A Perpetual Compression Scheme for Delay Tolerant Communication
Sanku Kumar Roy, Ioanis Nikolaidis · IEEE Internet of Things Journal · 2025
We address the question of compressing, into a fixed amount of storage space, a periodically sampled sequence of scalar values. The length of the sequence is, a-priori, unknown. The compression logic targets the minimization of the L∞ reconstruction error. Because of the limited storage, all relevant compression processing is performed in–place. The proposed scheme involves a synthesis of an early (“batch”) phase, and a subsequent “incremental” (online) phase. The technique is suitable for wireless sensor networks with limited storage and with unpredictable, and possibly rare, opportunities to communicate their data. We demonstrate that our scheme outperforms legacy sub-sampling techniques and that its reconstruction error gracefully degrades as the length of the data sequence increases. We show how a couple kilobytes of storage is sufficient to represent long sequences of sampled data, making it suitable for microcontroller-based wireless sensor nodes.