Socially-aware E-Box deployment schemes for joint data forwarding and energy harvesting

With the conversion capability from radio frequency into electricity, Radio Frequency based Energy Harvesting (RF-EH) has appeared as a promising means to overcome the battery exhaustion problem of mobile devices. However, despite the great efforts in RF-EH communication techniques made recently, a big drawback that limits the application of RF-EH is the large propagation loss of radio signal energy. This paper attempts to address this problem through deploying multiple energy sources in the network based on cognitive techniques that can perceive and analyze user behaviors. Under a Mobile Social Network (MSN) scenario, we conduct energy source deployment in combination with the throwbox deployment problem, which aims at improving data forwarding efficiency. Our focus is on both data forwarding (DF) and energy harvesting (EH) efficiency. We propose three deployment schemes, i.e., D-deployment, E-deployment and T-deployment. With a continuous-time Markov chain based mobility model, we formulate these deployment schemes as three optimization problems, respectively. Simulation results indicate that the proposed schemes outperform an existing deployment scheme in terms of both DF efficiency and EH efficiency.