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Multi-Service Resource Allocation in Future Network With Wireless Virtualization
Author(s) -
Letian Li,
Na Deng,
Weilong Ren,
Baohua Kou,
Wuyang Zhou,
Shui Yu
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.2018.2871506
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
Future network is envisioned to be a multi-service network which can support various types of terminal devices with diverse quality of service requirements. As one of the key technologies, wireless virtualization establishes different virtual networks dependent on different application scenarios and user requirements through flexibly slicing and sharing wireless resources in future networks. In this paper, we first propose a service-centric wireless virtualization model to slice network according to service types. In this model, how to share and slice wireless resource is one of the fundamental issues to be addressed. Therefore, we formulate and solve a multi-service resource allocation problem to realize spectrum virtualization. Different from the existing strategies, we decouple the multi-service resource allocation problem in the proposed virtualization model to make it easier to solve. Specifically, it is solved in two stages: inter-slice resource allocation and intra-slice resource scheduling. In the first stage, we formulate the inter-slice resource allocation as a discrete optimization problem and propose a heuristic algorithm to get sub-optimal solution of this NP-hard problem. In the second stage, we modify several existing scheduling algorithms suitable for scheduling users of several specific services. Numerical results show the superiority of the proposed scheduling algorithms over the existing ones when applied to schedule specific services. Moreover, proposed resource allocation scheme is verified to meet the properties of virtualization and solves the multi-service resource allocation problem well.

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