Gaurav Sinha, M. Kanagarathinam, Sujith Rengan Jayaseelan, G. Choudhary
{"title":"CQUIC: Cross-Layer QUIC for Next Generation Mobile Networks","authors":"Gaurav Sinha, M. Kanagarathinam, Sujith Rengan Jayaseelan, G. Choudhary","doi":"10.1109/WCNC45663.2020.9120850","DOIUrl":null,"url":null,"abstract":"Requirements for Next Generation Mobile Networks (NGMN) include low latency, higher throughput, scalability, and energy efficiency. As 5G millimeter wave (mmWave) band is short-range, the handover is inevitable. Google proposed QUIC (Quick UDP Internet Connection), which aims to address these challenges. However, Google QUIC (GQUIC), follows “WiFi-First” policy causing frequent network switching, which can lead to a throughput reduction and fast battery degradation. In this paper, we propose Cross-layer QUIC (CQUIC) framework, that follows “WiFi-if-best” policy to enhance the throughput and resilience by using a Cross-Layer approach. CQUIC proposes a novel migration scheme in QUIC which adapts to the dynamic network characteristics. GQUIC protocol with low bandwidth and high round-trip-time fail to migrate for seamless User Experience. CQUIC algorithm predicts Cross-Layer Score (CLS) which incorporates predicted Signal-to-Interference Noise Ratio (SINR), QUIC Bandwidth, round-triptime (RTT) stats from QUIC Session and models the handover decision pro-actively. Compared with state-of-the-art methods such as GQUIC and HTTP (using TCP) this paper reveals the significant benefits of the proposed method. A series of experimental results obtained in live air network over Samsung Galaxy S10 devices show CQUIC outperforms the GQUIC by 20%, TCP by 36% and MPTCP (Backup) by 17% in terms of throughput. Furthermore, CQUIC compared with MPTCP, reduces the data consumption over mobile network and operates green by reducing the power consumption by 25%.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC45663.2020.9120850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Requirements for Next Generation Mobile Networks (NGMN) include low latency, higher throughput, scalability, and energy efficiency. As 5G millimeter wave (mmWave) band is short-range, the handover is inevitable. Google proposed QUIC (Quick UDP Internet Connection), which aims to address these challenges. However, Google QUIC (GQUIC), follows “WiFi-First” policy causing frequent network switching, which can lead to a throughput reduction and fast battery degradation. In this paper, we propose Cross-layer QUIC (CQUIC) framework, that follows “WiFi-if-best” policy to enhance the throughput and resilience by using a Cross-Layer approach. CQUIC proposes a novel migration scheme in QUIC which adapts to the dynamic network characteristics. GQUIC protocol with low bandwidth and high round-trip-time fail to migrate for seamless User Experience. CQUIC algorithm predicts Cross-Layer Score (CLS) which incorporates predicted Signal-to-Interference Noise Ratio (SINR), QUIC Bandwidth, round-triptime (RTT) stats from QUIC Session and models the handover decision pro-actively. Compared with state-of-the-art methods such as GQUIC and HTTP (using TCP) this paper reveals the significant benefits of the proposed method. A series of experimental results obtained in live air network over Samsung Galaxy S10 devices show CQUIC outperforms the GQUIC by 20%, TCP by 36% and MPTCP (Backup) by 17% in terms of throughput. Furthermore, CQUIC compared with MPTCP, reduces the data consumption over mobile network and operates green by reducing the power consumption by 25%.