The Internet architecture has been undergoing a significant refactoring, where the past preeminence of transit providers has been replaced by content providers, which have a ubiquitous presence throughout the world, seeking to improve the user experience, bringing content closer to its final recipients. This restructuring is materialized in the emergence of Massive Scale Data Centers (MSDC) worldwide, which allows the implementation of the Cloud Computing concept. MSDC usually deploy Fat-Tree topologies, with constant bisection bandwidth among servers and multi-path routing. To take full advantage of such characteristics, specific routing protocols are needed. Multi-path routing also calls for revision of transport protocols and forwarding policies, also affected by specific MSDC applications’ traffic characteristics. Experimenting over these infrastructures is prohibitively expensive, and therefore, scalable and realistic experimentation environments are needed to research and test solutions for MSDC. In this paper, we review several environments, both single-host and distributed, which permit analyzing the pros and cons of different solutions.

Massive scale data centers (MSDC) have become a key component of current content-centric Internet architecture. With scales of up to hundreds of thousands servers, conveying traffic inside these infrastructures requires much greater connectivity resources than traditional broadband Internet transit networks. MSDCs use Fat-Tree type topologies, which ensure multipath connectivity and constant bisection bandwidth between servers. To properly use the potential advantages of these topologies, specific routing protocols are needed, with multipath support and low control messaging load. These infrastructures are enormously expensive, and therefore it is not possible to use them to experiment with new protocols; that is why scalable and realistic emulation/simulation environments are needed. Based on previous experiences, in this paper we present extensions to the ns-3 network simulator that allow executing the Free Range Routing (FRR) protocol suite, which support some of the specific MSDC routing protocols. Focused on the Border Gateway Protocol (BGP), we run a comprehensive set of control plane experiments over Fat-Tree topologies, achieving competitive scalability running on a single-host environment, which demonstrates that the modified ns-3 simulator can be effectively used for experimenting in the MSDC. Moreover, the validation was complemented with a theoretical analysis of BGP behavior over selected scenarios. The whole project is available to the community and fully reproducible.

Several data centers adopt fat-tree topologies, where high bisection bandwidth is achieved by interconnecting commodity hardware and by using specific routing solutions. These solutions, which include protocol implementations and configurations, are difficult to evaluate and test both for the density of fat-trees and for the complexity of the protocols. Also, since most issues show up only when a fault happens, it is unfeasible to perform such tests in a production environment. Additionally, the lack of standard testing procedures motivates an effort in developing solutions for such a critical task. In this paper, we propose a methodology devised for testing fat-tree routing protocol implementations. It adopts a wall-clock independent method to establish metrics, which permits normalizing the results of different routing protocol implementations independently from the execution environment. The methodology is implemented by Sibyl, a software framework developed to perform repeatable tests on arbitrary fat-tree topologies automatically. Sibyl also provides a set of tools to analyze the results and investigate implementation behaviors. We evaluate the methodology and Sibyl in three use cases. Such use cases witness a wide spectrum of situations where Sibyl is effective for analyzing, comparing, developing, and debugging routing protocol implementations.

Next-generation services demand stringent Quality of Service (QoS) guarantees, such as per-flow bandwidth assurance, ultra-low latency, and traffic prioritization, posing significant challenges to 5G and beyond networks. As 5G network functions increasingly migrate to edge and central clouds, the transport layer becomes a critical enabler of end-to-end QoS compliance. However, traditional fixed-function infrastructure lacks the flexibility to support the diverse and dynamic QoS profiles standardized by 3GPP. This paper presents a QoS-aware data plane model for programmable transport networks, designed to provide predictable behavior and fine-grained service differentiation. The model supports all 3GPP QoS resource types and integrates per-flow metering, classification, strict priority scheduling, and delay-aware queuing. Implemented on off-the-shelf programmable hardware using P4 and evaluated on an Intel Tofino switch, our approach ensures per-flow bandwidth guarantees, sub-millisecond delay for delay-critical traffic, and resilience under congestion. Experimental results demonstrate that the model achieves microsecond-level latencies and near-zero packet loss for mission-critical flows, validating its suitability for future QoS-sensitive applications in 5G and beyond.