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IEEE Network
Article . 2016 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2016
Data sources: DBLP
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Network softwarization and parallel networks: beyond software-defined networks

Authors: Fei-Yue Wang 0001; Liuqing Yang 0001; Xiang Cheng 0001; Shuangshuang Han; Jian Yang 0035;

Network softwarization and parallel networks: beyond software-defined networks

Abstract

The coexistence of various protocols for current network equipment leads to extremely complex network systems, which not only limit the development of network technologies, but also cannot meet the growing demands for cloud computing, big data, and service visualization applications, just to name a few. As a new network architecture, parallel networks are expected to revolutionize this situation and meet the evolving demands for network services. The main idea of a parallel network is to leverage upon software-defined networking to construct artificial networks, and then effectively optimize the network system operations via the interactions between actual and artificial networks. The foundation of the parallel network is the theory of ACP, composed of artificial societies, computational experiments, and parallel execution. By the computational experiments and analysis of the artificial network, a control strategy based on network traffic flow can be continuously updated and tracked on a real-time basis; meanwhile, the collected operating status of the actual network can also be used to optimize the model of the artificial network. These strategies can be applied to all types of network equipment to control network operations at various levels; thus, it is possible to allocate the network resources more effectively, improve the management and utilization of resources, and then provide new network solutions to effectively address the constantly evolving network demands for network performance, scalability, and security.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
34
Top 10%
Top 10%
Top 10%
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