A Novel Framework of Distributed Datacenter Networks to Support Intelligent Services: Architecture, Operation, and Solutions | Zendy

Limei Peng | Zendy; Pin-Han Ho | Zendy

Open Access

A Novel Framework of Distributed Datacenter Networks to Support Intelligent Services: Architecture, Operation, and Solutions

Author(s) -

Limei Peng,

Pin-Han Ho

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2883252

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

Existing datacenter networks (DCNs) support the legacy cloud services well; nonetheless, it is inherently short of provisioning the emerging IoT services, such as the vehicle services, where real-time intelligence, cognition, and security are required, mainly due to its long distance with the IoT devices that generate the intelligent services. Regarding this, this paper proposes a new interconnection architecture for distributed DCNs by way of passive optical network (PON) technology to construct a ubiquitous cloud computing (UCC) environment with high scalability, resiliency, and data locality. A novel de-centralized architecture of virtualized mega DCNs on customized next-generation PONs (NGPONs) to provision UCC is proposed under the name of NGPON-DCN. In addition, a cost-effective deployment design framework and an associated revenue-driven elastic infrastructure-as-a-service delivery model are specified for creation and operation of such NGPON-DCN, followed by a discussion of anticipated key research challenges and optimization opportunities in this new NGPON-DCN convergence paradigm.

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