Maximum Data Collection Rate in Rechargeable Wireless Sensor Networks with Multiple Sinks
Maximum data collection rate in rechargeable wireless sensor networks with multiple sinks In Rechargeable Wireless Sensor Networks (R-WSNs), because of the sporadic availability of energy, it is critical that sensors operate in very low duty cycles in order to achieve the maximum data collection rate.
Moreover, a sensor can not always conserve energy if a network is able to harvest excessive energy from the environment due to its limited storage capacity. Therefore, energy exploitation and energy saving have to be traded off depending on different application scenarios.
Through extensive simulation and experiments, we demonstrate that our algorithm is effective in maximizing the data collection rate in rechargeable wireless sensor networks. We first define the network system, energy expenditure, and replenished model, data aggregation scheme, and elaborate on the packet delivery process in this work.
We demonstrate that our algorithm is efficient in rechargeable wireless sensor networks to maximize data collection rates through extensive simulation and experiments. Since it is NP hard, by introducing Lagrange, the original linear programming is converted into a dual problem and subgradient algorithms are used to solve it in a distributed way.