{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:20:42Z","timestamp":1781194842684,"version":"3.54.1"},"reference-count":48,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T00:00:00Z","timestamp":1657929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education of the Czech Republic","award":["SP2022\/18"],"award-info":[{"award-number":["SP2022\/18"]}]},{"name":"Ministry of Education of the Czech Republic","award":["SP2022\/34"],"award-info":[{"award-number":["SP2022\/34"]}]},{"name":"Ministry of Education of the Czech Republic","award":["CZ.02.1.01\/0.0\/0.0\/17_049\/0008425"],"award-info":[{"award-number":["CZ.02.1.01\/0.0\/0.0\/17_049\/0008425"]}]},{"name":"European Regional Development Fund","award":["SP2022\/18"],"award-info":[{"award-number":["SP2022\/18"]}]},{"name":"European Regional Development Fund","award":["SP2022\/34"],"award-info":[{"award-number":["SP2022\/34"]}]},{"name":"European Regional Development Fund","award":["CZ.02.1.01\/0.0\/0.0\/17_049\/0008425"],"award-info":[{"award-number":["CZ.02.1.01\/0.0\/0.0\/17_049\/0008425"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In healthcare, there are rapid emergency response systems that necessitate real-time actions where speed and efficiency are critical; this may suffer as a result of cloud latency because of the delay caused by the cloud. Therefore, fog computing is utilized in real-time healthcare applications. There are still limitations in response time, latency, and energy consumption. Thus, a proper fog computing architecture and good task scheduling algorithms should be developed to minimize these limitations. In this study, an Energy-Efficient Internet of Medical Things to Fog Interoperability of Task Scheduling (EEIoMT) framework is proposed. This framework schedules tasks in an efficient way by ensuring that critical tasks are executed in the shortest possible time within their deadline while balancing energy consumption when processing other tasks. In our architecture, Electrocardiogram (ECG) sensors are used to monitor heart health at home in a smart city. ECG sensors send the sensed data continuously to the ESP32 microcontroller through Bluetooth (BLE) for analysis. ESP32 is also linked to the fog scheduler via Wi-Fi to send the results data of the analysis (tasks). The appropriate fog node is carefully selected to execute the task by giving each node a special weight, which is formulated on the basis of the expected amount of energy consumed and latency in executing this task and choosing the node with the lowest weight. Simulations were performed in iFogSim2. The simulation outcomes show that the suggested framework has a superior performance in reducing the usage of energy, latency, and network utilization when weighed against CHTM, LBS, and FNPA models.<\/jats:p>","DOI":"10.3390\/s22145327","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T01:53:22Z","timestamp":1658109202000},"page":"5327","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":94,"title":["A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System"],"prefix":"10.3390","volume":"22","author":[{"given":"Kholoud","family":"Alatoun","sequence":"first","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering, Al-Hussein Bin Talal University, Ma\u2019an 71111, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8647-1393","authenticated-orcid":false,"given":"Khaled","family":"Matrouk","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, Faculty of Engineering, Al-Hussein Bin Talal University, Ma\u2019an 71111, Jordan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9030-8102","authenticated-orcid":false,"given":"Mazin Abed","family":"Mohammed","sequence":"additional","affiliation":[{"name":"College of Computer Science and Information Technology, University of Anbar, Ramadi 31001, Iraq"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7459-2043","authenticated-orcid":false,"given":"Jan","family":"Nedoma","sequence":"additional","affiliation":[{"name":"Department of Telecommunications, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2054-143X","authenticated-orcid":false,"given":"Radek","family":"Martinek","sequence":"additional","affiliation":[{"name":"Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 70800 Ostrava, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Petr","family":"Zmij","sequence":"additional","affiliation":[{"name":"Industrial Engineering\u2014Brose Group, Prumyslovy Park 302, 74221 Koprivnice, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,16]]},"reference":[{"key":"ref_1","first-page":"100355","article-title":"A novel four-tier architecture for delay aware scheduling and load balancing in fog environment","volume":"24","author":"Sharma","year":"2019","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Dubey, H., Monteiro, A., Constant, N., Abtahi, M., Borthakur, D., Mahler, L., Sun, Y., Yang, Q., Akbar, U., and Mankodiya, K. (2017). Fog computing in medical internet-of-things: Architecture, implementation, and applications. Handbook of Large-Scale Distributed Computing in Smart Healthcare, Springer.","DOI":"10.1007\/978-3-319-58280-1_11"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"9206","DOI":"10.1109\/ACCESS.2017.2704100","article-title":"Fog computing in healthcare\u2013A review and discussion","volume":"5","author":"Kraemer","year":"2017","journal-title":"IEEE Access"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1386470","DOI":"10.1155\/2018\/1386470","article-title":"Fog computing-based IoT for health monitoring system","volume":"2018","author":"Paul","year":"2018","journal-title":"J. Sens."},{"key":"ref_5","unstructured":"Cao, Y., Chen, S., Hou, P., and Brown, D. (2015, January 6\u20137). FAST: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation. Proceedings of the 2015 IEEE International Conference on Networking, Architecture and Storage (NAS), Boston, MA, USA."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1080\/17517575.2017.1304579","article-title":"Fog computing job scheduling optimization based on bees swarm","volume":"12","author":"Bitam","year":"2018","journal-title":"Enterp. Inf. Syst."},{"key":"ref_7","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 First Edition of the MCC Workshop on Mobile Cloud Computing, Helsinki, Finland.","DOI":"10.1145\/2342509.2342513"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1109\/MIC.2017.26","article-title":"Challenges and software architecture for fog computing","volume":"21","author":"Hao","year":"2017","journal-title":"IEEE Internet Comput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"101982","DOI":"10.1016\/j.simpat.2019.101982","article-title":"A scheduling algorithm for a fog computing system with bag-of-tasks jobs: Simulation and performance evaluation","volume":"98","author":"Tychalas","year":"2019","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"113292","DOI":"10.1109\/ACCESS.2021.3103725","article-title":"Recent security trends in internet of things: A comprehensive survey","volume":"9","author":"Harbi","year":"2021","journal-title":"IEEE Access"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"115760","DOI":"10.1109\/ACCESS.2019.2924958","article-title":"A novel bio-inspired hybrid algorithm (NBIHA) for efficient resource management in fog computing","volume":"7","author":"Rafique","year":"2019","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"e3770","DOI":"10.1002\/ett.3770","article-title":"An efficient task scheduling approach using moth-flame optimization algorithm for cyber-physical system applications in fog computing","volume":"31","author":"Souri","year":"2020","journal-title":"Trans. Emerg. Telecommun. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1550147717742073","DOI":"10.1177\/1550147717742073","article-title":"A cost- and performance-effective approach for task scheduling based on collaboration between cloud and fog computing","volume":"13","author":"Pham","year":"2017","journal-title":"Int. J. Distrib. Sens. Netw."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"6429","DOI":"10.1007\/s00500-022-07167-9","article-title":"Blockchain multi-objective optimization approach-enabled secure and cost-efficient scheduling for the Internet of Medical Things (IoMT) in fog-cloud system","volume":"26","author":"Lakhan","year":"2022","journal-title":"Soft Comput."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lakhan, A., Mohammed, M.A., Nedoma, J., Martinek, R., Tiwari, P., Vidyarthi, A., Alkhayyat, A., and Wang, W. (2022). Federated-learning based privacy preservation and fraud-enabled blockchain IoMT system for healthcare. IEEE J. Biomed. Health Inform., 2168\u20132194.","DOI":"10.1109\/JBHI.2022.3165945"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Lakhan, A., Mohammed, M.A., Kozlov, S., and Rodrigues, J.J. (2021). Mobile-fog-cloud assisted deep reinforcement learning and blockchain-enable IoMT system for healthcare workflows. Trans. Emerg. Telecommun. Technol., e4363.","DOI":"10.1002\/ett.4363"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Lakhan, A., Mohammed, M.A., Rashid, A.N., Kadry, S., Abdulkareem, K.H., Nedoma, J., Martinek, R., and Razzak, I. (2022). Restricted Boltzmann machine assisted secure serverless edge system for internet of medical things. IEEE J. Biomed. Health Inform.","DOI":"10.1109\/JBHI.2022.3178660"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"9148373","DOI":"10.1155\/2022\/9148373","article-title":"Dimensions of internet of things: Technological taxonomy architecture applications and open challenges\u2014A systematic review","volume":"2022","author":"Kumar","year":"2022","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1708","DOI":"10.1056\/NEJMoa2002032","article-title":"Clinical characteristics of coronavirus disease in China","volume":"382","author":"Guan","year":"2020","journal-title":"N. Engl. J. Med."},{"key":"ref_20","first-page":"639","article-title":"Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up","volume":"80","author":"Terracciano","year":"2021","journal-title":"J. Infect."},{"key":"ref_21","first-page":"3413","article-title":"Low power wearable cardiac activity monitoring device: ECG A review","volume":"8","author":"Jain","year":"2021","journal-title":"Int. Res. J. Eng. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1004","DOI":"10.1016\/j.procs.2015.05.093","article-title":"Stream processing of healthcare sensor data: Studying user traces to identify challenges from a big data perspective","volume":"52","author":"Bonnaire","year":"2015","journal-title":"Procedia Comput. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Nguyen, B.M., Binh, H.T.T., Anh, T.T., and Son, D.B. (2019). Evolutionary algorithms to optimize task scheduling problem for the IoT based bag-of-tasks application in cloud\u2013fog computing environment. Appl. Sci., 9.","DOI":"10.3390\/app9091730"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hassan, S.R., Ahmad, I., Ahmad, S., AlFaify, A., and Shafiq, M. (2020). Remote pain monitoring using fog computing for e-healthcare: An efficient architecture. Sensors, 20.","DOI":"10.3390\/s20226574"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Abdelmoneem, R.M., Benslimane, A., Shaaban, E., Abdelhamid, S., and Ghoneim, S. (2019, January 20\u201324). A cloud-fog based architecture for IoT applications dedicated to healthcare. Proceedings of the ICC 2019\u20132019 IEEE International Conference on Communications (ICC), Shanghai, China.","DOI":"10.1109\/ICC.2019.8761092"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"943","DOI":"10.1007\/s12652-020-02113-9","article-title":"Internet of Health Things (IoHT) for personalized health care using integrated edge-fog-cloud network","volume":"12","author":"Mukherjee","year":"2020","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Mutlag, A.A., Ghani, M.K.A., Mohammed, M.A., Maashi, M.S., Mohd, O., Mostafa, S.A., Abdulkareem, K.H., Marques, G., and D\u00edez, I.D.L.T. (2020). MAFC: Multi-agent fog computing model for healthcare critical tasks management. Sensors, 20.","DOI":"10.3390\/s20071853"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mastoi, Q.-U., Wah, T.Y., Raj, R.G., and Lakhan, A. (2020). A novel cost-efficient framework for critical heartbeat task scheduling using the internet of medical things in a fog cloud system. Sensors, 20.","DOI":"10.3390\/s20020441"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"96189","DOI":"10.1109\/ACCESS.2021.3094033","article-title":"Fog based architecture and load balancing methodology for health monitoring systems","volume":"9","author":"Asghar","year":"2021","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Tun, K.N., and Paing, A.M.M. (2020, January 4\u20135). Resource aware placement of IoT devices in fog computing. Proceedings of the 2020 International Conference on Advanced Information Technologies (ICAIT), Yangon, Myanmar.","DOI":"10.1109\/ICAIT51105.2020.9261787"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Mutlag, A.A., Ghani, M.K.A., Mohammed, M.A., Lakhan, A., Mohd, O., Abdulkareem, K.H., and Garcia-Zapirain, B. (2021). Multi-agent systems in fog\u2013cloud computing for critical healthcare task management model (CHTM) used for ECG monitoring. Sensors, 21.","DOI":"10.3390\/s21206923"},{"key":"ref_32","unstructured":"Ghanavati, S., Abawajy, J.H., and Izadi, D. (2020). An energy aware task scheduling model using ant-mating optimization in fog computing environment. IEEE Trans. Serv. Comput., 1\u201310."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Wen, Y., Zhang, W., and Luo, H. (2012, January 25\u201330). Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones. Proceedings of the 2012 Proceedings IEEE INFOCOM, Orlando, FL, USA.","DOI":"10.1109\/INFCOM.2012.6195685"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"219","DOI":"10.3233\/AIS-210598","article-title":"M2FBalancer: A mist-assisted fog computing-based load balancing strategy for smart cities","volume":"13","author":"Tripathy","year":"2021","journal-title":"J. Ambient Intell. Smart Environ."},{"key":"ref_35","unstructured":"Pochet, Y., and Wolsey, L.A. (2006). Production Planning by Mixed Integer Programming, Springer Science & Business Media."},{"key":"ref_36","unstructured":"Zhou, S., Zhang, Z., and Gu, J. (2011\u20133, January 30). Time-domain ECG signal analysis based on smart-phone. Proceedings of the 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Boston, MA, USA."},{"key":"ref_37","unstructured":"(2022, January 16). Available online: http:\/\/csmbio.csm.jmu.edu\/biology\/danie2jc\/heart.htm."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"886","DOI":"10.4236\/abb.2014.511103","article-title":"Electrocardiogram feature extraction and pattern recognition using a novel windowing algorithm","volume":"5","author":"Umer","year":"2014","journal-title":"Adv. Biosci. Biotechnol."},{"key":"ref_39","unstructured":"Sai, Y.P. (2020, January 22\u201323). A review on arrhythmia classification using ECG signals. Proceedings of the 2020 IEEE International Students\u2019 Conference on Electrical, Electronics and Computer Science (SCEECS), Bhopal, India."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Triantaphyllou, E. (2000). Multi-criteria decision-making methods. Multi-Criteria Decision-Making Methods: A Comparative Study, Springer.","DOI":"10.1007\/978-1-4757-3157-6"},{"key":"ref_41","unstructured":"MacCrimmon, K.R. (1968). Decisionmaking among Multiple-Attribute Alternatives: A Survey and Consolidated Approach, Rand Corp."},{"key":"ref_42","unstructured":"(2022, January 16). Available online: http:\/\/archive.ics.uci.edu\/ml\/datasets\/arrhythmia."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"100251","DOI":"10.1016\/j.iot.2020.100251","article-title":"An IoT patient monitoring based on fog computing and data mining: Cardiac arrhythmia usecase","volume":"11","author":"Moghadas","year":"2020","journal-title":"Internet Things"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Sidikova, M., Martinek, R., Kawala-Sterniuk, A., Ladrova, M., Jaros, R., Danys, L., and Simonik, P. (2020). Vital sign monitoring in car seats based on electrocardiography, ballistocardiography and seismocardiography: A review. Sensors, 20.","DOI":"10.3390\/s20195699"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Lakhan, A., Mohammed, M., Rashid, A., Kadry, S., Panityakul, T., Abdulkareem, K., and Thinnukool, O. (2021). Smart-contract aware ethereum and client-fog-cloud healthcare system. Sensors, 21.","DOI":"10.3390\/s21124093"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1883122","DOI":"10.1080\/17517575.2021.1883122","article-title":"Deep neural network-based application partitioning and scheduling for hospitals and medical enterprises using IoT assisted mobile fog cloud","volume":"16","author":"Lakhan","year":"2022","journal-title":"Enterp. Inf. Syst."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Zhang, T., Wang, S., Li, G., Liu, F., Zhu, G., and Wang, R. (2021). Accelerating edge intelligence via integrated sensing and communication. arXiv.","DOI":"10.1109\/ICC45855.2022.9839016"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Gong, A., Zhang, T., Chen, H., and Zhang, Y. (2020, January 7\u201311). Age-of-information-based scheduling in multiuser uplinks with stochastic arrivals: A POMDP approach. Proceedings of the GLOBECOM 2020\u20132020 IEEE Global Communications Conference, Taipei, Taiwan.","DOI":"10.1109\/GLOBECOM42002.2020.9348022"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/14\/5327\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:52:06Z","timestamp":1760140326000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/14\/5327"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,16]]},"references-count":48,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["s22145327"],"URL":"https:\/\/doi.org\/10.3390\/s22145327","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,16]]}}}