A robust energy-efficient routing algorithm to cloud computing networks for learning

Dingde Jiang, Jindi Liu, Zhihan Lv, Shuping Dang, Gaojie Chen, Lei Shi

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)2483-2495
Number of pages13
JournalJournal of Intelligent and Fuzzy Systems
Issue number5
Publication statusPublished - 13 Oct 2016


  • Cloud computing
  • energy-efficient networks
  • network traffic
  • routing
  • technology enhanced learning


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