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Surv."],"published-print":{"date-parts":[[2021,7,31]]},"abstract":"<jats:p>\n            As a recent innovation, network functions virtualization (NFV)\u2014with its core concept of replacing hardware middleboxes with software network functions (NFs) implemented in commodity servers\u2014promises cost savings and flexibility benefits. However, transitioning NFs from special-purpose hardware to commodity servers has turned out to be more challenging than expected, as it inevitably incurs performance penalties due to bottlenecks in both software and hardware. To achieve performance comparable to hardware middleboxes, there is a strong demand for a speedup in NF processing, which plays a crucial role in the success of NFV. In this article, we study the performance challenges that exist in general-purpose servers and simultaneously summarize the typical performance bottlenecks in NFV. Through reviewing the progress in the field of\n            <jats:italic>NFV acceleration<\/jats:italic>\n            , we present a new taxonomy of the state-of-the-art efforts according to various acceleration approaches. We discuss the surveyed works and identify the respective advantages and disadvantages in each category. We then discuss the products, solutions, and projects emerged in industry. We also present a gap analysis to improve current solutions and highlight promising research trends that can be explored in the future.\n          <\/jats:p>","DOI":"10.1145\/3397022","type":"journal-article","created":{"date-parts":[[2020,7,7]],"date-time":"2020-07-07T12:38:30Z","timestamp":1594125510000},"page":"1-42","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["Paving the Way for NFV Acceleration"],"prefix":"10.1145","volume":"53","author":[{"given":"Xincai","family":"Fei","sequence":"first","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8570-1345","authenticated-orcid":false,"given":"Fangming","family":"Liu","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}]},{"given":"Qixia","family":"Zhang","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}]},{"given":"Hai","family":"Jin","sequence":"additional","affiliation":[{"name":"National Engineering Research Center for Big Data Technology and System, Key Laboratory of Services Computing Technology and System, Ministry of Education, School of Computer Science and Technology, Huazhong University of Science and Technology, China"}]},{"given":"Hongxin","family":"Hu","sequence":"additional","affiliation":[{"name":"Clemson University, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_2_2_1_1","unstructured":"6WIND. 2019. 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