SAP: Subchain-Aware NFV Service Placement in Mobile Edge Cloud
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Existing Network Function Virtualization (NFV) service placements that reuse existing network functions either reuse an entire Service Function Chain (SFC) or only individual network functions while ignoring the chain configuration cost for configuring the SFC traffic steering and ignoring the reliability of the network functions. Also, the Mobile Edge Cloud (MEC) frameworks that are required to implement an NFV service placement should ideally seamlessly cooperate with the various existing NFV Management and Orchestration (MANO) frameworks. However, the existing MEC frameworks lack multi-MANO support. We formulate the novel Subchain-Aware NFV service Placement (SAP) optimization model that accounts for the configuration cost for stitching together reused network functions to an SFC and strives to reuse existing subchains of consecutive network functions (with already deployed SFC traffic steering), while accounting for the recovery cost of network functions with limited reliability. We develop Tabu-SAP, a Tabu search approach to solve the SAP optimization problem. Furthermore, we introduce the novel Automated Provisioning framework for MEC (APMEC) with open-source OpenStack implementation to enable the deployment of Tabu-SAP in real networks; APMEC supports multiple MANOs through a loose coupling MANO-MEC design. Our Tabu-SAP evaluations indicate an around eightfold increase of the number of supported SFCs compared to the state-of-the-art reuse of individual network functions, while substantially reducing the total cost, which includes the chain configuration cost. Also, for long SFCs of seven or more network functions, the Tabu-SAP total cost is less than 10% higher than the optimal solution (which requires over ten times longer execution time).
Details
Original language | English |
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Article number | 9866548 |
Pages (from-to) | 319-341 |
Number of pages | 23 |
Journal | IEEE Transactions on Network and Service Management |
Volume | 2022 |
Issue number | 20(1) |
Publication status | Published - 1 Jan 2022 |
Peer-reviewed | Yes |
External IDs
Scopus | 85135960879 |
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ORCID | /0000-0001-7008-1537/work/142248648 |
ORCID | /0000-0001-8469-9573/work/161891049 |
Keywords
Keywords
- Cloud computing, Costs, Hardware, Network function virtualization, Noise measurement, Reliability, Software reliability