Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks. (February 2018)
- Record Type:
- Journal Article
- Title:
- Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks. (February 2018)
- Main Title:
- Applying improved particle swarm optimization for dynamic service composition focusing on quality of service evaluations under hybrid networks
- Authors:
- Gao, Honghao
Zhang, Kang
Yang, Jianhua
Wu, Fangguo
Liu, Hongsheng - Abstract:
- Hybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applications that can sense mobility via changes in user location and combining services to support target functions. In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. First, this work classifies hybrid services into different task groups to generate candidate sets and then interface matching is used to compare the operations of candidate services with user requirements to select the appropriate services. Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. Finally, a set of experiments is conducted to demonstrate the effectiveness of the proposed method for determining the dynamic service composition, particularly when the scale of hybrid services is large. The methodHybrid services use different protocols on various networks, such as WIFI networks, Bluetooth networks, 5G communications systems, and wireless sensor networks. Hybrid service compositions can be varied, representing an effective method of integrating into wireless scenarios context-aware applications that can sense mobility via changes in user location and combining services to support target functions. In this article, improved particle swarm optimization is introduced into the quality service evaluation of dynamic service composition to meet the mobility requirements of hybrid networks. First, this work classifies hybrid services into different task groups to generate candidate sets and then interface matching is used to compare the operations of candidate services with user requirements to select the appropriate services. Second, the service composition is determined by the particle swarm optimization simulation process, which aims to identify an optimal plan based on the calculated value from quality of service. Third, considering a change of service repository, when the quality of a composite service is lower than a predefined threshold, the local greedy algorithm and global reconfiguration method are adopted to dynamically restructure composite services. Finally, a set of experiments is conducted to demonstrate the effectiveness of the proposed method for determining the dynamic service composition, particularly when the scale of hybrid services is large. The method provides a technical reference for engineering practice that will fulfill mobile computing needs. … (more)
- Is Part Of:
- International journal of distributed sensor networks. Volume 14:Number 2(2018)
- Journal:
- International journal of distributed sensor networks
- Issue:
- Volume 14:Number 2(2018)
- Issue Display:
- Volume 14, Issue 2 (2018)
- Year:
- 2018
- Volume:
- 14
- Issue:
- 2
- Issue Sort Value:
- 2018-0014-0002-0000
- Page Start:
- Page End:
- Publication Date:
- 2018-02
- Subjects:
- Hybrid service selection -- quality of service -- improved particle swarm optimization -- greedy algorithm -- dynamic service composition
Sensor networks -- Periodicals
Intelligent agents (Computer software) -- Periodicals
Multisensor data fusion -- Periodicals
681.2 - Journal URLs:
- http://www.informaworld.com/smpp/title~content=t714578688~db=all ↗
http://www.metapress.com/openurl.asp?genre=journal&issn=1550-1329 ↗
http://dsn.sagepub.com/ ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1177/1550147718761583 ↗
- Languages:
- English
- ISSNs:
- 1550-1329
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.186400
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 8485.xml