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SLA-NFV: an SLA-aware High Performance Framework for Network Function Virtualization

Published: 22 August 2016 Publication History

Abstract

We propose SLA-NFV, a Service Level Agreement (SLA) aware framework, for building high-performance NFV, focusing on fulfilling SLAs of service subscribers (or tenants). SLA-NFV leverages a hybrid infrastructure with both software and programmable hardware to enhance NFV’s capability with respect to various SLAs. Evaluations show that a hybrid service chain could reduce latency by up to 60% compared with a pure soft- ware service chain.

References

[1]
Gember-Jacobson, A., Viswanathan, R., Prakash, C., Grandl, R., Khalid, J., Das, S., and Akella, A. Opennf: Enabling innovation in network function control. In Proceedings of the 2014 ACM conference on SIGCOMM (2014), ACM, pp. 163–174.
[2]
Halpern, J., and Pignataro, C. Service function chaining (sfc) architecture. draft-ietf-sfc-architecture-07 (in progress) (2015).
[3]
Zhu, S., Bi, J., Sun, C., Wu, C., and Hu, H. Sdpa: Enhancing stateful forwarding for software-defined networking. In Proceedings of the 23rd IEEE International Conference on Network Protocols (ICNP 2015), pp. 323–333.

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  • (2024)Load-Aware Network Resource Orchestration in LEO Satellite Network: A GAT-Based ApproachIEEE Internet of Things Journal10.1109/JIOT.2024.335007211:9(15969-15984)Online publication date: 1-May-2024
  • (2023)A Meta Reinforcement Learning Approach for SFC Placement in Dynamic IoT-MEC NetworksApplied Sciences10.3390/app1317996013:17(9960)Online publication date: 3-Sep-2023
  • (2022)Network Function Virtualization and Service Function Chaining Frameworks: A Comprehensive Review of Requirements, Objectives, Implementations, and Open Research ChallengesFuture Internet10.3390/fi1402005914:2(59)Online publication date: 15-Feb-2022
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  1. SLA-NFV: an SLA-aware High Performance Framework for Network Function Virtualization

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        cover image ACM Conferences
        SIGCOMM '16: Proceedings of the 2016 ACM SIGCOMM Conference
        August 2016
        645 pages
        ISBN:9781450341936
        DOI:10.1145/2934872
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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        New York, NY, United States

        Publication History

        Published: 22 August 2016

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        Author Tags

        1. High Performance
        2. Hybrid Infrastructure
        3. NFV
        4. SLA

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        SIGCOMM '16
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        SIGCOMM '16: ACM SIGCOMM 2016 Conference
        August 22 - 26, 2016
        Florianopolis, Brazil

        Acceptance Rates

        SIGCOMM '16 Paper Acceptance Rate 39 of 231 submissions, 17%;
        Overall Acceptance Rate 462 of 3,389 submissions, 14%

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        Cited By

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        • (2024)Load-Aware Network Resource Orchestration in LEO Satellite Network: A GAT-Based ApproachIEEE Internet of Things Journal10.1109/JIOT.2024.335007211:9(15969-15984)Online publication date: 1-May-2024
        • (2023)A Meta Reinforcement Learning Approach for SFC Placement in Dynamic IoT-MEC NetworksApplied Sciences10.3390/app1317996013:17(9960)Online publication date: 3-Sep-2023
        • (2022)Network Function Virtualization and Service Function Chaining Frameworks: A Comprehensive Review of Requirements, Objectives, Implementations, and Open Research ChallengesFuture Internet10.3390/fi1402005914:2(59)Online publication date: 15-Feb-2022
        • (2022)Complementary in Time and Space: Optimization on Cost and Performance with Multiple Resources Usage by Server Consolidation in Cloud Data CenterApplied Sciences10.3390/app1219965412:19(9654)Online publication date: 26-Sep-2022
        • (2022)Deep Reinforcement Learning-based Dynamic SFC Deployment in IoT-MEC Networks2022 IEEE 8th International Conference on Computer and Communications (ICCC)10.1109/ICCC56324.2022.10065921(862-867)Online publication date: 9-Dec-2022
        • (2022)A Residual LSTM based Multi-Label Classification Framework for Proactive SLA Management in a Latency Critical NFV Application Use-Case2022 IEEE 19th Annual Consumer Communications & Networking Conference (CCNC)10.1109/CCNC49033.2022.9700502(782-789)Online publication date: 8-Jan-2022
        • (2021)Online Service Function Chain Deployment for Live-Streaming in Virtualized Content Delivery Networks: A Deep Reinforcement Learning ApproachFuture Internet10.3390/fi1311027813:11(278)Online publication date: 29-Oct-2021
        • (2021)DRL-QOR: Deep Reinforcement Learning-Based QoS/QoE-Aware Adaptive Online Orchestration in NFV-Enabled NetworksIEEE Transactions on Network and Service Management10.1109/TNSM.2021.305549418:2(1758-1774)Online publication date: Jun-2021
        • (2021)DDQP: A Double Deep Q-Learning Approach to Online Fault-Tolerant SFC PlacementIEEE Transactions on Network and Service Management10.1109/TNSM.2021.304929818:1(118-132)Online publication date: Mar-2021
        • (2021)A Deep Neural Network-Based Multi-Label Classifier for SLA Violation Prediction in a Latency Sensitive NFV ApplicationIEEE Open Journal of the Communications Society10.1109/OJCOMS.2021.31228442(2469-2493)Online publication date: 2021
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