## 2 Related Work
SCLP was designed to enhance the performance of software tunneling by leveraging the Generic Receive Offload (GRO) feature in the Linux kernel, thereby reducing the number of software interrupts. The authors implemented VXLAN over SCLP and compared its performance with the original UDP-based VXLAN, NVGRE, GENEVE, and STT. Their results showed that SCLP achieved throughput comparable to STT and significantly higher than the other protocols without modifying existing protocol semantics, making it a viable alternative for high-performance software tunneling in data centers. A research paper focused on improving the performance of Open vSwitch VXLAN in cloud data centers through hardware acceleration proposed a design that utilizes hardware acceleration methods to enhance the throughput performance of VXLAN [19]. Their implementation demonstrated a fivefold increase in performance, achieving up to 12 Gbps throughput, compared to the 2 Gbps achieved by software-only solutions. This significant improvement underscores the potential of hardware acceleration in optimizing virtualized network environment performance in cloud data centers. Researchers also detailed the VXLAN framework for overlay virtualized Layer 2 networks over Layer 3 networks [20]. This protocol addresses the need for scalable overlay networks within virtualized data centers, accommodating multiple tenants. VXLAN's deployment in cloud service providers and enterprise data centers helps overcome the limitations of traditional VLANs. The protocol's ability to encapsulate Ethernet frames in UDP packets allows for effective communication across IP networks, making it a crucial component in multi-tenant cloud infrastructures. Challenges of measuring latencies in high-speed optical networks, particularly in scenarios requiring microsecond resolution, have also been researched [21]. Researchers propose a software-based solution for latency measurement using high-performance packet engines like DPDK, which provides a cost-effective alternative to hardware-based methods. The paper introduces a novel concept of a convoy of packet trains to measure bandwidth and latency accurately, demonstrating the feasibility of their approach in 10 Gbit/s networks. Researchers also debated a method for real-time measurement of end-to-end path latency in Software-Defined Networks (SDN) [22]. They propose improving the looping technique by using IP TTL as a counter and measuring latency per link stored in the SDN controller. This method reduces redundant work and network overhead, providing accurate and efficient latency measurements. Their approach also includes a technique for measuring latency using queue lengths at network switches, further reducing network overhead. Machine learning-based methods for estimating network latency that does not require explicit measurements have also been researched [23]. ML is trained using the iConnect-Ubisoft dataset and uses IP addresses as the primary input to predict latencies between nodes. Performance evaluations show high accuracy and speed, with a significant proportion of measurements falling within a low estimation error margin. This method offers a fast and efficient alternative to traditional latency measurement techniques in large-scale network systems. In 2021, researchers developed Formullar, a novel FPGA-based network testing tool designed to measure ultra-low latency (ULL) in exact and flexible networking systems [24]. The tool comprises a hybrid architecture with hardware (FPGA) and software components, enabling accurate packet generation and timing control according to various traffic patterns. The hardware layer measures latency based on packet generation and reception timings, providing exact results. Evaluations indicate that Formullar achieves nanosecond precision at a bandwidth of 10 Gbps, making it suitable for time-sensitive applications requiring strict latency guarantees.