Horizontal and vertical scaling frameworks for network function virtualization = 네트워크 기능 가상화의 수평적 수직적 성능 확장성을 지원하기 위한 프레임워크들에 관한 연구

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dc.contributor.advisorMoon, Sue Bok-
dc.contributor.advisor문수복-
dc.contributor.authorWoo, Shinae-
dc.date.accessioned2019-08-25T02:47:45Z-
dc.date.available2019-08-25T02:47:45Z-
dc.date.issued2017-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=866987&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/265328-
dc.description학위논문(박사) - 한국과학기술원 : 전산학부, 2017.8,[iv, 73 p. :]-
dc.description.abstractNFV (Network function virtualizations) promises the benefit of the virtual environment -- elastic scaling, fault tolerance, rapid deployment of new services -- by moving network functions from fixed-function middlebox infrastructures to software on virtual machines run on commodity servers. One of the challenges arise from the NFV (Network Function Virtualization) is that the gap between the promise of network function virtualization (NFV) and the practice as is. My dissertation focuses on the scalability, one of such gap-
dc.description.abstractprocessing throughput should increase linearly with added resources (CPU cores, VMs, processes) without imposing much overhead. However, building scalable network functions is difficult since they are stateful-
dc.description.abstractSome state needs to be migrated to other instance (VM, core, process) to preserve locality as network traffic is re-balanced (e.g., per-flow structures), while others need to be shared across instances (e.g., aggregated counters, a list of detected hosts). The statefulness is a source of performance overhead such as core/machine-crossing overhead, locking for shared structures as well as making the programming task complex. In this dissertation, we identify the challenges for achieving a scalable performance of network functions and propose three systems for them. Firstly, based on the observation of the state access patterns of network functions, we build a network function building programming model and framework to support elastic horizontal scalability (S6). It shows linear throughput scaling with 2-3 orders of magnitude lower per-packet added latency than existing state-of-the-art systems. Secondly, we present a hardware assisted flow load-balancing mechanism (Symmetric RSS) to avoid core-crossing overhead and implement a high-performance and multi-core scalable flow monitoring system (MonBot) with the mechanism. Using the system, we conduct large-scale real-time measurement study on the live 3G commercial traffic. Lastly, we design and implement a multi-core scalable network stack (mTCP) to overcome the current kernel's inefficiency. It shows 25 times better connection set-up performance than Linux kernel.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.subjectNetwork function virtualization▼amiddlebox▼aelastic horizontal scalability▼amulticore vertical scalability▼adistributed shared objects▼anetwork stack▼aTCP▼anetwork monitoring▼a3G network traffic analysis▼aweb caching▼abyte caching-
dc.subject네트워크 기능 가상화▼a미들박스▼a탄력적 성능 확장성▼a멀티코어 수평적 확장성▼a분산 공유 오브젝트▼aTCP▼a네트워크 모니터링▼a3G 네트워크 트래픽 분석▼a웹 캐싱▼a바이트 캐싱-
dc.titleHorizontal and vertical scaling frameworks for network function virtualization = 네트워크 기능 가상화의 수평적 수직적 성능 확장성을 지원하기 위한 프레임워크들에 관한 연구-
dc.typeThesis(Ph.D)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :전산학부,-
dc.contributor.alternativeauthor우신애-
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