SLICES-RI is being developed as a scientific instrument, following established methodologies and best practices from the scientific community. This approach is increasingly essential to address the accelerating pace of data-driven research, which continuously generates a deluge of publications. The core mission of a scientific instrument is to provide a standardized and trusted reference, enabling direct performance comparisons of algorithms and ensuring reproducibility — thereby simplifying and strengthening the peer review process. To meet these goals, SLICES-RI adopts an intent-based design and generates tailored Blueprints for specific scientific questions. While it does not aim to be exhaustive, this approach significantly reduces the complexity involved in designing and executing experiments. In this presentation, we share the current deployment status of SLICES-RI as it entered its pre-operational phase. We illustrate its capabilities through the Post-5G and Federated Learning Blueprints. Additionally, we highlight MRS/DMI, a key feature of SLICES-RI, which offers an advanced data management framework aligned with the FAIR principles and fully integrated into the experimental workflow.

Effective scheduling of software updates is a significant challenge in network operations and management, particularly when considering specific performance and security requirements. This paper focuses on the synthesis of such software updates in the context of emerging virtualized and softwarized networks, such as 5G network infrastructures, with the objective of ensuring vulnerability avoidance and congestion freedom at any time during the updates. We formalize the update synthesis problem and propose an algorithmic solution, called Eagle, that exploits formal methods and mixed integer linear programming, to achieve optimal solutions. We then complement it with a greedy algorithm to support faster computation. We exemplify our framework considering an implementation of a 5G architecture, as the one described in the ETSI 5123 standard, and which relies on kubernetes. Finally, we evaluate our approach through a large range of realistic ISP topologies from the Topology Zoo dataset, and we also perform extensive experiments on our kubernetes cluster, where we execute the software update sequences generated by our tool. This allows us to discuss the scalability of our approach along with its practical applicability.

Experimental research in Post-5G involves complex interactions between software, hardware, and protocols. Therefore, it is crucial to develop solutions that allow researchers to conduct their experiments in a reproducible manner. To support this need, the EU SLICES Research Infrastructure (RI) provides a scientific instrument that encompasses all the needs for Post-5G experimental research. The facility is currently being built to enable experimentation with state-of-the-art resources in various fields. SLICES-RI is intent-driven and facilitates the entire lifecycle of thought experiments. This is achieved by enabling reproducible deployment of experiments over the infrastructure using blueprints and by systematically collecting and archiving all outputs through a clear and structured methodology for experimentation. For this demonstration, we focus on the Post-5G part of the facility and will showcase how the entire lifecycle of such an experiment is orchestrated using the tools and functionalities developed. We will showcase blueprints for deploying a cloud-native 5G core and a split 7.2 radio network using open-source software in a fully reproducible manner, with the results being automatically archived and published using the SLICES metadata model. The reproducibility, deployment options, experimenter control capabilities, and access to the collected results will be highlighted.

To handle the ever growing demand of resource intensive experiments distributed, network emulation tools such as Mininet and Maxinet have been proposed. They automatically allocate experimental resources. In this work, we show that resources are poorly allocated, leading to resource overloading and hence to dubious experimental results.This is why we propose and implement a new placement module for distributed emulation. Our algorithms take into account both link and node resources and minimize the number of physical hosts needed to carry out the emulation. Through extensive numerical evaluations, simulations, and actual experiments, we show that our placement methods outperform existing ones and allowing to re-establish trust in experimental results.

ISP networks are taking a leap forward thanks to emerging technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV). Efficient algorithms considered too hard to be put in practice on legacy networks now have a second chance to be considered again. In this context, we rethink the ISP network dimensioning problem with protection against Shared Risk Link Group (SLRG) failures. We consider a path-based protection scheme with a global rerouting strategy in which, for each failure situation, we may have a new routing of all the demands. Our optimization task is to minimize the needed amount of bandwidth. We develop a scalable mathematical model that we handle using the Column Generation technique. We show the effectiveness of our methods and demonstrate the feasibility of our approach using Mininet.

A prominent portion of the traffic carried by Internet Service Providers (ISPs) is delivered by Content Delivery Networks (CDNs), the vast majority being video traffic served over HTTP adaptive streaming. CDNs often deploy their own caches at ISPs in addition to the servers deployed in their own premises. The ability of user devices to use two network interfaces simultaneously is instrumental in improving the quality of access, and this is enabled by multipath (MP) transport protocols such as MPTCP. This ability however precludes the use of caches in access networks. This article investigates the operational points obtained from the combination of MP routing with different cache locations. By modelling the optimization problems of both actors, ISPs and CDN, and designing a simulation testbed using a mobile operator topology, we identify for which metrics (video bitrate, acceptance rate, link congestion) and in which conditions (cache locations, multipath enabled or not, type of video content), the new operational points are interesting. Under realistic video patterns, multipath allows to improve served bitrates over all request types by up to 40% depending on the load.

To optimize routing of flows in datacenters, SDN controllers receive a packet-in message whenever a new flow appears in the network. Unfortunately, flow arrival rates can peak to millions per second, impairing the ability of controllers to treat them on time. Flow scheduling copes with such sheer numbers by segmenting the traffic between elephant and mice flows and by treating elephant flows in priority, as they disrupt short lived TCP flows and create bottlenecks. We propose a learning algorithm called SOFIA and able to perform optimal online flow segmentation. Our solution, based on stochastic approximation techniques, is implemented at the switch level and updated by the controller, with minimal signaling over the control channel. SOFIA is blind, i.e., it is oblivious to the flow size distribution. It is also adaptive, since it can track traffic variations over time. We prove its convergence properties and its message complexity. Moreover, we specialize our solution to be robust to traffic classification errors. Extensive numerical experiments characterize the performance of our approach in vitro. Finally, results of the implementation in a real OpenFlow controller demonstrate the viability of SOFIA as a solution in production environments.

The Software-Defined Networking approach permits to realize new policies. In OpenFlow in particular, a controller decides on behalf of the switches which forwarding rules must be installed and where. However with this flexibility comes the challenge of the computation of a rule allocation matrix meeting both high-level policies and the network constraints such as memory or link capacity limitations. Nevertheless, in many situations (e.g., data-center networks), the exact path followed by packets does not severely impact performances as long as packets are delivered according to the endpoint policy. It is thus possible to deviate part of the traffic to alternative paths so to better use network resources without violating the endpoint policy. In this paper, we propose a linear optimization model of the rule allocation problem in resource constrained OpenFlow networks with relaxing routing policy. We show that the general problem is NP-hard and propose a polynomial time heuristic, called OFFICER, which aims to maximize the amount of carried traffic in under-provisioned networks. Our numerical evaluation on four different topologies shows that exploiting various paths allows to increase the amount of traffic supported by the network without significantly increasing the path length.

The future Internet has been a hot topic during the past decade and many approaches towards this future Internet, ranging from incremental evolution to complete clean slate ones, have been proposed. One of the proposition, LISP, advocates for the separation of the identifier and the locator roles of IP addresses to reduce BGP churn and BGP table size. Up to now, however, most studies concerning LISP have been theoretical and, in fact, little is known about the actual LISP deployment performance. In this paper, we fill this gap through measurement campaigns carried out on the LISP Beta Network. More precisely, we evaluate the performance of the two key components of the infrastructure: the control plane (i.e., the mapping system) and the interworking mechanism (i.e., communication between LISP and non-LISP sites). Our measurements highlight that performance offered by the LISP interworking infrastructure is strongly dependent on BGP routing policies. If we exclude misconfigured nodes, the mapping system typically provides reliable performance and relatively low median mapping resolution delays. Although the bias is not very important, control plane performance favors USA sites as a result of its larger LISP user base but also because European infrastructure appears to be less reliable.

Information-centric networking (ICN) leverages content demand redundancy and proposes in-network caching to reduce network and servers load and to improve quality of experience. In this paper, we study the interaction between in-network caching of ICN and Additive Increase Multiplicative Decrease (AIMD) end-to-end congestion control with a focus on how bandwidth is shared, as a function of content popularity and cache provisioning. As caching shortens AIMD feedback loop, the download rate of AIMD is impacted. Supported by an analytical model based on Discriminatory Processor Sharing and real experiments, we observe that popular contents benefit from caching and realize a shorter download time at the expense of unpopular contents, which see their download time inflated by a factor bounded by 1/1-ρ where ρ is the network load. This bias can be removed by redefining congestion control to be delay independent or by over-provisioning link capacity at the edge so that to compensate for the greediness of popular contents.

Content-Centric Networking (CCN) is designed for efficient content dissemination and supports caching contents on the path from content providers to content consumers to improve user experience and reduce costs. However, this strategy is not optimal inside a domain. In this paper, we propose a solution to improve caching in CCN using a Software-Defined Networking approach.

The sustained growth of the global routing table is exerting an economical strain on ISPs by requiring untimely router upgrades. Notably, it has been speculated that the growth rate of router FIBs is surpassing that of its supporting technology and that the deployment of IPv6 is only to make matters worse. In this paper, we propose LISP-MPS, an architecture based on LISP, that isolates the intra-domain routing of an Autonomous System (AS) from its inter-domain routing. The resulting separation implies the decrease of backbone routing table sizes and enables an AS to control the forwarding of traffic inside its network. For a seamless, cost effective, and incremental deployment, LISP-MPS leverages iBGP to implement the LISP mapping system functionality with minimal modification to a small subset of deployed equipment. Finally, an analysis of realistic topologies shows that, despite changing how packets transit a network, the architecture does not lose resilience to failures. Moreover, we show that it can be a viable alternative to BGP/MPLS deployments due to its low implementation cost.

Routing diversity has been identified as essential for network robustness and traffic engineering. The Internet possesses by its very nature a large path diversity. However this diversity cannot be fully exploited due to BGP limitations, which only keeps one single route for each available prefix. Despite some previous works in the area, no operational and non-disruptive architecture have been proposed yet to allow the networks to better exploit Internet path diversity. This paper proposes one step in this direction, focusing on the interconnection between an Autonomous System (AS) and its Internet Service Provider (ISP). We propose the use of a so-called “Map-and-Encap” scheme to bypass current BGP limitations in order to use arbitrary paths. With this scheme, an ISP may propose its rich path diversity (at least partially) to its customers, in order to perform advanced traffic engineering (e.g. fast recovery, load balancing...) based on richer and more flexible path selection policies (e.g., considering price, performance or stability of routes). To assess the potential benefits of the proposed architecture, we evaluate the potential route diversity that a Tier 1 may offer to its stub clients, based on different possible route selection policies (i.e. which routes are offered to its customers). We also analyze the overhead that is created at the control-plane (routing updates received by the mapping database) and that may impact the data-plane (path changes that may be caused by some route withdrawals/updates). Our evaluation shows that the increase in diversity has a controllable and acceptable overhead. It also gives some insights into efficient deployment strategies.

Nowadays Internet is ubiquitous resulting in an increasing path diversity and content duplication. However, while content can be retrieved from many different places, the paths to those places are not equivalent. Indeed, some paths offer better bandwidth while others are less expensive or more stable. In addition, a new range of applications is sensitive to the performance of the paths that carry their traffic. To support this evolution of the Internet, we propose ISP-Driven Informed Path Selection (IDIPS). Any ISP can easily deploy IDIPS to help its customers to select the paths that best meet their requirements in order to reach their content. IDIPS helps in this selection through pro-active measurements and ISP-defined policies. IDIPS is scalable and can support thousands of clients. IDIPS is also flexible and can thus be used by the ISP to optimize its routing decisions to take the performance of its inter-domain links into account.

During the last years, some operators have expressed concerns about the continued growth of the BGP routing tables in the default-free zone. Several proposed solutions for this issue are centered around the idea of separating the network node's identifier from its topological location. Among the existing proposals, the Locator/ID Separation Protocol (LISP) has seen important development and implementation effort. LISP relies on a mapping system to provide bindings between locators and identifiers. The mapping system is a critical protocol component, and its design is still an open issue. In this paper we present a new mapping system: LISP-TREE. It is based on DNS and has a similar hierarchical topology: blocks of identifiers are assigned to the levels of the hierarchy by following the current IP address allocation policies. We also present measurement-driven simulations of mapping systems' performance, assuming a deployment of LISP in the current Internet.

During the past ten years, we have seen the emergence of a set of applications requiring more and more quality of service (QoS). For instance, IPTV needs large bandwidth and delays as lows as possible. Further, while previously a content was located in a single place, it is, nowadays, frequent that the content is replicated among a set of servers located anywhere on five continents or even among users themselves. Perfect examples of this are peer-to-peer (P2P) applications and FTP mirrors. In addition, multihoming, i.e., the ability of having different connections to Internet potentially through different providers, is becoming more and more popular [1, 2]. Finally, network level protocols such as SHIM6 or LISP must often choose the best path among a list of highly disparate paths according to traffic engineering or policies considerations (see discussions on IETF mailing lists). This situation leads to more complexity in ensuring QoS to the user. We have now to maximize the QoS perceived by the user based on a set of highly disparate paths. In addition, in many new applications, path selection and QoS are ensured at the application layer resulting in an ineffective network level resources use. Today, although many of measurements techniques have been developed within the IPPM working group of the IETF, an application that needs to select a path or a server must implement its own measurement system to obtain data to perform its selection. Thus, several applications running on the same host or in the same campus will probably perform almost the same kind of measurements. Duplicating those measurements is not the appropriate solution. This work was partially supported by the Europeanfounded