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.
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Data Availability Statement
In order to promote future works from this study, all the raw and synthesized data are provided in a dataset repository published in the ECSA Zenodo Community https://doi.org/10.5281/zenodo.12516350 and GitHub [1].
References
Energy consumption of IoT monitoring software architectures in the edge (2024). https://github.com/jenniferperezbenedi/EnergyConsumption_IoTMonitoringEdge. Architectures. https://doi.org/10.5281/zenodo.12516350
jRAPL: A framework for profiling energy consumption of java programs (2024). https://kliu20.github.io/jRAPL/
Aazam, M., Huh, E.N.: Fog computing and smart gateway based communication for cloud of things. In: 2014 International Conference on Future Internet of Things and Cloud, pp. 464–470 (2014). https://doi.org/10.1109/FiCloud.2014.83
Ahvar, E., Orgerie, A.C., Lebre, A.: Estimating energy consumption of cloud, fog, and edge computing infrastructures. IEEE Trans. Sustain. Comput. 7(2), 277–288 (2022)
Al Aidaros, O., Kardjadja, Y., Bouida, Z., Ibnkahla, M.: Energy and time-effective computation offloading for edge computing-enabled IoT networks. In: 2023 IEEE Sensors Applications Symposium (SAS), pp. 1–6 (2023)
Alharbi, H.A., Aldossary, M.: Energy-efficient edge-fog-cloud architecture for IoT-based smart agriculture environment. IEEE Access 9, 110480–110492 (2021)
Amsel, N., Ibrahim, Z., Malik, A., Tomlinson, B.: Toward sustainable software engineering: NIER track. In: 2011 33rd International Conference on Software Engineering (ICSE), pp. 976–979 (2011)
Andrae, A.S.G., Edler, T.: On global electricity usage of communication technology: trends to 2030. Challenges 6(1), 117–157 (2015)
Armbrust, M., et al.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)
Becker, C., et al.: Sustainability design and software: the karlskrona manifesto. In: 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, vol. 2, pp. 467–476 (2015)
Bonomi, F., Milito, R., Zhu, J., Addepalli, S.: Fog computing and its role in the internet of things. In: Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing, MCC 2012, pp. 13–16. Association for Computing Machinery, New York (2012)
Borujeni, A.M., Fathy, M., Mozayani, N.: Developing and evaluating a real time and energy efficient architecture for an internet of health things. In: 2020 4th International Conference on Smart City, Internet of Things and Applications (SCIOT), pp. 106–111 (2020)
Capra, E., Formenti, G., Francalanci, C., Gallazzi, S.: The impact of MIS software on it energy consumption (2010)
Chen, S., Li, Q., Zhang, H., Zhu, F., Xiong, G., Tang, Y.: An IoT edge computing system architecture and its application. In: 2020 IEEE International Conference on Networking, Sensing and Control (ICNSC), pp. 1–7 (2020)
Cui, L., et al.: Joint optimization of energy consumption and latency in mobile edge computing for internet of things. IEEE Internet Things J. 6(3), 4791–4803 (2019)
El-Sayed, H., et al.: Edge of things: The big picture on the integration of edge, IoT and the cloud in a distributed computing environment. IEEE Access 6, 1706–1717 (2018)
Farahani, S.: ZigBee Wireless Networks and Transceivers. Newnes, USA (2008)
The Climate Group: Smart 2020: enabling the low carbon economy in the information age (2008)
Jalali, F., Khodadustan, S., Gray, C., Hinton, K., Suits, F.: Greening IoT with fog: a survey. In: 2017 IEEE International Conference on Edge Computing (EDGE), pp. 25–31 (2017)
LE, H.: Optimizing energy in fog computing architecture based on offloading mechanism for IoT devices. In: 2023 Asia Meeting on Environment and Electrical Engineering (EEE-AM), pp. 1–6 (2023)
Madhura, S.: A review on low power VLSI design models in various circuits. J. Electron. 4, 74–81 (2022)
Mancebo, J., García, F., Calero, C.: A process for analysing the energy efficiency of software. Inf. Softw. Technol. 134, 106560 (2021)
Mebrek, A., Merghem-Boulahia, L., Esseghir, M.: Efficient green solution for a balanced energy consumption and delay in the IoT-fog-cloud computing. In: 2017 IEEE 16th International Symposium on Network Computing and Applications (NCA), pp. 1–4 (2017)
Global System for Mobile Communications Association: The mobile economy 2024. GSMA (2024). https://www.gsma.com/solutions-and-impact/connectivity-for-good/mobile-economy/wp-content/uploads/2024/02/260224-The-Mobile-Economy-2024.pdf
Muniswamaiah, M., Agerwala, T., Tappert, C.C.: Green computing for internet of things. In: 2020 7th IEEE International Conference on Cyber Security and Cloud Computing (CSCloud)/2020 6th IEEE International Conference on Edge Computing and Scalable Cloud (EdgeCom), pp. 182–185 (2020)
Noureddine, A., Rouvoy, R., Seinturier, L.: A review of energy measurement approaches. SIGOPS Oper. Syst. Rev. 47(3), 42–49 (2013)
Runeson, P., Host, M., Rainer, A., Regnell, B.: Case Study Research in Software Engineering: Guidelines and Examples, 1st edn. Wiley Publishing, Hoboken (2012)
Thanh, N.H., Trung Kien, N., Hoa, N.V., Huong, T.T., Wamser, F., Hossfeld, T.: Energy-aware service function chain embedding in edge-cloud environments for IoT applications. IEEE Internet Things J. 8(17), 13465–13486 (2021)
Verde Romero, D.A., Villalvazo Laureano, E., Jiménez Betancourt, R.O., Navarro Álvarez, E.: An open source IoT edge-computing system for monitoring energy consumption in buildings. Results Eng. 21, 101875 (2024)
Wang, C., Zhai, D., Zhang, R., Kaddoum, G., Singh, S.: Energy consumption minimization in dynamic UAV-assisted mobile edge computing networks. In: ICC 2023 - IEEE International Conference on Communications, pp. 4671–4676 (2023)
Webb, M., et al.: Smart 2020: Enabling the low carbon economy in the information age. The Climate Group, London, vol. 1, no. 1, p. 1 (2008)
Wohlin, C., Runeson, P., Hst, M., Ohlsson, M.C., Regnell, B., Wessln, A.: Experimentation in Software Engineering. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-29044-2
Yu, W., Liang, F., He, X., Hatcher, W.G., Lu, C., Lin, J., Yang, X.: A survey on the edge computing for the internet of things. IEEE Access 6, 6900–6919 (2018)
Zhang, J., Chen, B., Zhao, Y., Cheng, X., Hu, F.: Data security and privacy-preserving in edge computing paradigm: survey and open issues. IEEE Access 6, 18209–18237 (2018)
Acknowledgments
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).
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Ochoa, J.S., Pérez, J., García, J., Guamán, D., Cañas, N., Rodriguez-Horcajo, V. (2024). Energy Consumption of IoT Monitoring Software Architectures in the Edge. In: Galster, M., Scandurra, P., Mikkonen, T., Oliveira Antonino, P., Nakagawa, E.Y., Navarro, E. (eds) Software Architecture. ECSA 2024. Lecture Notes in Computer Science, vol 14889. Springer, Cham. https://doi.org/10.1007/978-3-031-70797-1_15
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