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This work is supported by the Spanish Ministry of Science and Innovation (MICINN) through "SIoTCom: Sustainability-Aware IoT Systems Driven by Social Communities" (PID2020-118969RB-I00).

Analysis of institutional authors

Perez, JenniferCorresponding AuthorGuaman, DanielAuthorCanas, NorbertoAuthor
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Proceedings Paper

Energy Consumption of IoT Monitoring Software Architectures in the Edge

Publicated to:Lecture Notes In Computer Science. 14889 217-232 - 2024-01-01 14889(), DOI: 10.1007/978-3-031-70797-1_15

Authors: Ochoa, JS; Pérez, J; García, J; Guamán, D; Cañas, N; Rodriguez-Horcajo, V

Affiliations

Univ Politecn Madrid, Madrid, Spain - Author
Univ Tecn Particular Loja, Loja, Ecuador - Author

Abstract

IoT has led energy consumption to be a critical issue for sustainability due to the huge amount of power connections of IoT devices and the huge amount of generated data that must be transmitted and stored. As a result, the data monitoring process and its processing activities must be performed by the nodes and servers of the Edge in a sustainable way. The IoT monitoring process of data consists of four main activities: listening, filtering, translating and routing. Once the data has been monitored, it can be stored and transmitted to the Edge/Cloud. In order to address sustainable monitoring processes in the Edge, it is necessary to evaluate how the configuration of the components that compose the Edge monitoring architecture may influence its energy consumption. In this paper, we present the experimental results of an exploratory study and its findings, in which the energy consumption of four different software architecture configurations of an indoor environmental monitoring IoT system is measured. From the execution of 24 experiments, the study reveals the importance of balancing the monitoring activities between the Edge nodes and servers, and evidences the energy consumption increment that data storage implies for the Edge.

Keywords
CloudCritical issuesData monitoringEdgeEdge cloudsEnergy consumptioEnergy consumptionEnergy-consumptionEnvironmental monitoringInterneIotMonitoring processPower connectionsProcessing activityRoutingsSoftware architectureSustainability

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Lecture Notes In Computer Science due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2024 there are still no calculated indicators, but in 2023, it was in position 13/61, thus managing to position itself as a Q1 (Primer Cuartil), in the category Computer Science, Theory & Methods. Notably, the journal is positioned above the 90th percentile.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-05-22:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 2 (PlumX).
Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Ecuador.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (Sebastian Ochoa, Juan) and Last Author (Rodriguez-Horcajo, Vanessa).

the author responsible for correspondence tasks has been PEREZ BENEDI, JENIFER.