liu.seSearch for publications in DiVA
Planned maintenance
A system upgrade is planned for 10/12-2024, at 12:00-13:00. During this time DiVA will be unavailable.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
An adaptive QoS computation for medical data processing in intelligent healthcare applications
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Sukkur IBA Univ, Pakistan.ORCID iD: 0000-0001-5502-530x
Kyunghee Univ South Korea, South Korea.
Shah Abdul Latif Univ, Pakistan.
Bahria Univ, Pakistan.
Show others and affiliations
2020 (English)In: Neural Computing & Applications, ISSN 0941-0643, E-ISSN 1433-3058, Vol. 32, no 3, p. 723-734Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
SPRINGER LONDON LTD , 2020. Vol. 32, no 3, p. 723-734
Keywords [en]
Adaptive; QoS computation; Medical data processing; QoS-QoE correlation; Intelligent healthcare applications
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:liu:diva-164206DOI: 10.1007/s00521-018-3931-1ISI: 000512022900009OAI: oai:DiVA.org:liu-164206DiVA, id: diva2:1413456
Available from: 2020-03-10 Created: 2020-03-10 Last updated: 2023-06-26

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records

Sodhro, Ali Hassan

Search in DiVA

By author/editor
Sodhro, Ali Hassan
By organisation
Database and information techniquesFaculty of Science & Engineering
In the same journal
Neural Computing & Applications
Energy Engineering

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 51 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf