Yew, Hoe Tung (2017) Network selection mechanism for telecardiology application in high speed environment. PhD thesis, Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering.
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Abstract
The existing network selection schemes biased either to cost or Quality of Service (QoS) are not efficient enough for telecardiology application in high traveling speed environment. Selection of the candidate network that is fulfilling the telecardiology service requirements as well as user preference is a challenging issue. This is because the preference of telecardiology user might change based on the patient health condition. This research proposed a novel Telecardiology-based Handover Decision Making (THODM) mechanism that consists of three closely integrated algorithms: Adaptive Service Adjustment (ASA), Dwelling Time Prediction (DTP) and Patient Health Condition-based Network Evaluation (PHCNE). The ASA algorithm guarantees the quality of telecardiology service when none of the available networks fulfils the service requirements. The DTP algorithm minimizes the probability of handover failure and unnecessary handover to Wireless Local Area Network (WLAN), while optimizing the connection time with WLAN in high traveling speed environment. The PHCNE algorithm evaluates the quality of available networks and selects the best network based on the telecardiology services requirement and the patient health condition. Simulation results show that the proposed THODM mechanism reduced the number of handover failures and unnecessary handovers up to 80.0% and 97.7%, respectively, compared with existing works. The cost of THODM mechanism is 20% and 85.3% lower than the Speed Threshold-based Handover (STHO) and Bandwidth-based Handover (BWHO) schemes, respectively. In terms of throughput, the proposed scheme is up to 75% higher than the STHO scheme and 370% greater than the BWHO scheme. For telecardiology application in high traveling speed environment, the proposed THODM mechanism has better performance than the existing network selection schemes.
Item Type: | Thesis (PhD) |
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Additional Information: | Thesis (Doktor Falsafah (Kejuruteraan Bioperubatan)) - Universiti Teknologi Malaysia, 2017; Supervisors : Prof. Dr. Ing. Eko Supriyanto, Dr. Muhammad Haikal Sastria, Dr. Hau Yuan Wen |
Subjects: | Q Science > QH Natural history |
Divisions: | Biosciences and Medical Engineering |
ID Code: | 79592 |
Deposited By: | Widya Wahid |
Deposited On: | 31 Oct 2018 13:00 |
Last Modified: | 31 Oct 2018 13:00 |
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