Network bandwidth continues to scale rapidly, yet Internet data transmission performance remains constrained by the legacy 1500 B MTU. This small MTU translates high bandwidth into high packet rates that strain CPU processing at middleboxes and end hosts. While increasing the MTU could substantially improve performance, coordinating upgrades across arbitrary Internet paths is impractical.

This paper proposes a systematic approach to incrementally enabling large MTUs in the Internet. We demonstrate that increasing the MTU size significantly enhances the performance of both middleboxes and end hosts. To bridge MTU mismatches at network borders, we introduce PacketExpress gateway (PXGW), an MTU-translating gateway that dynamically adjusts packet sizes for cross-traffic. PXGW merges and splits TCP payloads on the fly and tunnels UDP packets, ensuring seamless adaptation. Also, we propose F-PMTUD, a new path MTU discovery algorithm that determines the path MTU within a single round-trip without relying on ICMP. Our preliminary evaluation shows that the PXGW prototype achieves 1.45 Tbps of packet forwarding throughput using only 8 CPU cores. After dynamic conversion, 94% of transmitted TCP packets are 9000 B jumbo frames, indicating that most flows were effectively converted into large segments, thereby demonstrating the system's efficiency and scalability. We also find that large-MTU packets, made available via PXGW, enhance end-host performance by up to 2.5X.

The Maximum Transmission Unit (MTU) refers to the largest packet size that can be transferred on a particular layer-3 network. As the dominance of Ethernet prevails, the "de-facto" standard MTU of 1500B has become universal in the wide-area networks. Unfortunately, the current MTU size overly limits the transmission performance especially when the underlying link speed rapidly increases while the CPU advancement stagnates.

With the development of cloud technology, people are focusing on lightweight container technology. Container networking is a core technology in providing high-level cloud services, and there are various implementation models such as Container Network Model (CNM) and Container Network Interface (CNI). Among them, CNI is a de-facto standard adopted by various container platforms. There are many plugins that implement the CNI networking model, and the implementation method differs, showing a great difference in a view of performance. MEC (Multi-Access Edge Computing) is a technology that provides services by locating the server closest to the user who wants to use mobile communication services. In this paper, the performance was measured by applying various CNI network plugins to the CoV architecture. Through this measurement, we analyzed the factors of network performance degradation. The result of the analysis is expected to be used as a good reference in constructing the CoV architecture for low latency in the future.