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      Design of a Prediction based MAC Scheme for Wireless Body Area Networks

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      https://www.riss.kr/link?id=A109080011

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      다국어 초록 (Multilingual Abstract)

      To provide the effective monitoring in health care field, the access of communication medium to transmitting nodes should be according to the medical conditions of patients. For more reliable and efficient use of WBANs the medium access needs to be assigned to data transmissions before the occurrence of emergency conditions, so that timely treatments can be triggered for medically critical patients. The existing MAC schemes are able to prioritize the emergency data for transmissions but, after the occurrence of emergency events and the prioritization process of data transmissions itself incurs delay. The delays in transmissions of medically critical patient’s data can be disastrous. Even the conventional MAC schemes of IEEE 802.15.4 and 802.15.6 protocols are not able to transmit the medical data with dynamic and predicted priorities. This research study focused on the prioritization of the data transmissions of the patients based on the predicted conditions of patients in dynamic manner. Therefore, the data of patients is analyzed to predict the emergency events and then prioritized to transmit the data of critical patients to medical concerns in time. The design of proposed MAC scheme is based on Time Division Multiple Access which makes it a congestion free MAC scheme. The proposed scheme is tested in simulation environment. The results showed that the presented MAC scheme predicted the patient’s condition with approximately 87% of accuracy and prioritized the data streams accordingly in dynamic manners. The proposed scheme efficiently prioritized the patient’s data transmissions when tested on one type of dataset and some factors are assumed ideal or null too.
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      To provide the effective monitoring in health care field, the access of communication medium to transmitting nodes should be according to the medical conditions of patients. For more reliable and efficient use of WBANs the medium access needs to be as...

      To provide the effective monitoring in health care field, the access of communication medium to transmitting nodes should be according to the medical conditions of patients. For more reliable and efficient use of WBANs the medium access needs to be assigned to data transmissions before the occurrence of emergency conditions, so that timely treatments can be triggered for medically critical patients. The existing MAC schemes are able to prioritize the emergency data for transmissions but, after the occurrence of emergency events and the prioritization process of data transmissions itself incurs delay. The delays in transmissions of medically critical patient’s data can be disastrous. Even the conventional MAC schemes of IEEE 802.15.4 and 802.15.6 protocols are not able to transmit the medical data with dynamic and predicted priorities. This research study focused on the prioritization of the data transmissions of the patients based on the predicted conditions of patients in dynamic manner. Therefore, the data of patients is analyzed to predict the emergency events and then prioritized to transmit the data of critical patients to medical concerns in time. The design of proposed MAC scheme is based on Time Division Multiple Access which makes it a congestion free MAC scheme. The proposed scheme is tested in simulation environment. The results showed that the presented MAC scheme predicted the patient’s condition with approximately 87% of accuracy and prioritized the data streams accordingly in dynamic manners. The proposed scheme efficiently prioritized the patient’s data transmissions when tested on one type of dataset and some factors are assumed ideal or null too.

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      목차 (Table of Contents)

      • Abstract
      • I. INTRODUCTION
      • II. RELATED WORK
      • III. RESEARCH METHODOLOGY
      • A. Experimental Setup
      • Abstract
      • I. INTRODUCTION
      • II. RELATED WORK
      • III. RESEARCH METHODOLOGY
      • A. Experimental Setup
      • IV. RESULTS AND DISCUSSION
      • A. Results for Deviation Measures
      • B. Research Comparison
      • V. CONCLUSION
      • REFERENCES
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