Energy-Aware Optimization of Communication and Computation in Indoor IoT Swarm Networks
In this paper, we propose an Energy-Aware Cross-Layer Communication and Computation Optimization (EACCO) framework to maximize energy efficiency and operational lifetime of indoor Internet of Things (IoT) swarm robotic networks. The method takes into account energy harvesting, adaptive scheduling, communication and computation altogether in a single cross-layer optimization framework. Results of simulation show that EACCO reduced the energy consumed per day to 2.0-2.3 Wh/day and obtained the energy neutral ratio (ENR) of 1.05-1.18, increased the packet delivery ratio (PDR) to 95-97% and increased mission lifetime to 30-36 hours compared to other energy-only, EDF and FIFO schedulers under the same operating conditions. The results show the effectiveness of EACCO to design reliable, energy neutral and sustainable indoor IoT swarm robotic systems.