Link Scheduling in Rechargeable Wireless Sensor Networks with Limited Harvested Energy - Tony (Curtin University, 2021)
To date, rechargeable Wireless Sensor Networks are of great interest because sensor nodes are able to harvest energy from their environment, e.g., solar and wind, and store the harvested energy in rechargeable batteries. In this thesis, we design three greedy heuristic algorithms, i.e., LS-rWSN, LSBCC, and LSDBS, to solve three proposed link scheduling problems in rWSNs, i.e., LSHUS, LSME-1, and LSME-2. Simulations on arbitrary networks show the merits and effectiveness of the proposed solutions.