Improving Data-Throughput in Energy Harvesting Wireless Sensor Networks Using a Data Mule

Abstract

Background: In Energy Harvesting Wireless Sensor Networks (EH-WSNs), sensors are harvesting energy from the renewable environment to make their operations endless and uninterrupted. However, in such a network, the time-varying nature of harvesting imposes a challenging issue in obtaining improved data-throughput. The use of a static-sink in EH-WSNs to improve data- throughput is less reliable because there is no assurance of the network connectivity. To alleviate such shortcomings, a Data Mule (MDM) has been introduced in EH-WSN for collecting sensors’ data. In this article, the MDM-based distance constrained tour finding problem is formulated such that the data-throughput can be improved within a given delay constraint. Methods: To solve the problem, we devise two different heuristic algorithms based on two different metrics. Results: The obtained experimental results demonstrate that the devised algorithms are more effective than the existing algorithms in terms of data-throughput. Conclusion: The data-throughput values of the first proposed algorithm are about 6.14% and 3.56% better than the other for two different data gathering time durations of 100 sec and 800 sec. The data-throughput values of the second proposed algorithm are about 5.03% and 5.25% better than the other for two different data gathering time durations of 100 sec and 800 sec.