Conference paper Open Access

Slice-aware Resource Orchestration of an Elastic 5G Network via Evolutionary Algorithms

Mpatziakas, Asterios; Papadopoulos, Stavros; Khatibi, Sina; Drosou, Anastasios; Tzovaras, Dimitrios


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    <subfield code="a">© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.</subfield>
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    <subfield code="u">Information Technologies Institute, Centre for Research and Technology, Thessaloniki, Greece</subfield>
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    <subfield code="a">Slice-aware Resource Orchestration of an Elastic 5G Network via Evolutionary Algorithms</subfield>
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    <subfield code="c">761445</subfield>
    <subfield code="a">5G Mobile Network Architecture for diverse services, use cases, and applications in 5G and beyond</subfield>
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    <subfield code="a">&lt;p&gt;Fifth generation mobile networks (5G) will enable new use cases for industries and vertical markets via numerous innovative approaches that overcome limitations of existing systems. Two concepts essential for the realization of 5G, are network elasticity and slicing. The application of these concepts allows the simultaneous hosting of more services that use a common resource pool while reducing operation and capital expenses. The realization of these benefits demands an efficient method to scale the resources allocated between different slices often with diverse demands. We apply a multi-objective approach, based on evolutionary algorithms to accomplish optimized resource orchestration between cloud-based slices in a 5G network deployed over a large European city. Numerical results are provided for the proposed approach and are compared to other allocation schemes.&lt;/p&gt;</subfield>
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