The softwarization and virtualization of network functions have enabled better flexibility and manageability in mobile communication systems today. However, considering the slowdown of Moore's law, it would be critical to reduce the cost of providing data plane services in the 6G era. In this paper, we argue that by leveraging programmable network devices such as Smart Network Interface Cards (SmartNICs) and programmable switches, we can offload custom network functionalities instead of using expensive host CPU resources for data plane operations. We propose S-Core, a scalable systems design for mobile packet core harnessing network data plane offloading. S-Core operates on top of multiple heterogeneous network devices, where heavy-hitter session rules can be dynamically placed in response to varying network traffic. Based on our prototype implementation, we argue that the use of programmable network devices will enable lessened CPU load, reduced latency, and improved energy efficiency in the next-gen communication systems.

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.

In this paper, we propose a new user-plane (UP) network architecture for 6G cellular networks, where there is no distinction between radio access network (RAN) and core network (CN). We define a new network function (NF), called merged-UP (M-UP), where the UP functions of both RAN and CN sides are merged, thus enabling efficient protocol operations. We also propose an IP flow-based radio quality-of-service (QoS) control scheme to support 6G services with diverse QoS requirements. Based on our network testbed system, we show that the proposed architecture improves the system performance in terms of packet processing load and maximum throughput.

Delay-tolerant Wi-Fi offloading is known to improve overall mobile network bandwidth at low delay and low cost. Yet, in reality, we rarely find mobile apps that fully support opportunistic Wi-Fi access. This is mainly because it is still challenging to develop delay-tolerant mobile apps due to the complexity of handling network disruptions and delays. In this paper, we present Cedos, a practical delay-tolerant mobile network access architecture in which one can easily build a mobile app. Cedos consists of three components. First, it provides a familiar socket API whose semantics conforms to TCP, while the underlying protocol, D2TP, transparently handles network disruptions and delays in mobility. Second, Cedos allows the developers to explicitly exploit delays in mobile apps. App developers can express maximum user-specified delays in content download or use the API for real-time buffer management at opportunistic Wi-Fi usage. Third, for backward compatibility to existing TCP-based servers, Cedos provides D2Prox, a protocol-translation Web proxy. D2Prox allows intermittent connections on the mobile device side, but correctly translates Web transactions with traditional TCP servers. We demonstrate the practicality of Cedos by porting mobile Firefox and VLC video streaming client to using the API. We also implement delay/disruption-tolerant podcast client and run a field study with 50 people for eight weeks. We find that up to 92.4% of the podcast traffic is offloaded to Wi-Fi, and one can watch a streaming video in a moving train while offloading 48% of the content to Wi-Fi without a single pause.

Delay-tolerant Wi-Fi offloading is known to improve overall mobile network bandwidth at low delay and low cost. Yet, in reality, we rarely find mobile apps that fully support opportunistic Wi-Fi access. This is mainly because it is still challenging to develop delay-tolerant mobile apps due to the complexity of handling network disruptions and delays.

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