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Networks have become complex systems that combine various concepts, techniques, and technologies. As a consequence, modelling or simulating them now is extremely complicated and researchers massively resort to prototyping techniques. Mininet is the most popular tool when it comes to evaluate SDN propositions. Mininet allows to emulate SDN networks on a single computer but shows its limitations with resource intensive experiments as the emulating host may become overloaded. To tackle this issue, we propose Distrinet , a distributed implementation of Mininet over multiple hosts, based on LXD/LXC, Ansible, and VXLAN tunnels. Distrinet uses the same API than Mininet, meaning that it is compatible with Mininet programs. It is generic and can deploy experiments on Linux clusters (e.g., Grid'5000), as well as on the Amazon EC2 cloud platform.

International audience; 5G enhanced Mobile broadband (eMBB) aims to provide users with a peak data rate of 20 Gbps in the Radio Access Network (RAN). However, since most Congestion Control Algorithms (CCAs) rely on startup and probe phases to discover the bottleneck bandwidth, they cannot quickly utilize the available RAN bandwidth and adapt to fast capacity changes without introducing large delay increase, especially when multiple flows are sharing the same Radio Link Control (RLC) buffer. To tackle this issue, we propose RAPID, a RANaware proxy-based flow control mechanism that prevents CCAs from overshooting more than the available RAN capacity while allowing near optimal link utilization. Based on analysis of up-todate radio information using Multi-access Edge Computing (MEC) services and packet arrival rates, RAPID is able to differentiate slow interactive flows from fast download flows and allocate the available bandwidth accordingly. Our experiments with concurrent Cubic and BBR flows show that RAPID can reduce delay increase by a factor of 10 to 50 in both Line-of-Sight (LOS) and Non-LOS (NLOS) conditions while preserving high throughput.

International audience; More than ever, data networks have demonstrated their central role in the world economy, but also in the well-being of humanity that needs fast and reliable networks. In parallel, with the emergence of Network Function Virtualization (NFV) and Software Defined Networking (SDN), efficient network algorithms considered too hard to be put in practice in the past now have a second chance to be considered again. In this context, as new networks will be deployed and current ones get significant upgrades, it is thus time to rethink the network dimensioning problem with protection against failures. In this paper, we consider a path-based protection scheme with the global rerouting strategy in which, for each failure situation, there may be a new routing of all the demands. Our optimization task is to minimize the needed amount of bandwidth. After discussing the hardness of the problem, we develop two scalable mathematical models that we handle using both Column Generation and Benders Decomposition techniques. Through extensive simulations on real-world IP network topologies and on randomly generated instances, we show the effectiveness of our methods: they lead to savings of 40 to 48% of the bandwidth to be installed in a network to protect against failures compared to traditional schemes. Finally, our implementation in OpenDaylight demonstrates the feasibility of the approach. Its evaluation with Mininet shows that our solution provides sub-second recovery times, but the way it is implemented may greatly impact the amount of signaling traffic exchanged. In our evaluations, the recovery phase requires only a few tens of milliseconds for the fastest implementation, compared to a few hundreds of milliseconds for the slowest one.

International audience; In this paper, we introduce a novel dynamic controller assignment algorithm targeting connected vehicle services and applications, also known as Internet of Vehicles (IoV). The proposed approach considers a hierarchically distributed control plane, decoupled from the data plane, and uses vehicle location and control traffic load to perform controller assignment dynamically. We model the dynamic controller assignment problem as a multi-agent Markov game and solve it with cooperative multi-agent deep reinforcement learning. Simulation results using real-world vehicle mobility traces show that the proposed approach outperforms existing ones by reducing control delay as well as packet loss. Index Terms-Internet of Vehicles (IoV), Software Defined Networking (SDN), multi-agent deep reinforcement learning, controller assignment.

International audience; Terrestrial wireless infrastructure-based networks do not always guarantee that their resources will be shared uniformly by nodes in vehicular networks mostly due to the uneven and dynamic distribution of vehicles in the network as well as path loss effects. In this paper, we leverage multiple fifth-generation (5G) unmanned aerial vehicles (UAVs) to enhance network resource allocation among vehicles by positioning UAVs on-demand as "flying communication infrastructure". We propose a deep reinforcement learning (DRL) approach to determine the position of UAVs in order to improve the fairness and efficiency of network resource allocation while considering the UAVs' flying range, communication range, and limited energy resources. We use a parametric fairness function for resource allocation that can be tuned to reach different allocation objectives ranging from maximizing the total throughput of vehicles, maximizing minimum throughput, as well as achieving proportional band-width allocation. Simulation results show that the proposed DRL approach to UAV positioning can help improve network resource allocation according to the targeted fairness objective.

International audience; There has been a considerable increase in the demand for high quality mobile video streaming services, while at the same time, the video traffic volume is expected to grow exponentially. Consequently, maintaining high quality of experience (QoE) and saving network resources are becoming crucial challenges to solve. In this paper, we propose a name-based mobile streaming scheme that allows efficient video content delivery by exploiting a smart pulling mechanism designed for information-centric networks (ICNs). The proposed mechanism enables fast packet loss recovery by leveraging in-network caching and coding. Through an experimental evaluation of our mechanism over an open wireless testbed and the Internet, we demonstrate that the proposed scheme leads to higher QoE levels than classical ICN and TCP-based streaming mechanisms.

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.In this paper, 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. After discussing the hardness of the problem, we develop a scalable mathematical model that we handle using the Column Generation technique. Through extensive simulations on real-world IP network topologies and on random generated instances, we show the effectiveness of our method. Finally, our implementation in OpenDaylight demonstrates the feasibility of the approach and its evaluation with Mininet shows that technical implementation choices may have a dramatic impact on the time needed to reestablish the flows after a failure takes place.

International audience; Networks have become complex systems that combine various concepts, techniques, and technologies. As a consequence , modelling or simulating them is now extremely complicated and researchers massively resort to prototyping techniques. Among other tools, Mininet is the most popular when it comes to evaluate SDN propositions. It allows to emulate SDN networks on a single computer. However, under certain circumstances experiments (e.g., resource intensive ones) may overload the host running Mininet. To tackle this issue, we propose Distrinet, a way to distribute Mininet over multiple hosts. Distrinet uses the same API than Mininet, meaning that it is compatible with Mininet programs. Distrinet is generic and can deploy experiments in Linux clusters or in the Amazon EC2 cloud. Thanks to optimization techniques, Distrinet minimizes the number of hosts required to perform an experiment given the capabilities of the hosting infrastructure, meaning that the experiment is run in a single host (as Mininet) if possible. Otherwise, it is automatically deployed on a platform using a minimum amount of resources in a Linux cluster or with a minimum cost in Amazon EC2.

International audience; 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.

Information-centric networking (ICN) is a promising solution for most of Internet applications where the content represents the core of the application. However, the proposed solutions for the ICN architecture are associated with many complexities including pervasive caching in the Internet and incompatibility with legacy IP networks, so the deployment of ICN in real networks is still an open problem. In this paper, we propose a backward-compatible ICN architecture to address the caching issue in particular. The key idea is implementing edge caching in ICN, using a coalition of end clients and edge servers. Our solution can be deployed in IP networks with HTTP requests. We performed a trace-driven simulation for analyzing peer-assisted information-centric networking (PICN) benefits using IRCache and Berkeley trace files. The results show that on average, PICN decreases the latency for 78% and increases the content retrieval speed for 69% compared with a direct download from the original Web servers. When comparing PICN with a solution based on central proxy servers, we show that the hit ratio obtained using a small cache size in each PICN client is almost 14% higher than the hit ratio obtained with a central proxy server using an unlimited cache storage.

International audience; We have provided critical evaluations of new potential testbeds for the evaluation of SDN-based WMNs. We evaluated the R2Lab wireless testbed platform at INRIA Sophia-Antipolis, France. This testbed has 37 customisable wireless devices in an anechoic chamber for reproducible research in wireless WiFi and 4G/5G networks. Our work presents the first initial evaluation of the testbed for wireless multi-hop experiments , using traditional WMN routing protocols. Our results demonstrate the potential for SDN experiments. We believe this is an important contribution in its own right, since experimental validation is a key research methodology in this context, and trust in the validity of experimental results is absolutely critical.

International audience; Experimentation is an essential step for realistic evaluation of wireless network protocols. The evaluation methodology entails controllable environment conditions and a rigorous and efficient experiment control and orchestration for a variety of scenarios. Existing experiment control tools such as OMF often lack in efficiency in terms of resource management and rely on abstractions that hide the details about the wireless setup. In this paper, we propose nepi-ng, an efficient experiment control tool that leverages job oriented programming model and efficient single-thread execution of parallel programs using asyncio. nepi-ng provides an efficient and modular fine grain synchronization mechanism for networking experiments with light software dependency footprint. We present and discuss our design choices and compare to the state of the art tools, mainly OMF.

International audience; Complex inter-connections of virtual functions form the so-called Service Function Chains (SFCs) deployed in the Cloud. Such service chains are used for critical services like e-health or autonomous transportation systems and thus require high availability. Respecting some availability level is hard in general, but it becomes even harder if the operator of the service is not aware of the physical infrastructure that will support the service, which is the case when SFCs are deployed in multi-tenant data centers. In this paper, we propose an algorithm to solve the placement of topology-oblivious SFC demands such that placed SFCs respect availability constraints imposed by the tenant. The algorithm leverages Fat-Tree properties to be computationally doable in an online manner. The simulation results show that it is able to satisfy as many demands as possible by spreading the load between the replicas and enhancing the network resources utilization.

International audience; In this paper, we build upon our prior work on D2-ITS, a flexible and extensible framework to dynamically distribute network control to enable message dissemination in Intelligent Transport Systems (ITS), and extend it with handover and load balancing capabilities. More specifically, D2-ITS' new handover feature allows a controller to automatically "delegate" control of a vehicle to another controller as the vehicle moves. Control delegation can also be used as a way to balance load among controllers and ensure that required application quality of service is maintained. We showcase D2-ITS' handover and load-balancing features using the Mininet-Wifi network simula-tor/emulator. Our preliminary experiments show D2-ITS' ability to seamlessly handover control of vehicles as they move.

International audience; In this paper, we propose a network planning and provisioning framework that optimizes deployment cost in C-RAN based 5G networks. Our framework is based on a Mixed Integer Quadratically Constrained Programming (MIQCP) model which optimizes " virtualized " 5G service chain deployment cost while performing adequate provisioning to address user demand and performance requirements. We use two realistic scenarios to showcase that our framework can be applied to different types of deployments and discuss the computational cost and scalability of our solution.

International audience; Ultra Dense Networks (UDNs) are a natural deployment evolution for handling the tremendous traffic increase related to the emerging 5G services, especially in urban environments. However, the associated infrastructure cost may become prohibitive. The evolving paradigm of network slicing can tackle such a challenge while optimizing the network resource usage, enabling multi-tenancy and facilitating resource sharing and efficient service-oriented communications. Indeed, network slicing in UDN deployments can offer the desired degree of customization in both vanilla Radio Access Network (RAN) designs, but also in the case of disaggregated multi-service RANs. In this article, we devise a novel multi-service RAN environment, i.e., RAN runtime, capable to support slice orchestration procedures and to enable flexible customization of slices as per tenant needs. Each network slice can exploit a number of services, which can either be dedicated or shared between multiple slices over a common RAN. The novel architecture we present concentrates on the orchestration and management systems. It interacts with the RAN modules, through the RAN runtime, via a number of new interfaces enabling a customized dedicated orchestration logic for each slice. We present results for a disaggregated UDN deployment where the RAN runtime is used to support slice-based multi-service chain creation and chain placement, with an auto-scaling mechanism to increase the performance.

International audience; —New applications where anyone can broadcast high quality video are becoming very popular. ISPs may take the opportunity to propose new high quality multicast services to their clients. Because of its centralized control plane, Software Defined Networking (SDN) enables the deployment of such a service in a flexible and bandwidth-efficient way. But deploying large-scale multicast services on SDN requires smart group membership management and a bandwidth reservation mechanism with QoS guarantees that should neither waste bandwidth nor impact too severely best effort traffic. In this paper, we propose; (1) a scalable multicast group management mechanism based on a Network Function Virtualization (NFV) approach for Software Defined ISP networks to implement and deploy multicast services on the network edge, and (2) the Lazy Load Balancing Multicast (L2BM) routing algorithm for sharing the core network capacity in a friendly way between guaranteed-bandwidth multicast traffic and best-effort traffic and that does not require costly real-time monitoring of link utilization. We have implemented the mechanism and algorithm, and evaluated them both in a simulator and a testbed. In the testbed, we experimented the group management at the edge and L2BM in the core with an Open vSwitch based QoS framework and evaluated the performance of L2BM with an exhaustive set of experiments on various realistic scenarios. The results show that L2BM outperforms other state-of-the art algorithms by being less aggressive with best-effort traffic and accepting about 5-15% more guaranteed-bandwidth multicast join requests.

International audience; We propose D2-ITS, a flexible and extensible framework to dynamically distribute network control to enable message dissemination in Intelligent Transport Systems (ITS). By decoupling the control- from the data plane, D2-ITS leverages network programmability to address ITS scalability, delay intolerance and decentralization. It uses a distributed control plane based on a hierarchy of controllers that can dynamically adjust to environment and network conditions in order to satisfy ITS application requirements. We demonstrate the benefits of D2-ITS through a proof-of-concept prototype using the ns-3 simulation platform. Results indicate lower message delivery latency with minimal additional overhead.

International audience; Software-Defined Wireless Networking (SDWN) is an emerging approach based on decoupling radio control functions from the radio data plane through programmatic interfaces. Despite diverse ongoing efforts to realize the vision of SDWN, many questions remain open from multiple perspectives such as means to rapid prototype and experiment candidate software solutions applicable to real world deployments. To this end, emulation of SDWN has the potential to boost research and development efforts by re-using existing protocol and application stacks while mimicking the behavior of real wireless networks. In this article, we provide an in-depth discussion on that matter focusing on the Mininet-WiFi emulator design to fill a gap in the experimental platform space. We showcase the applicability of our emulator in an SDN wireless context by illustrating the support of a number of use cases aiming to address the question on how far we can go in realistic SDWN experiments, including comparisons to the results obtained in a wireless testbed. Finally, we discuss the ability to replay packet-level and radio signal traces captured in the real testbed towards a virtual yet realistic emulation environment in support of SDWN research.

International audience; With MIMO, Wi-Fi led the way to the adoption of antenna array signal processing techniques for fine-grained localization using commodity hardware. These techniques, previously exclusive to specific domains of applications, will spur interest to reach beyond localization, and now allow to consider estimating the device’s orientation in space, that once required other sources of information. Wi-Fi’s popularity and the availability of metrics related to channel propagation (CSI), makes it a candidate readily available for experimentation. Accordingly, we propose the ORION system to estimate the orientation (heading and yaw) of a MIMO Wi-Fi equipped object, relying on a joint estimation of the angle of arrival and the angle of departure. Although the CSI’s phase data is plagued by several phase inconsistencies, we demonstrate that an appropriate phase compensation strategy significantly improves estimation accuracy. By feeding the estimation to a Kalman filter, we further improve the overall system accuracy, and lay the ground for an efficient tracking. Our technique allows estimating orientations within high precision (millimeter-level).

International audience; New applications where anyone can broadcast video are becoming very popular on smartphones. With the advent of high definition video, ISP providers may take the opportunity to propose new high quality broadcast services to their clients. Because of its centralized control plane, Software Defined Networking (SDN) seems an ideal way to deploy such a service in a flexible and bandwidth-efficient way. But deploying large scale multicast services on SDN requires smart group membership management and a bandwidth reservation mechanism to support QoS guarantees that should neither waste bandwidth nor impact too severely best effort traffic. In this paper, we propose a Network Function Virtualization based solution for Software Defined ISP networks to implement scalable multicast group management. Then, we propose the Lazy Load balancing Multicast (L2BM) routing algorithm for sharing the network capacity in a friendly way between guaranteed-bandwidth multicast traffic and best-effort traffic. Our implementation of the framework made on Floodlight controllers and Open vSwitches is used to study the performance of L2BM.

International audience; Owing to the rapid growth in high-quality video streaming over the Internet, preserving high-level robustness against data loss and low latency, while maintaining higher data transmission rates, is becoming an increasingly important issue for high-quality real-time delay-sensitive streaming. In this paper, we propose a low latency, low loss streaming mechanism, L4C2, convenient for high-quality delay-sensitive streaming. With L4C2, nodes in the network estimate the acceptable delay and packet loss probability in their uplinks, aiming at retrieving lost data packets from in-network cache and/or coded data packets using in-network coding within an acceptable delay, by extending the Content-Centric Networking (CCN) approach. Further, L4C2 naturally provides multiple paths and multicast technologies to efficiently utilize network resources while sharing network resources fairly with competing data flows by adjusting the video quality when necessary. We validate through comprehensive simulations that L4C2 achieves a high success probability of data transmission considering the acceptable one-way delay, and higher QoE while suppressing the interest and redundant data traffic than the proposed multipath congestion control mechanism in CCN.

This papers introduces Snipe, a novel system offering joint localization and range extensions for LPWANs. Although LPWAN systems such as Long Range (LoRa) are designed to achieve high communication range with low energy consumption, they suffer from fading in obstructed environments with dense multipath components, and their localization system is sub-par in terms of accuracy. In this work, MIMO techniques are leveraged to achieve a higher signal-to-noise ratio at both the end device and the gateway while providing an opportunistic accurate radar-based system for localization with limited additional cost.

International audience; When deploying network service function chains the focus is usually given on metrics such as the cost, the latency, or the energy and it is assumed that the underlying cloud infrastructure provides resiliency mechanisms to handle with the disruptions occurring in the physical infrastructure. In this position paper, we advocate that while usual performance metrics are essential to decide on the deployment of network service function chains, the notion of resiliency should not be neglected as the choice of virtual-to-physical placement may dramatically improve the ability of the service chains to handle with failures of the infrastructure without requiring complex resiliency mechanisms.

International audience; Software-Defined Networking (SDN) abstracts low- level network functionalities to simplify network management and reduce costs. The OpenFlow protocol implements the SDN concept by abstracting network communications as flows to be processed by network elements. In OpenFlow, the high-level policies are translated into network primitives called rules that are distributed over the network. While the abstraction offered by OpenFlow allows to potentially implement any policy, it raises the new question of how to define the rules and where to place them in the network while respecting all technical and administrative requirements. In this paper, we propose a comprehensive study of the so-called OpenFlow rules placement problem with a survey of the various proposals intending to solve it. Our study is multi-fold. First, we define the problem and its challenges. Second, we overview the large number of solutions proposed, with a clear distinction between solutions focusing on memory management and those proposing to reduce signaling traffic to ensure scalability. Finally, we discuss potential research directions around the OpenFlow rules placement problem.

International audience; Content-Centric Networks (CCNs) are fundamental evolutionary technologies that promise to form the cornerstone of the future Internet. The information flow in these networks is based on named data requesting, in-network caching, and forwarding -- which are unique and can be independent of IP routing. As a result, common IP-based network tools such as ping and traceroute can neither trace a forwarding path in CCNs nor feasibly evaluate CCN performance. We propose "contrace," a network tool for CCNs (particularly, CCNx implementation running on top of IP) that can be used to investigate 1) the Round-Trip Time (RTT) between content forwarder and consumer, 2) the states of in-network cache per name prefix, and 3) the forwarding path information per name prefix. We report a series of experiments conducted using contrace on a CCN topology created on a local testbed and the GEANT network topology emulated by the Mini-CCNx emulator. The results confirm that contrace is not only a useful tool for monitoring and operating a network, but also a helpful analysis tool for enhancing the design of CCNs. Further, contrace can report the number of received interests per cache or per chunk on the forwarding routers. This enables us to estimate the content popularity and design more effective cache control mechanisms in experimental networks.

International audience; 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 has not significant impact on performances as long as packets are delivered to their final destination decided by 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 loose routing policies. We show that the general problem is NP-hard and propose a polynomial time heuristic, called OFFICER, that aims to maximize the amount of carried traffic in under-provisioned networks. Our numerical evaluation on four different topologies show that exploiting various paths allows to increase the amount of traffic supported by the network without significantly increasing the path length.

accepted in IEEE Communications Surveys & Tutorials; International audience; The idea of programmable networks has recently re-gained considerable momentum due to the emergence of the Software-Defined Networking (SDN) paradigm. SDN, often referred to as a ''radical new idea in networking'', promises to dramatically simplify network management and enable innovation through network programmability. This paper surveys the state-of-the-art in programmable networks with an emphasis on SDN. We provide a historic perspective of programmable networks from early ideas to recent developments. Then we present the SDN architecture and the OpenFlow standard in particular, discuss current alternatives for implementation and testing of SDN-based protocols and services, examine current and future SDN applications, and explore promising research directions based on the SDN paradigm.

International audience; We present the Direct Code Execution (DCE) environment for ns-3, notable for being the first free, open source framework for integrating Linux kernel and application code within a leading discrete-event network simulator. This new approach has many potential advantages over virtual machine-based frameworks in terms of realism, reproducibility, avoidance of real-time execution constraints, configuration management and ability to debug a network-wide experiment from a single address space using common debugging tools. We provide an overview of DCE and illustrate some key features of this framework with two use cases, one involving thttpd, an HTTP server implementation, and another one involving the udp-perf traffic generator.

International audience; We describe the first capability, to our knowledge, to execute nearly unmodified applications and Linux kernel code in the context of a widely-used open source discrete event networking simulator (ns-3). We propose Direct Code Execution (DCE), a framework that dramatically increases the number of available protocol models and realism available for ns-3 simulations. DCE meets the goals recently proposed for fully reproducible networking research and runnable papers, with the added benefits of 1) the ability of completely deterministic reproducibility, 2) the scalability that simulation time dilation offers, 3) capabilities supporting automated code coverage analysis, and 4) improved debuggability via execution within a single address space. In this paper, we describe in detail DCE, report on packet processing benchmark and showcase key features of the framework with different use cases. Next, we reproduce a previously published Multipath TCP (MPTCP) experiment and highlight how code coverage testing can be automated by showing results achieving 55-86% coverage of the MPTCP implementation. Then we demonstrate how network stack debugging can be easily performed and reproduced across a distributed system. Our first benchmarks are promising and we believe this framework can benefit the network community by enabling realistic, reproducible experiments and runnable papers.

International audience; Network researchers rely on a wide variety of experimentation platforms, ranging from simulators to emulators and live testbeds, to validate new ideas. Many experiment management frameworks have been created to ease up the complexity and time cost of deploying experiments on different platforms. However, providing flexible deployment capabilities for arbitrary platforms remains a challenging problem. In this work we propose an experiment controller architecture based on event scheduling, designed to enable flexible experiment deployment on diverse platforms. This architecture is capable of handling arbitrary deployment dependencies , both imposed by user requirements and by platform restrictions. It additionally enables flexible resource provi-sioning, at any point in time during experiment execution, and flexible experiment monitoring events.

International audience; PlanetLab testbed is widely used to evaluate protocols and applications under realistic Internet conditions, but this realism comes at the cost of uncontrolled topology and traffic behavior. The use of overlay networks on PlanetLab can solve this problem by giving more control to the experimenter. However, manually creating such overlays is far from simple, and existing solutions are either not available for all PlanetLab nodes, or lack support for low level overlays. Deployment and customization of overlay architectures are also poorly supported. In this paper we present a flexible solution to support overlay networks on Plan-etLab, providing deployment automation, tunneling, routing, and traffic shaping capabilities. By building our solution into NEPI, a general framework for network experimentation, which automates design, deployment, and management of experiments, we simplify the complexity of building overlays on PlanetLab, and foster reusability and extensibility though NEPI's modular structure.

International audience; Simulation is often used for the evaluation of new network protocols and architectures. In order to perform more realistic simulations , modern simulators such as ns-3 integrate more detailed models and even support direct execution of real protocol code. However, such complex models require more computational and memory requirements. In this paper, we study the feasibility of a hybrid approach based on distributing a complex simulation scenario on several nodes in a grid network. We show that by exploiting the real time operation of the ns-3 simulator, it is possible to map such complex scenarios on grid nodes. We run experiments to define the operational zone in which the obtained results are accurate. We also propose a basic mapping algorithm to distribute a simulation scenario in several nodes.

International audience; We address the issue of asserting the accuracy of coordinates advertised by nodes of Internet coordinate systems during distance estimations. Indeed, some nodes may lie deliberately about their coordinates to mount various attacks against applications and overlays. Our proposed method consists in two steps: 1) establish the correctness of a node's claimed coordinate (which leverages our previous work on securing the coordinates embedding phase using a Surveyor infrastructure); and 2) issue a time limited validity certificate for each verified coordinate. Validity periods are computed based on an analysis of coordinate inter-shift times observed on PlanetLab, and shown to follow a long-tail distribution (lognormal distribution in most cases, or Weibull distribution otherwise). The effectiveness of the coordinate certification method is validated by measuring the impact of a variety of attacks on distance estimates.

International audience; In this paper, we present an efficient message delivery mechanism that enables distribution/dissemination of messages in an internet connecting heterogeneous networks and prone to disruptions in connectivity. We call our protocol MeDeHa (pronounced “medea”) for Message Delivery in Heterogeneous, Disruptionprone Networks. MeDeHa is complementary to the IRTF's Bundle Architecture: while the Bundle Architecture provides storage above the transport layer in order to enable interoperability among networks that support different types of transport layers, MeDeHa stores data at the link layer addressing heterogeneity at lower layers (e.g., when intermediate nodes do not support higher-layer protocols). MeDeHa also takes advantage of network heterogeneity (e.g., nodes supporting more than one network) to improve message delivery. For example, in the case of IEEE 802.11 networks, participating nodes may use both infrastructure- and ad hoc modes to deliver data to otherwise unavailable destinations. Another important feature of MeDeHa is that there is no need to deploy special-purpose nodes such as message ferries, data mules, or throwboxes in order to relay data to intended destinations, or to connect to the backbone network wherever infrastructure is available. The network is able to store data destined to temporarily unavailable nodes for some time depending upon existing storage as well as quality-of-service issues such as delivery delay bounds imposed by the application. We evaluate MeDeHa via simulations using indoor scenarios (e.g. convention centers, exposition halls, museums etc.) and show significant improvement in delivery ratio in the face of episodic connectivity. We also showcase MeDeHa's support for different levels of quality-of-service through traffic differentiation and message prioritization.

We consider the medium access control (MAC) layer for very high-speed wireless LANs, which is designed to support rich multimedia applications such as high-definition television. In such networks, the physical (PHY) layer data rate is proposed to exceed 216 Mbps. The legacy MAC layer, however, greatly restricts the performance improvement due to its overhead. It has been shown that MAC utilizes less than 20% of the transportation ability provided by the PHY layer. To mitigate this inefficiency, we propose an aggregation with fragment retransmission (AFR) scheme, which supports transmissions of very large frames and partial retransmissions in the case of errors. Aggregation allows for increased performance despite per-transmission overhead while partial retransmission alleviates the risk of losing the entire frame. Extensive simulations show that AFR fundamentally outperforms the legacy MAC protocol. It is particularly effective for applications with high data rates and large packet sizes such as HDTV and high-rate UDP traffic. For applications with very low data rates and small packet sizes such as voice over IP, AFR performs slightly better.

International audience; We focus on the optimization of real-time multimedia transmission over 802.11-based ad hoc networks. In particular, we propose a simple and efficient cross-layer mechanism that considers both the channel conditions and characteristics of the media for dynamically selecting the transmission mode. This mechanism called media-oriented rate selection algorithm (MORSA) targets loss-tolerant applications such as VoD that do not require full reliable transmission. We provide an evaluation of this mechanism for MANETs using simulations with NS and analyze the video quality obtained with a fine-grain scalable video encoder based on a motion-compensated spatiotemporal wavelet transform. Our results show that MORSA achieves up to 4 Mbps increase in throughput and that the routing overhead decreases significantly. Transmission of a sample video flow over an 802.11a wireless channel has been evaluated with MORSA. Important improvement is observed in throughput, latency, and jitter while keeping a good level of video quality.

International audience; Multicast applications and network monitors can potentially benefit from the ability to infer the loss rates along links within a multicast tree. Estimators, known generically by MINC, or multicast inference of network characteristics, have been developed to provide this ability. They consider multicast data packets to be probes, and conduct inference based upon reports of which probes reached each receiver. In practice, gathering reports from receivers in real time is a non-trivial task that presents scaling problems as the number of receivers increases. Prior work has led to an extension of the RTP data transport protocol to permit receivers to report per-probe information in packets known as RTCP XR packets. This paper demonstrates how MINC inference can, in fact, be conducted using only a default RTP packet format known as RTCP RR. RTCP RR packets contain summary information rather than per-probe information. They thus offer bandwidth savings, although this comes at the expense of an increase in estimator convergence time. Furthermore, this technique can be used by the observer of any standard RTP session, whereas estimation based upon per-probe information is only possible when a session explicitly employs the extended reporting format.

International audience; This paper introduces source-channel adaptive rate control (SARC), a new congestion control algorithm for layered video transmission in large multicast groups. In order to solve the well-known feedback implosion problem in large multicast groups, we first present a mechanism for filtering RTCP receiver reports sent from receivers to the whole session. The proposed filtering mechanism provides a classification of receivers according to a predefined similarity measure. An end-to-end source and FEC rate control based on this distributed feedback aggregation mechanism coupled with a video layered coding system is then described. The number of layers, their rate, and their levels of protection are adapted dynamically to aggregated feedbacks. The algorithms have been validated with the NS2 network simulator.

International audience; In this paper we propose a novel algorithm, namely Multi-Objective Placement (MOP), for the efficient placement of Virtualized Network Function (VNF) chains in future 5G systems. Real datasets are used to evaluate the performance of MOP in terms of acceptance ratio and embedding time when placing the time critical radio access network (RAN) functions as a chain. In addition, we rely on a realistic infrastructure topology to assess the performance of MOP with two main objectives: maximizing the number of base stations that could be embedded in the Cloud and load balancing. The results reveal that the acceptance ratio of embedding RAN functions is only 5% less than the one obtained with the optimal solution for the majority of considered scenarios, with a speedup factor of up to 2000 times.