Adaptive Data Transmission Scheduling On Energy Harvesting Wireless Sensor Node

The unchangeable and limited energy supply constrains the design and application of wireless sensor networks(WSNs), especially for applications in unfriendly environment. Recently, with the development of hardware design and environment energy harvesting technology, wireless sensor nodes can harvest solar, wind, water and thermal and transformed them to refresh the sensor nodes. As a result, Energy harvesting wireless sensor networks(EHWSNs) emergencies. While, the uncertainty of environment and randomness of harvested energy brings great challenges for the application of wireless sensor networks. How to make full use of the energy harvested to get the optimized performance is the focus of the research. So we consider the optimal transmission policies of wireless sensor nodes corresponding to the uncertainty of environment and randomness of harvested energy. The main work and innovations are as following:Firstly, based on the characteristics of energy arrived and data transmission, A data transmission model to maximizing the data delivered during a defined time period is established. An offline policy—looking forward-backward searching policy(FBS policy) is applied to solve the global optimization problem.Secondly, based on the characteristics of energy harvesting, we module the energy harvesting process with Markov chains and predict the energy harvested with Markov prediction. An adaptive data transmission policy(AFBS policy) is proposed to achieve the optimized data transmission without the message of energy harvesting.Thirdly, Simulation results show that the proposed FBS policy can achieve the goal of maximizing data delivered before the deadline. The longer the transmission time, the better the performance is. Furthermore, the performance of the amount of data transmitted by AFBS is bigger than the energy used up(EUP) policy and close to the optimized offline policy.