Abstract
Digital services - applications that often span the entire computing continuum - have become an essential part of our daily lives, but they can have a significant energy cost, raising sustainability concerns. The computing continuum features multiple distributed layers (edge, fog, and cloud) with specific computing infrastructure and scheduling decisions at each layer, which impact the overall quality of service and energy consumption of digital services. Measuring the energy consumption of such applications is challenging due to the distributed nature of the system and the application. As such, simulation techniques are promising solutions to estimate energy consumption, and several simulators are available for modeling the cloud and fog computing environment.
In this paper, we investigate iFogSim’s effectiveness in analyzing the end-to-end energy consumption of applications in the computing continuum through two case studies. We design different scenarios for each case study to map application modules to devices along the continuum, including the Edge-Cloud collaboration architecture, and compare them with the two placement policies native to iFogSim: Cloud-only and Edge-ward policies. We observe iFogSim’s limitations in reporting energy consumption, and improve its ability to report energy consumption from an application’s perspective; this enables additional insight into an application’s energy consumption, thus enhancing the usability of iFogSim in evaluating the end-to-end energy consumption of digital services.
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References
Aghapour, E., Sapra, D., Pimentel, A., Pathania, A.: CPU-GPU layer-switched low latency CNN inference. In: 2022 25th Euromicro Conference on Digital System Design (DSD), pp. 324–331. IEEE (2022)
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 (2019)
Alam, M.S., Jabin, S.J., Alam, A., Hossain, M.I.: Comparative analysis of cloud and fog environment based on network usage and cost of execution using iFogSim. In: DASA 2021, pp. 132–137. IEEE, (2021)
Arora, U., Singh, N.: IoT application modules placement in heterogeneous fog-cloud infrastructure. Int. J. Inf. Technol. 13(5), 1975–1982 (2021)
Awaisi, K.S.: Towards a fog enabled efficient car parking architecture. IEEE Access 7, 159100–159111 (2019)
Brogi, A., Forti, S., Guerrero, C., Lera, I.: How to place your apps in the fog: state of the art and open challenges. Softw. Pract. Experience 50(5), 719–740 (2020)
Byrne, J., et al.: A review of cloud computing simulation platforms and related environments. In: CLOSER, pp. 651–663 (2017)
Calheiros, R.N., Ranjan, R., Beloglazov, A., De Rose, C.A., Buyya, R.: CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw. Pract. Experience 41(1), 23–50 (2011)
Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of things (IoT): a vision, architectural elements, and future directions. Futur. Gener. Comput. Syst. 29(7), 1645–1660 (2013)
Gupta, H., Vahid Dastjerdi, A., Ghosh, S.K., Buyya, R.: iFogSim: a toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Softw. Pract. Experience 47(9), 1275–1296 (2017)
Hassan, S.R., Ahmad, I., Ahmad, S., Alfaify, A., Shafiq, M.: Remote pain monitoring using fog computing for e-healthcare: an efficient architecture. Sensors 20(22), 6574 (2020)
Jansen, M., Al-Dulaimy, A., Papadopoulos, A. V., Trivedi, A., Iosup, A.: The SPEC-RG reference architecture for the compute continuum. In: The 23rd IEEE/ACM CCGRID 2023, India, May 1–4, 2023 (2023)
Jansen, M., Wagner, L., Trivedi, A., Iosup, A.: Continuum: automate infrastructure deployment and benchmarking in the compute continuum. In: FastContinuum 2023, in conjuncrtion with ICPE, Portugal (2023)
Jones, N., et al.: How to stop data centres from gobbling up the world’s electricity. Nature 561(7722), 163–166 (2018)
Kliazovich, D., Bouvry, P., Khan, S.U.: GreenCloud: a packet-level simulator of energy-aware cloud computing data centers. J. Supercomput. 62, 1263–1283 (2012)
Mahmud, R., Buyya, R.: Modelling and simulation of fog and edge computing environments using iFogSim toolkit. In: Fog and Edge Computing: Principles and Paradigms, pp. 1–35 (2019)
Mastenbroek, F., et al.: OpenDC 2.0: convenient modeling and simulation of emerging technologies in cloud datacenters. In: 2021 IEEE/ACM CCGrid, pp. 455–464, USA, May 2021. IEEE Computer Society (2021)
Oma, R., Nakamura, S., Enokido, T., Takizawa, M.: A tree-based model of energy-efficient fog computing systems in IoT. In: Barolli, L., Javaid, N., Ikeda, M., Takizawa, M. (eds.) CISIS 2018. AISC, vol. 772, pp. 991–1001. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-93659-8_92
Pan, J., McElhannon, J.: Future edge cloud and edge computing for internet of things applications. IEEE Internet Things J. 5(1), 439–449 (2017)
Preist, C., Schien, D., Shabajee, P., Wood, S., Hodgson, C.: Analyzing end-to-end energy consumption for digital services. Computer 47(5), 92–95 (2014)
Sarkar, I., Kumar, S.: Fog computing based intelligent security surveillance using PTZ controller camera. In: 10th International Conference on ICCCNT, pp. 1–5. IEEE (2019)
Shrestha, S., Shakya, S.: A comparative performance analysis of fog-based smart surveillance system. TCSST J. 2(02), 78–88 (2020)
Sonmez, C., Ozgovde, A., Ersoy, C.: EdgeCloudSim: an environment for performance evaluation of edge computing systems. Trans. Emerg. Telecommun. Technol. 29(11), e3493 (2018)
Tang, W., Li, S., Rafique, W., Dou, W., Yu, S.: An offloading approach in fog computing environment. In: 2018 IEEE SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI, pp. 857–864. IEEE (2018)
Vadde, U., Kompalli, V.S.: Energy efficient service placement in fog computing. PeerJ Comput. Sci. 8, e1035 (2022)
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Baneshi, S., Varbanescu, AL., Pathania, A., Akesson, B., Pimentel, A. (2023). Estimating the Energy Consumption of Applications in the Computing Continuum with iFogSim. In: Bienz, A., Weiland, M., Baboulin, M., Kruse, C. (eds) High Performance Computing. ISC High Performance 2023. Lecture Notes in Computer Science, vol 13999. Springer, Cham. https://doi.org/10.1007/978-3-031-40843-4_18
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