-level perspective on the performance of SWIPT-MCnetworks, we propose a mathematical framework based on stochastic geometry tocharacterise the rate-energy trade-off of the system. The resulting achievableperformance region is then put in relation with the CPU energy consumption toinvestigate the operating conditions of real-time computing systems. Finally,numerical results illustrate the joint effect of the network densification andthe propagation environment on the optimisation of the CPU usage.

SWIPT-based Real-Time Mobile Computing Systems: A Stochastic Geometry Perspective