We present a pragmatic view of different approaches used to guarantee data delivery in a deployable marine habitat monitoring system, composed of a two-tier dual frequency (2.4 GHz/900 MHz) hierarchical wireless sensor network (WSN). We cover endto-end application layer aspects. At the lower tier, we preconfigured endpoint (EP) transceivers for automatic data acquisition and wireless transfer using their native Application Program Interface (API) framework. These endpoints communicate with a more powerful intermediate cluster-head (CLH) system. At the upper tier, we deployed a modified low level 8-bit "Lighter" version of the well-known web application protocol called JavaScript Object Notation (JSON, or in our case LJSON) for back and forth CLH to BS validated message exchange. These LJSON messages are converted by the BS to 16-bit JSON and vice versa, for remote Internet interaction. And finally, the BS software establishes Internet Protocol (IP) client socket connections with a remote custom JSON service, in charge of marine habitat sensor data reception, verification, and nonvolatile database storage.

We present refinements of a novel transmission power control (TPC) algorithm based on temperature and relative humidity (TRH). Previously, we deployed a prototype TRH TPC algorithm on wireless sensor nodes operating in real harsh environmental conditions and reported promising results. Since then, we have made enhancements of the TRH TPC model, which we will show here. Furthermore, in order to develop an understanding of the nonlinear behavior that we observed from this TRH TPC scheme, we developed a simulation platform that uses real radio frequency (RF) signal and interference samples and actual T and RH sensor data acquired simultaneously. Afterwards, we logged results of repeated experiments and determined the algorithms operating ranges and behaviors, varying its main parameters, such as (1) its gain factor, (2) the average time period to recalculate power level updates, and (3) proper received signal threshold selection. We then summarize optimal parameter ranges from the analytical results that reflect where this TRH TPC technique works best. And finally, we report results of the TRH TPC algorithm running on long range WSN systems deployed in harsh environmental conditions, corroborating behaviors observed through simulation.

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