Adaptive sensing and compression rate selection scheme for energy-harvesting wireless sensor networks

In wireless sensor networks, a node that increases its sensing rate to gather more data consumes more energy. Consequently, it will be exhausted earlier than other nodes. In this article, we propose a sensing rate control scheme to increase data resolution without increasing the number of blackout nodes in energy-harvesting wireless sensor networks. In the proposed scheme, each node selects a compression algorithm and adjusts the sensing rate to gather more data while the node operates properly. When a node is estimated to have extra energy, it gathers additional data. In contrast, when it is estimated to be exhausted, it gathers less data to save energy. It also selects an appropriate compression algorithm according to the compression ratio of the selected algorithm to reduce the workload of intermediate nodes. An experimental result verifies that the proposed scheme gathers more data with a lower number of blackout nodes than other schemes.