Wireless networks comprise the majority of devices within the growing edge of the global communication system. Performance metrics determining the successful application of wireless networks in that setting are goodput, latency and network lifetime. Overhead retransmissions due to redundant data transfer, inefficient transmissions, low link quality, and suboptimal network layer protocols affect negatively these three metrics. Designing wireless networks to minimize the overhead retransmissions encompasses three network levels: the data, structural and procedural levels. Encoded sensing (ES) is a "data-aware" scheme that shapes the network structural level to account for correlations across data sources and common data across groups of nodes. Via new encoding algorithms, ES achieves substantial reduction of the transmissions required to convey a message to a sink node. A few beneficial properties for network hardware and design, based on sparsity of ES signals, are also discussed. The structural level is further augmented by the placement of relay nodes to minimize the overhead retransmissions in the network due to low quality and heavily loaded links. Finally, the Time Sequence Scheme operates on the network procedural level, allowing for broadcast of messages reaching all network nodes, while minimizing redundant broadcast retransmissions. Explicitly minimizing the number of retransmissions at each of the three network levels impacts beneficially performance as shown by analysis and full network stack simulations.