Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring
In modern healthcare monitoring, wearable sensors play a crucial role in collecting patient data, especially for individuals with disabilities. However, analyzing this data presents significant challenges, such as high energy consumption, latency, and task allocation inefficiencies. Healthcare monit...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10753614/ |
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| author | Tabinda Salam Waheed Ur Rehman Ikram Ud Din Ahmad Almogren Mubarak Mohammed Al Ezzi Sufyan Kainat Muhammad Yasar Khan Ayman Altameem |
| author_facet | Tabinda Salam Waheed Ur Rehman Ikram Ud Din Ahmad Almogren Mubarak Mohammed Al Ezzi Sufyan Kainat Muhammad Yasar Khan Ayman Altameem |
| author_sort | Tabinda Salam |
| collection | DOAJ |
| description | In modern healthcare monitoring, wearable sensors play a crucial role in collecting patient data, especially for individuals with disabilities. However, analyzing this data presents significant challenges, such as high energy consumption, latency, and task allocation inefficiencies. Healthcare monitoring systems face computational demands due to the processing of data from wearable sensors, which are constrained by limited resources and often affected by connectivity issues for data offloading. To address these challenges, this paper proposes a Cooperative Dew-Computing for Healthcare (CCH) framework, which integrates wearable sensors and dew devices within a cloud-fog-dew infrastructure. The CCH framework ensures efficient task distribution and computational offloading by selecting appropriate anchor devices using probabilistic and fuzzy logic techniques, taking into account energy efficiency and computational capabilities. Cooperative communication among anchor devices enables efficient task management, allowing tasks to be offloaded or distributed among multiple anchor devices. The proposed framework enhances healthcare monitoring systems by improving computational efficiency, optimizing resource utilization, and mitigating connectivity issues. This is particularly beneficial for disabled patients who rely on continuous monitoring and efficient data processing. Our evaluations demonstrate that the CCH framework outperforms existing techniques in terms of energy efficiency, latency, and task delay reduction, underscoring its effectiveness in providing timely and efficient data processing for healthcare monitoring systems. |
| format | Article |
| id | doaj-art-ab83bc8d91534e4e8bd6fc60f29c75bb |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-ab83bc8d91534e4e8bd6fc60f29c75bb2024-11-22T00:01:23ZengIEEEIEEE Access2169-35362024-01-011217004117005610.1109/ACCESS.2024.349891110753614Cooperative Dew Computing for Computational Offloading in Healthcare MonitoringTabinda Salam0https://orcid.org/0000-0002-7934-3385Waheed Ur Rehman1Ikram Ud Din2https://orcid.org/0000-0001-8896-547XAhmad Almogren3https://orcid.org/0000-0002-8253-9709Mubarak Mohammed Al Ezzi Sufyan4https://orcid.org/0000-0002-0443-6819 Kainat5Muhammad Yasar Khan6https://orcid.org/0000-0002-9449-961XAyman Altameem7https://orcid.org/0000-0002-9946-423XDepartment of Computer Science, Shaheed Benazir Bhutto Women University (SBBWU), Peshawar, PakistanDepartment of Computer Science, University of Peshawar, Peshawar, PakistanDepartment of Information Technology, The University of Haripur, Haripur, PakistanDepartment of Computer Science, Chair of Cyber Security, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi ArabiaDepartment of Computer Science, University of Peshawar, Peshawar, PakistanDepartment of Computer Science, Shaheed Benazir Bhutto Women University (SBBWU), Peshawar, PakistanSFI-Funded E-Governance Unit, Insight Centre for Data Analytics, University of Galway, Galway, IrelandDepartment of Natural and Engineering Sciences, College of Applied Studies and Community Services, King Saud University, Riyadh, Saudi ArabiaIn modern healthcare monitoring, wearable sensors play a crucial role in collecting patient data, especially for individuals with disabilities. However, analyzing this data presents significant challenges, such as high energy consumption, latency, and task allocation inefficiencies. Healthcare monitoring systems face computational demands due to the processing of data from wearable sensors, which are constrained by limited resources and often affected by connectivity issues for data offloading. To address these challenges, this paper proposes a Cooperative Dew-Computing for Healthcare (CCH) framework, which integrates wearable sensors and dew devices within a cloud-fog-dew infrastructure. The CCH framework ensures efficient task distribution and computational offloading by selecting appropriate anchor devices using probabilistic and fuzzy logic techniques, taking into account energy efficiency and computational capabilities. Cooperative communication among anchor devices enables efficient task management, allowing tasks to be offloaded or distributed among multiple anchor devices. The proposed framework enhances healthcare monitoring systems by improving computational efficiency, optimizing resource utilization, and mitigating connectivity issues. This is particularly beneficial for disabled patients who rely on continuous monitoring and efficient data processing. Our evaluations demonstrate that the CCH framework outperforms existing techniques in terms of energy efficiency, latency, and task delay reduction, underscoring its effectiveness in providing timely and efficient data processing for healthcare monitoring systems.https://ieeexplore.ieee.org/document/10753614/Dew computingcooperative communicationhealthcare monitoringdisabilitycomputational offloadingInternet of Medical Things |
| spellingShingle | Tabinda Salam Waheed Ur Rehman Ikram Ud Din Ahmad Almogren Mubarak Mohammed Al Ezzi Sufyan Kainat Muhammad Yasar Khan Ayman Altameem Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring IEEE Access Dew computing cooperative communication healthcare monitoring disability computational offloading Internet of Medical Things |
| title | Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring |
| title_full | Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring |
| title_fullStr | Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring |
| title_full_unstemmed | Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring |
| title_short | Cooperative Dew Computing for Computational Offloading in Healthcare Monitoring |
| title_sort | cooperative dew computing for computational offloading in healthcare monitoring |
| topic | Dew computing cooperative communication healthcare monitoring disability computational offloading Internet of Medical Things |
| url | https://ieeexplore.ieee.org/document/10753614/ |
| work_keys_str_mv | AT tabindasalam cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT waheedurrehman cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT ikramuddin cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT ahmadalmogren cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT mubarakmohammedalezzisufyan cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT kainat cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT muhammadyasarkhan cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring AT aymanaltameem cooperativedewcomputingforcomputationaloffloadinginhealthcaremonitoring |