{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T16:39:04Z","timestamp":1776443944697,"version":"3.51.2"},"reference-count":23,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,3,17]],"date-time":"2022-03-17T00:00:00Z","timestamp":1647475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>In an IoT (Internet of Things) system, the autonomy of battery-operated edge devices is of paramount importance. When such devices operate intermittently, reducing power consumption during standby improves such a characteristic. The deep-sleep operation mode obtains such a result: it keeps on power only the hardware needed to wake up the unit after a timeout or an external trigger. For this reason, deep sleep exhibits the issue of losing the working memory, which prevents its use with applications depending on long-lasting or stateful computations. A way to circumvent such an issue consists of saving a snapshot of the working memory on a remote repository. However, such a solution is not always convenient since it exhibits an energy footprint due to checkpoint transmission. This article analyzes the applicability of such a solution. Firstly, by comparing its energy footprint against keeping the working memory on power. The analysis follows a formal, technology-agnostic methodology based on a mathematical model for energy consumption. It yields a discriminant inequality identifying the use cases where remote checkpointing is of interest. Once justified the approach, the article proceeds by defining an architecture and a secure protocol for data transport and storage. Finally, the description of a prototype implementation provides concrete insights.<\/jats:p>","DOI":"10.3390\/info13030156","type":"journal-article","created":{"date-parts":[[2022,3,20]],"date-time":"2022-03-20T21:30:14Z","timestamp":1647811814000},"page":"156","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Deep-Sleep for Stateful IoT Edge Devices"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9734-2044","authenticated-orcid":false,"given":"Augusto","family":"Ciuffoletti","sequence":"first","affiliation":[{"name":"Dipartimento di Informatica, Universit\u00e0 di Pisa, I-56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"373","DOI":"10.3846\/transport.2019.10402","article-title":"Beacon technology for real-time informing the traffic network users about the environment","volume":"34","author":"Husnjak","year":"2019","journal-title":"Transport"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"186821","DOI":"10.1109\/ACCESS.2020.3030090","article-title":"IoT in the Wake of COVID-19: A Survey on Contributions, Challenges and Evolution","volume":"8","author":"Ndiaye","year":"2020","journal-title":"IEEE Access"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.future.2017.03.034","article-title":"Smart City and IoT","volume":"76","author":"Ramos","year":"2017","journal-title":"Future Gener. 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