Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud. Issue 4 (1st October 2016)
- Record Type:
- Journal Article
- Title:
- Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud. Issue 4 (1st October 2016)
- Main Title:
- Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud
- Authors:
- Xie, Xiaolan
Liu, Ruikun
Cheng, Xiaochun
Hu, Xin
Ni, Jinsheng - Abstract:
- Abstract: With the advent of big data era, Cloud Computing has drawn widespread interests from industrial and academia. Job scheduling algorithm plays a crucial role in the paradigm of Cloud Computing. The well-designed job scheduling algorithms can provide fast, high quality and safe services. However, the conventional job scheduling algorithms are focusing on the improvement of efficiency, these obscure the important issue of trustworthiness in Cloud. This paper proposes a job scheduling algorithm with the consideration of efficiency and trustworthiness in Cloud. The intuition of the proposed algorithm is based on Particle Swarm Optimization (PSO) and Shuffled Frog Leaping Algorithm (SFLA). In this way, the proposed algorithm can avoid to obtain local optimal results. Also, the trust model is introduced to improve the trust of resources. The comprehensive simulations have been conducted via CloudSim. The experimental results have demonstrated that the proposed algorithm improve the trustworthiness than that of two classical compared algorithms GA and TDMin-Min, respectively.
- Is Part Of:
- Intelligent automation & soft computing. Volume 22:Issue 4(2016)
- Journal:
- Intelligent automation & soft computing
- Issue:
- Volume 22:Issue 4(2016)
- Issue Display:
- Volume 22, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 22
- Issue:
- 4
- Issue Sort Value:
- 2016-0022-0004-0000
- Page Start:
- 561
- Page End:
- 566
- Publication Date:
- 2016-10-01
- Subjects:
- Cloud service -- job scheduling -- trust mechanism in Cloud -- Particle Swarm Optimization (PSO) -- Shuffled Frog Leaping Algorithm (SFLA)
Artificial intelligence -- Periodicals
Intelligent control systems -- Periodicals
003.5 - Journal URLs:
- http://www.tandfonline.com/loi/tasj20 ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/10798587.2016.1152770 ↗
- Languages:
- English
- ISSNs:
- 1079-8587
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4531.831515
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 2663.xml