Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Issue title: Multimedia in technology enhanced learning
Guest editors: Zhihan Lv
Article type: Research Article
Authors: Jiang, Dingdea; * | Liu, Jindia | Lv, Zhihanb | Dang, Shupingc | Chen, Gaojiec | Shi, Leid
Affiliations: [a] School of Computer Science and Engineering, Northeastern University, Shenyang, China | [b] SIAT, Chinese Academy of Science, Shenzhen, China | [c] Department of Engineering Science, University of Oxford, Oxford, UK | [d] TSSG, Waterford Institute of Technology, Waterford, Ireland
Correspondence: [*] Corresponding author. Dingde Jiang, School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China. Tel./Fax: +86 02483684219; E-mail: [email protected].
Abstract: With the advancement of multimedia, Internet of things, and cloud computing technologies, technology enhanced learning applications such as smart school and smart learning at home have been paid more attentions to. Cloud computing services, which provide a novel collaborative and personalized learning style, have an important impact on learning and teaching. However, with the rapid development of cloud computing, the energy consumption problem for cloud computing networks cannot be ignored and the idea of energy efficiency comes into being. Currently, the main method to solve energy consumption problem is to turn the idle routers and links into sleeping, but this approach cannot be suited for cloud computing networks and may bring down network resource utility and network performance. This paper combining the Sleeping Redundant Links Algorithm (SRLA) with the Minimum Criticality Routing Algorithm (MCRA), proposes a Robust Energy Efficiency Routing Algorithm (REERA) used for cloud computing networks. The REERA uses the SRLA algorithm to sleep the redundant links in cloud computing backbone network, and then improves the robustness of the entire network by the MCRA algorithm. The REERA is able to dynamically change the link weight, ensure that most of the link can be used uniformly, and avoid the traffic congestion when certain links of cloud computing networks was excessively used. It thus improves the performance of the entire network. Comparing REERA with OSPF-based algorithm, the simulation results show that REERA outperforms Open Shortest Path First (OSPF) -based algorithm, and REERA can realize the energy-efficient routing algorithm under the premise of network robustness constraints.
Keywords: Cloud computing, energy-efficient networks, network traffic, technology enhanced learning, routing
DOI: 10.3233/JIFS-169090
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 5, pp. 2483-2495, 2016
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]