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학술대회 A Flow-based Parallel Packet Processing Approach for Core Affinity and Core Scalability
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저자
최강일
발행일
201912
출처
International Conference on Information Science and Applications (ICISA) 2019 (LNEE 621), pp.129-134
DOI
https://dx.doi.org/10.1007/978-981-15-1465-4_14
협약과제
19HH1200, 초연결 지능 인프라 원천기술 연구개발, 김선미
초록
Existing high-speed parallel packet processing approaches lack in supporting core affinity and scalability. The core affinity is important to improve the packet processing performance for the flow, and the core scalability is adjusting the number of cores of a network application, that is required to achieve parallel packet processing efficiency, scaling based on the incoming network traffic. In this paper, we propose an approach to support flow core affinity and core scalability simultaneously. We allow multiple cores to handle packets in parallel while ensuring the flow core affinity by using a flow-to-core table. We also allow one packet-receive queue for one core and monitoring traffic workload, we automatically adjust the number of packet-receive queues and cores according to the traffic workload for core scalability. Through experiments, we examine the feasibility of the proposed approach.
키워드
Core scalability, Flow core affinity, Parallel packet processing
KSP 제안 키워드
Flow-based, High Speed, Network Traffic, Network applications, monitoring traffic, packet processing, processing efficiency, processing performance