Joint Slot Scheduling and Power Allocation in Clustered Underwater Acoustic Sensor Networks

On‐board energy scheduling optimization algorithm for nanosatellites

“…In the literature, there are several examples of researches that aim to optimize the use of resources (such as energy, communication slots, or computing time) to meet certain objectives (such as profit, coverage, energy efficiency, or benefits). Examples include the stochastic biobjective disassembly sequence planning (DSP) problem, which involves maximizing disassembly profit and minimizing energy consumption subject to a chance constraint 1 ; the multiobjective resource-constrained disassembly optimization problem, which involves optimizing disassembly sequences in industrial products in order to improve recovery efficiency and reduce environmental impact 2 ; the problem of deploying energyharvesting directional sensor networks for optimal target coverage, which involves optimizing the communication route selection and energy usage in a wireless network 3 ; the joint slot scheduling and power allocation problem in clustered Underwater Acoustic Sensor Networks (UASNs), which involves scheduling the use of communication resources to optimize the energy usage of the network 4 ; and the fully distributed microgrid system model, which involves optimizing the charging and discharging states of electric vehicles to maximize benefits. 5 In the same sense, as energy availability on a satellite is directly related to its capacity to perform different tasks simultaneously or accommodate higher consumption payloads, there is a general interest in maximizing its generated energy and efficiently distributing the harvested energy.…”