An adaptive QoS computation for medical data processing in intelligent healthcare applications

Sodhro, Ali Hassan1,2; Malokani, Abdul Sattar3; Sodhro, Gul Hassan4; Muzammal, Muhammad5; Zongwei, Luo6

2020

10.1007/s00521-018-3931-1

Neural Computing and Applications   影响因子和分区

14333058

1433-3058

Efficient computation of quality of service (QoS) during medical data processing through intelligent measurement methods is one of the mandatory requirements of the medial healthcare world. However, emergency medical services often involve transmission of critical data, thus having stringent requirements for network quality of service (QoS). This paper contributes in three distinct ways. First, it proposes the novel adaptive QoS computation algorithm (AQCA) for fair and efficient monitoring of the performance indicators, i.e., transmission power, duty cycle and route selection during medical data processing in healthcare applications. Second, framework of QoS computation in medical applications is proposed at physical, medium access control (MAC) and network layers. Third, QoS computation mechanism with proposed AQCA and quality of experience (QoE) is developed. Besides, proper examination of QoS computation for medical healthcare application is evaluated with 4–10 inches large-screen user terminal (UT) devices (for example, LCD panel size, resolution, etc.). These devices are based on high visualization, battery lifetime and power optimization for ECG service in emergency condition. These UT devices are used to achieve highest level of satisfaction in terms, i.e., less power drain, extended battery lifetime and optimal route selection. QoS parameters with estimation of QoE perception identify the degree of influence of each QoS parameters on the medical data processing is analyzed. The experimental results indicate that QoS is computed at physical, MAC and network layers with transmission power (− 15 dBm), delay (100 ms), jitter (40 ms), throughput (200 Bytes), duty cycle (10%) and route selection (optimal). Thus it can be said that proposed AQCA is the potential candidate for QoS computation than Baseline for medical healthcare applications.
© 2019, Springer-Verlag London Ltd., part of Springer Nature.

Adaptive QoS computation Medical data processing QoS-QoE correlation Intelligent healthcare applications

SCI ; EI

英语

通讯

[2017YFC0804003] ; [21-1465/SRGP/R&D/HEC/2016] ; [JCYJ20170817112037041] ; [2017KTSCX166] ; National Natural Science Foundation of China[6171101169]

Computer Science

Computer Science, Artificial Intelligence

WOS:000512022900009

Springer

20190206346641

Computational efficiency ; Electric batteries ; Emergency services ; Health care ; Liquid crystal displays ; Medical applications ; Medium access control ; Network layers ; Transportation routes

Health Care:461.7 ; Electric Batteries:702.1 ; Computer Software, Data Handling and Applications:723 ; Accidents and Accident Prevention:914.1

ENGINEERING

Web of Science

1.Electrical Engineering Department, Sukkur IBA University, Sukkur; 65200, Pakistan
2.IDA-Computer and Information Science Department, Linkoping University, Linköping; 58183, Sweden
3.Department of Biomedical Engineering, Kyunghee University South Korea, Suwon; 16705, Korea, Republic of
4.Department of Physics, Shah Abdul Latif University, Khairpur Mirs; Sindh; 66111, Pakistan
5.Department of Computer Science, Bahria University, Islamabad, Pakistan
6.Shenzhen Key Laboratory of Computational Intelligence, Department of the Computer Science and Engineering, Southern University of Science and Technology, Shenzhen; 518055, China

Sodhro, Ali Hassan,Malokani, Abdul Sattar,Sodhro, Gul Hassan,et al. An adaptive QoS computation for medical data processing in intelligent healthcare applications[J]. Neural Computing and Applications,2020,32(3):723-734.

Sodhro, Ali Hassan,Malokani, Abdul Sattar,Sodhro, Gul Hassan,Muzammal, Muhammad,&Zongwei, Luo.(2020).An adaptive QoS computation for medical data processing in intelligent healthcare applications.Neural Computing and Applications,32(3),723-734.

Sodhro, Ali Hassan,et al."An adaptive QoS computation for medical data processing in intelligent healthcare applications".Neural Computing and Applications 32.3(2020):723-734.