{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:32:44Z","timestamp":1760239964080,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,2,2]],"date-time":"2019-02-02T00:00:00Z","timestamp":1549065600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["PROCAD 2966\/2014"],"award-info":[{"award-number":["PROCAD 2966\/2014"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["140653\/2017-1","313012\/2017-2"],"award-info":[{"award-number":["140653\/2017-1","313012\/2017-2"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001807","name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","doi-asserted-by":"publisher","award":["2013\/08293-7"],"award-info":[{"award-number":["2013\/08293-7"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>In this article, we work toward the answer to the question \u201cis it worth processing a data stream on the device that collected it or should we send it somewhere else?\u201d. As it is often the case in computer science, the response is \u201cit depends\u201d. To find out the cases where it is more profitable to stay in the device (which is part of the fog) or to go to a different one (for example, a device in the cloud), we propose two models that intend to help the user evaluate the cost of performing a certain computation on the fog or sending all the data to be handled by the cloud. In our generic mathematical model, the user can define a cost type (e.g., number of instructions, execution time, energy consumption) and plug in values to analyze test cases. As filters have a very important role in the future of the Internet of Things and can be implemented as lightweight programs capable of running on resource-constrained devices, this kind of procedure is the main focus of our study. Furthermore, our visual model guides the user in their decision by aiding the visualization of the proposed linear equations and their slope, which allows them to find if either fog or cloud computing is more profitable for their specific scenario. We validated our models by analyzing four benchmark instances (two applications using two different sets of parameters each) being executed on five datasets. We use execution time and energy consumption as the cost types for this investigation.<\/jats:p>","DOI":"10.3390\/fi11020034","type":"journal-article","created":{"date-parts":[[2019,2,5]],"date-time":"2019-02-05T11:31:07Z","timestamp":1549366267000},"page":"34","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Fog vs. Cloud Computing: Should I Stay or Should I Go?"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2670-7197","authenticated-orcid":false,"given":"Fl\u00e1via","family":"Pisani","sequence":"first","affiliation":[{"name":"Institute of Computing, University of Campinas, Campinas 13083-852, Brazil"}]},{"given":"Vanderson","family":"Martins do Rosario","sequence":"additional","affiliation":[{"name":"Institute of Computing, University of Campinas, Campinas 13083-852, Brazil"}]},{"given":"Edson","family":"Borin","sequence":"additional","affiliation":[{"name":"Institute of Computing, University of Campinas, Campinas 13083-852, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,2]]},"reference":[{"key":"ref_1","unstructured":"Lucero, S. (2016). IoT Platforms: Enabling the Internet of Things, IHS Technology. Technical Report."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012, January 17). Fog Computing and Its Role in the Internet of Things. Proceedings of the 1st MCC Workshop on Mobile Cloud Computing, Helsinki, Finland.","DOI":"10.1145\/2342509.2342513"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1145\/2677046.2677052","article-title":"Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing","volume":"44","author":"Vaquero","year":"2014","journal-title":"ACM SIGCOMM Comput. Commun. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Li, Z., Wang, C., and Xu, R. (2001, January 16\u201317). Computation Offloading to Save Energy on Handheld Devices: A Partition Scheme. Proceedings of the 2001 International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, Atlanta, GA, USA.","DOI":"10.1145\/502217.502257"},{"key":"ref_5","unstructured":"Li, Z., Wang, C., and Xu, R. (2001, January 15\u201319). Task Allocation for Distributed Multimedia Processing on Wirelessly Networked Handheld Devices. Proceedings of the 16th International Parallel and Distributed Processing Symposium, Ft. Lauderdale, FL, USA."},{"key":"ref_6","unstructured":"Li, Z., and Xu, R. (2002, January 25). Energy Impact of Secure Computation on a Handheld Device. Proceedings of the 2002 IEEE International Workshop on Workload Characterization, Austin, TX, USA."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Kremer, U., Hicks, J., and Rehg, J. (2003). A Compilation Framework for Power and Energy Management on Mobile Computers. International Workshop on Languages and Compilers for Parallel Computing, Springer.","DOI":"10.1007\/3-540-35767-X_8"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Rong, P., and Pedram, M. (2003, January 2\u20136). Extending the Lifetime of a Network of Battery-Powered Mobile Devices by Remote Processing: A Markovian Decision-based Approach. Proceedings of the 2003 Design Automation Conference, Anaheim, CA, USA.","DOI":"10.1145\/775832.776060"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1109\/TPDS.2004.47","article-title":"Studying Energy Trade Offs in Offloading Computation\/Compilation in Java-Enabled Mobile Devices","volume":"15","author":"Chen","year":"2004","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_10","unstructured":"O\u2019Hara, K.J., Nathuji, R., Raj, H., Schwan, K., and Balch, T. (2006, January 15\u201319). AutoPower: Toward Energy-Aware Software Systems for Distributed Mobile Robots. Proceedings of the 2006 IEEE International Conference on Robotics and Automation, Orlando, FL, USA."},{"key":"ref_11","unstructured":"Xian, C., Lu, Y.-H., and Li, Z. (2007, January 5\u20137). Adaptive Computation Offloading for Energy Conservation on Battery-Powered Systems. Proceedings of the 2007 International Conference on Parallel and Distributed Systems, Hsinchu, Taiwan."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Hong, Y.-J., Kumar, K., and Lu, Y.-H. (2009, January 24\u201327). Energy Efficient Content-Based Image Retrieval for Mobile Systems. Proceedings of the IEEE International Symposium on Circuits and Systems, Taipei, Taiwan.","DOI":"10.1109\/ISCAS.2009.5118095"},{"key":"ref_13","unstructured":"Gu, X., Nahrstedt, K., Messer, A., Greenberg, I., and Milojicic, D. (2003, January 26). Adaptive Offloading Inference for Delivering Applications in Pervasive Computing Environments. Proceedings of the First IEEE International Conference on Pervasive Computing and Communications, Fort Worth, TX, USA."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Gurun, S., Krintz, C., and Wolski, R. (2004, January 6\u20139). NWSLite: A Light-Weight Prediction Utility for Mobile Devices. Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services, Boston, MA, USA.","DOI":"10.1145\/990064.990068"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Wang, C., and Li, Z. (2004, January 9\u201311). Parametric Analysis for Adaptive Computation Offloading. Proceedings of the 2004 Conference on Programming Language Design and Implementation, Washington, DC, USA.","DOI":"10.1145\/996841.996857"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Wolski, R., Gurun, S., Krintz, C., and Nurmi, D. (2008, January 14\u201318). Using Bandwidth Data To Make Computation Offloading Decisions. Proceedings of the 2008 IEEE International Symposium on Parallel and Distributed Processing, Miami, FL, USA.","DOI":"10.1109\/IPDPS.2008.4536215"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Nimmagadda, Y., Kumar, K., Lu, Y.-H., and Lee, C.S.G. (2010, January 18\u201322). Real-time Moving Object Recognition and Tracking Using Computation Offloading. Proceedings of the 2010 IEEE\/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan.","DOI":"10.1109\/IROS.2010.5650303"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Jayaraman, P.P., Gomes, J.B., Nguyen, H.L., Abdallah, Z.S., Krishnaswamy, S., and Zaslavsky, A. (2014). CARDAP: A Scalable Energy-Efficient Context Aware Distributed Mobile Data Analytics Platform for the Fog. East European Conference on Advances in Databases and Information Systems, Springer.","DOI":"10.1007\/978-3-319-10933-6_15"},{"key":"ref_19","first-page":"1171","article-title":"Optimal Workload Allocation in Fog-Cloud Computing Toward Balanced Delay and Power Consumption","volume":"3","author":"Deng","year":"2016","journal-title":"IEEE Internet Things J."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Xu, J., and Ren, S. (2016, January 4\u20138). Online Learning for Offloading and Autoscaling in Renewable-Powered Mobile Edge Computing. Proceedings of the 2016 IEEE Global Communications Conference, Washington, DC, USA.","DOI":"10.1109\/GLOCOM.2016.7842069"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1109\/JIOT.2017.2780236","article-title":"Multiobjective Optimization for Computation Offloading in Fog Computing","volume":"5","author":"Liu","year":"2018","journal-title":"IEEE Internet Things J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1145\/1498765.1498785","article-title":"Roofline: An Insightful Visual Performance Model for Multicore Architectures","volume":"52","author":"Williams","year":"2009","journal-title":"Commun. ACM"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Pisani, F., Brunetta, J.R., do Rosario, V.M., and Borin, E. (2017, January 17\u201320). Beyond the Fog: Bringing Cross-Platform Code Execution to Constrained IoT Devices. Proceedings of the 29th International Symposium on Computer Architecture and High Performance Computing, Campinas, Brazil.","DOI":"10.1109\/SBAC-PAD.2017.10"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Do Rosario, V.M., Pisani, F., Gomes, A.R., and Borin, E. (2018, January 21\u201325). Fog-Assisted Translation: Towards Efficient Software Emulation on Heterogeneous IoT Devices. Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium Workshops, Vancouver, BC, Canada.","DOI":"10.1109\/IPDPSW.2018.00196"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1080\/01621459.1986.10478363","article-title":"Performance of Some Resistant Rules for Outlier Labeling","volume":"81","author":"Hoaglin","year":"1986","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_26","unstructured":"National Centers for Environmental Information (2018, August 23). Climate Data Online: Dataset Discovery, Available online: https:\/\/www.ncdc.noaa.gov\/cdo-web\/datasets#LCD."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.ifacol.2018.07.147","article-title":"Impact of Edge Computing Paradigm on Energy Consumption in IoT","volume":"51","author":"Mocnej","year":"2018","journal-title":"IFAC-PapersOnLine"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.jnca.2018.07.016","article-title":"EMPIOT: An Energy Measurement Platform for Wireless IoT Devices","volume":"121","author":"Dezfouli","year":"2018","journal-title":"J. Netw. Comput. Appl."}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/11\/2\/34\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:30:43Z","timestamp":1760185843000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/11\/2\/34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,2]]},"references-count":28,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2019,2]]}},"alternative-id":["fi11020034"],"URL":"https:\/\/doi.org\/10.3390\/fi11020034","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2019,2,2]]}}}