Abstract
In this paper, a new approach to energy harvesting and data transmission optimization in a heterogeneous-based multi-class and multiple resource wireless transmission wireless sensor network system that focus on monitoring water and its quality is presented. Currently, energy is a scarce resource in wireless sensor networks due to the limited energy budget of batteries, which are typically employed for powering sensors. Once the available energy of a particular sensor node battery is depleted, such sensor node becomes inactive in a network. As a consequence, such node may not be able to participate in the transmission of the application signal in the uplink stage of the network, resulting in a lack of ability to communicate vital signals in a timely manner. Energy scarcity has been a long standing problem in wireless sensor network applications. To address this problem, energy harvesting from intended radiofrequency power source is considered in this work. However, wirelessly powered wireless sensor network systems are confronted by unfairness in resource allocation problem, as well as interference problem in multiple energy resource transmissions. These problems adversely impact the performance of the system in the context of the harvested energy by the sensor nodes, sensors information transmission rates, and the overall system throughput rate. These problems are tackled in this paper by formulating a sum-throughput maximization problem to reduce system energy consumption and enhance the system overall throughput rate. The throughput optimization problem is formulated as a non-convex function. Through the exploitation of the problem structure, it is converted to a convex function. The mathematical models of the optimization problem are validated through numerical simulations. The simulation results reveal that the proposed wireless powered sensor network system outperforms an existing wireless powered sensor network system, by comparison of the numerical simulations of this work to the numerical simulations of the existing WPSN system, regardless of the distances of the sensor nodes to the IPS and the base station. Also, the newly proposed method performs efficiently using parameters that include path-loss exponent impact, performance comparison of systems, convergence based on iteration, comparison based on unequal network distances to the BS, transmission power impact on the attainable throughput and on fraction of energy consumed on information transmissions, and influence of different number of nodes in the network classes.
Highlights
In recent times, there has been an upsurge in the need for efficient sensing systems for monitoring the parameters of water quality that include bacteria load and pH values, in a timely fashion [1, 2]
4 Results and discussion This section presents the performance of the proposed optimization algorithm by investigating the effects of number of sensors, path-loss exponent, and transmission power on the system, through simulation experiments
5 Conclusion This paper has proposed a new approach to energy harvesting and data transmission optimization in a heterogeneous multi-class and multiple resource wireless transmission system that focuses on monitoring water and its quality
Summary
There has been an upsurge in the need for efficient sensing systems for monitoring the parameters of water quality that include bacteria load and pH values, in a timely fashion [1, 2]. An approximate estimate of 250 million cases of disease caused by polluted water is reported annually [7]. These diseases are responsible for human death and claims up to about ten million lives across the globe annually [7] This is an indication that water problems caused by contaminants are major issues in this dispensation. The alarming rate of human death on a global scale caused by water pollution is as a result of a surge in water and environmental contaminants. These contaminants are due to two major factors, namely natural processes and man-made (anthropogenic) activities [2, 8, 9]. Examples of natural phenomena that adversely influence the quality of water through climatic factors are run-off caused by hydrological conditions, rock weathering, soil leaching, depositions caused by wind, and evapotranspiration, while some of the key man-made activities that negatively influences the quality of water are mining operations, deforestation, agricultural run-off, and industrial effluent [10]
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