A Perpetual Compression Scheme for Delay Tolerant Communication

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.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-04-03
DOI
https://doi.org/10.1109/jiot.2025.3557024
Primary Topic
Opportunistic and Delay-Tolerant Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

A Perpetual Compression Scheme for Delay Tolerant Communication

Sanku Kumar Roy, Ioanis Nikolaidis
IEEE Internet of Things Journal
Opportunistic and Delay-Tolerant Networks
article

A Perpetual Compression Scheme for Delay Tolerant Communication

Sanku Kumar Roy, Ioanis Nikolaidis
article en

Abstract

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.

IEEE Internet of Things JournalVol. 12(13)
University of Alberta (CA)
Alberta Innovates, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 94%
Opportunistic and Delay-Tolerant Networks
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A Perpetual Compression Scheme for Delay Tolerant Communication — Sanku Kumar Roy, Ioanis Nikolaidis · IEEE Internet of Things Journal (2025) | TGRS Research Map | TGRS