Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/217399
Title: Buffer-Aware Resource Allocation Scheme With Energy Efficiency and QoS Effectiveness in Wireless Body Area Networks
Authors: Zhiqiang Liu;Bin Liu;Chang Wen Chen
Year: 2017
Publisher: IEEE
Abstract: Wireless body area network (WBAN) has attracted more and more attention to automatically and intelligently sense the health data of one person for supporting various health applications in smart cities. In the energy-constrained and heterogeneous WBAN system, there are three main issues: 1) the dynamic link characteristics due to the time-varying postures and environments; 2) the high energy efficiency requirement with considering the limited sensor battery; and 3) the high quality-of-service (QoS) requirement due to the importance of health data. To provide long service with high quality, the resource allocation scheme becomes indispensable with considering all these issues. In this paper, a mix-cost parameter is designed to evaluate the energy efficiency and QoS effectiveness, and a resource allocation problem is formulated to minimize the total mix-cost with optimizing the transmission rate, the transmission power, and the allocated time slots for each sensor. Then, a buffer-aware sensor evaluation method with low complexity is introduced to the resource allocation scheme to evaluate the sensor state in real time and then decide when applying for the resource re-allocation by the hub for further improving both the short-term and the long-term QoS performance. Finally, a greedy sub-optimal resource allocation scheme is designed to reduce the time complexity of the resource allocation scheme. Simulation results are presented to demonstrate the effectiveness of the proposed optimal buffer-aware resource allocation scheme as well as the greedy sub-optimal resource allocation scheme with low complexity.
Description: 
URI: http://localhost/handle/Hannan/217399
volume: 5
More Information: 20763,
20776
Appears in Collections:2017

Files in This Item:
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8055547.pdf1.74 MBAdobe PDF
Title: Buffer-Aware Resource Allocation Scheme With Energy Efficiency and QoS Effectiveness in Wireless Body Area Networks
Authors: Zhiqiang Liu;Bin Liu;Chang Wen Chen
Year: 2017
Publisher: IEEE
Abstract: Wireless body area network (WBAN) has attracted more and more attention to automatically and intelligently sense the health data of one person for supporting various health applications in smart cities. In the energy-constrained and heterogeneous WBAN system, there are three main issues: 1) the dynamic link characteristics due to the time-varying postures and environments; 2) the high energy efficiency requirement with considering the limited sensor battery; and 3) the high quality-of-service (QoS) requirement due to the importance of health data. To provide long service with high quality, the resource allocation scheme becomes indispensable with considering all these issues. In this paper, a mix-cost parameter is designed to evaluate the energy efficiency and QoS effectiveness, and a resource allocation problem is formulated to minimize the total mix-cost with optimizing the transmission rate, the transmission power, and the allocated time slots for each sensor. Then, a buffer-aware sensor evaluation method with low complexity is introduced to the resource allocation scheme to evaluate the sensor state in real time and then decide when applying for the resource re-allocation by the hub for further improving both the short-term and the long-term QoS performance. Finally, a greedy sub-optimal resource allocation scheme is designed to reduce the time complexity of the resource allocation scheme. Simulation results are presented to demonstrate the effectiveness of the proposed optimal buffer-aware resource allocation scheme as well as the greedy sub-optimal resource allocation scheme with low complexity.
Description: 
URI: http://localhost/handle/Hannan/217399
volume: 5
More Information: 20763,
20776
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8055547.pdf1.74 MBAdobe PDF
Title: Buffer-Aware Resource Allocation Scheme With Energy Efficiency and QoS Effectiveness in Wireless Body Area Networks
Authors: Zhiqiang Liu;Bin Liu;Chang Wen Chen
Year: 2017
Publisher: IEEE
Abstract: Wireless body area network (WBAN) has attracted more and more attention to automatically and intelligently sense the health data of one person for supporting various health applications in smart cities. In the energy-constrained and heterogeneous WBAN system, there are three main issues: 1) the dynamic link characteristics due to the time-varying postures and environments; 2) the high energy efficiency requirement with considering the limited sensor battery; and 3) the high quality-of-service (QoS) requirement due to the importance of health data. To provide long service with high quality, the resource allocation scheme becomes indispensable with considering all these issues. In this paper, a mix-cost parameter is designed to evaluate the energy efficiency and QoS effectiveness, and a resource allocation problem is formulated to minimize the total mix-cost with optimizing the transmission rate, the transmission power, and the allocated time slots for each sensor. Then, a buffer-aware sensor evaluation method with low complexity is introduced to the resource allocation scheme to evaluate the sensor state in real time and then decide when applying for the resource re-allocation by the hub for further improving both the short-term and the long-term QoS performance. Finally, a greedy sub-optimal resource allocation scheme is designed to reduce the time complexity of the resource allocation scheme. Simulation results are presented to demonstrate the effectiveness of the proposed optimal buffer-aware resource allocation scheme as well as the greedy sub-optimal resource allocation scheme with low complexity.
Description: 
URI: http://localhost/handle/Hannan/217399
volume: 5
More Information: 20763,
20776
Appears in Collections:2017

Files in This Item:
File SizeFormat 
8055547.pdf1.74 MBAdobe PDF