“RNDM 2019 selected papers” special issue

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Optical Switching and Networking Pub Date : 2022-09-01 DOI:10.1016/j.osn.2022.100681
G. Ellinas, T. Panayiotou
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来源期刊
Optical Switching and Networking
Optical Switching and Networking COMPUTER SCIENCE, INFORMATION SYSTEMS-OPTICS
CiteScore
5.20
自引率
18.20%
发文量
29
审稿时长
77 days
期刊介绍: Optical Switching and Networking (OSN) is an archival journal aiming to provide complete coverage of all topics of interest to those involved in the optical and high-speed opto-electronic networking areas. The editorial board is committed to providing detailed, constructive feedback to submitted papers, as well as a fast turn-around time. Optical Switching and Networking considers high-quality, original, and unpublished contributions addressing all aspects of optical and opto-electronic networks. Specific areas of interest include, but are not limited to: • Optical and Opto-Electronic Backbone, Metropolitan and Local Area Networks • Optical Data Center Networks • Elastic optical networks • Green Optical Networks • Software Defined Optical Networks • Novel Multi-layer Architectures and Protocols (Ethernet, Internet, Physical Layer) • Optical Networks for Interet of Things (IOT) • Home Networks, In-Vehicle Networks, and Other Short-Reach Networks • Optical Access Networks • Optical Data Center Interconnection Systems • Optical OFDM and coherent optical network systems • Free Space Optics (FSO) networks • Hybrid Fiber - Wireless Networks • Optical Satellite Networks • Visible Light Communication Networks • Optical Storage Networks • Optical Network Security • Optical Network Resiliance and Reliability • Control Plane Issues and Signaling Protocols • Optical Quality of Service (OQoS) and Impairment Monitoring • Optical Layer Anycast, Broadcast and Multicast • Optical Network Applications, Testbeds and Experimental Networks • Optical Network for Science and High Performance Computing Networks
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Modeling and upgrade of disaster-resilient interdependent networks using machine learning Self-adjusting resilient control plane for virtual software-defined optical networks NFV recovery strategies for critical services after massive failures in optical networks Editorial Board An architecture to improve performance of software-defined optical networks
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