期刊
IEEE-ACM TRANSACTIONS ON NETWORKING
卷 29, 期 3, 页码 1308-1320出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNET.2021.3058401
关键词
Servers; Distributed databases; Edge computing; Cloud computing; Indexes; Routing; Protocols; Data location service; Cuckoo Summary; greedy routing; mobile edge computing; SDN
类别
资金
- National Key Research and Development Program of China [2018YFE0207600]
- National Natural Science Foundation of China [U19B2024]
- Tianjin Science and Technology Foundation [18ZXJMTG00290]
The HDS framework divides the data location service into intra-region and inter-region, utilizing different protocols to achieve efficient data localization, with short response latency and low false positive rate.
The hierarchical mobile edge computing satisfies the stringent latency requirements of data access and processing for emerging edge applications. The data location service is a basic function to provide data storage and retrieval to enable these applications. However, it still lacks research of a scalable and low-latency data location service in the environment. The existing solutions, such as DNS and DHT, fail to meet the requirement of those latency-sensitive applications. Therefore, in this article, we present a low-latency hybrid data-sharing framework, HDS. The HDS divides the data location service into two parts: intra-region and inter-region. More precisely, we design a data sharing protocol called Cuckoo Summary to achieve fast data localization in intra-region. Furthermore, for the inter-region data sharing, we develop a geographic routing based scheme to achieve efficient data localization with only one overlay hop. The advantages of HDS include short response latency, low implementation overhead, and few false positives. We implement the HDS framework based on a P4 prototype. The experimental results show that, compared to the state-of-the-art solutions, our design achieves 50.21% shorter lookup paths and 92.75% fewer false positives.
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