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International audience; Ray Tracing is an electromagnetic wave propagation modeling approach used for accurate generation of Quality of Service (QoS) maps in mobile networks. Due to its complexity, current implementation of Ray Tracing fails to generate such maps in wide areas. In this paper, we propose an optimization to Ray Tracing able to accurately generate QoS maps in a reasonable time. Using a site-specific ray launching technique and an alternative to the reception test process, we divide by almost 1200 the execution time of Ray Tracing with less than 2% of memory usage as compared to baseline solutions.

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 RAN-aware 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-to-date 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 simulation and experimentation results 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 in both 4G and 5G environments.

International audience; Emulation has become a popular approach for the validation and evaluation of network research. It provides researchers with a contained, customizable, and scalable testing environment, which can be easily packaged and published for potential readers to reproduce their results. However, as the network components are only virtual, emulation lacks the inherent realism of physical testbeds. In light of this, monitoring specific metrics of the emulated network has been proposed as a solution to mitigate to some degree inaccuracies caused by emulation. While this is not difficult to implement in a single-machine setting (e.g. with Mininet), monitoring is limited by the lack of time synchronization in scenarios where the emulation is distributed over multiple physical machines (e.g., Distrinet). In this paper we tackle the case of packet delay monitoring, to which we propose a methodology for passively measuring one-way delays with underlying assumptions about time synchronization, and round-trip delays otherwise. For an efficient implementation of our methodology, we propose an eBPF-based packet measurement tool that performs better than current packet sniffers under emulation-specific assumptions. We implement and evaluate our system in an open testbed and show that it can reach results within few microseconds of perfect accuracy and precision.

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.

This deliverable aims to organise the discussions regarding the reference architecture of SLICES-RI. In this document, different scenarios are analysed and presented as a baseline for the future discussions regarding the SLICES-RI’s reference architecture. Other scenarios, in addition to the above-mentioned ones, might be considered by the partners in the future.

International audience; Many companies and organizations are moving their applications from on-premises data centers to the cloud. The cloud infrastructures can potentially provide an infinite amount of computation (e.g., Elastic Compute) and storage (e.g., Simple Service Storage). In addition, all cloud providers propose different offers: IaaS, PaaS, and SaaS. This demo focuses on the IaaS services, presenting a simple tool to measure the network delay in a virtual infrastructure built entirely in the cloud. These measurements are useful for organizations that are moving current applications to, or creating new applications in, the cloud, but have requirements on the maximum, or average, network delay that these applications can tolerate. We present CloudTrace, a simple CLI tool that creates regional and multiregional experiments to measure delay, using Amazon AWS.

International audience; 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.

International audience; Traditional loss-based Congestion Control Algorithms (CCAs) suffer from performance issues over wireless networks mostly due to their inability to distinguish wireless random losses from congestion losses. Different loss discrimination algorithms have been proposed to tackle this issue but they are not efficient for 4G networks since they do not consider the impact of various link layer mechanisms such as adaptive modulation and coding and retransmission techniques on congestion in LTE Radio Access Networks (RANs). We propose MELD (MEC-based Edge Loss Discrimination), a novel server-side loss discrimination mechanism that leverages recent advancements in Multi-access Edge Computing (MEC) services to discriminate packet losses based on real-time RAN statistics. Our approach collects the relevant radio information via MEC's Radio Network Information Service and uses it to correctly distinguish random losses from congestion losses. Our experimental study made with the QUIC transport protocol shows over 80% higher goodput when MELD is used with NewReno and 8% higher goodput when used with Cubic.

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.

International audience; Networks became so complex and technical that it is now hard if not impossible to model or simulate them. Consequently, more and more researchers rely on prototypes emulated in controlled environments and Mininet is by far the most popular tool. Mininet implements a simple, yet powerful API to define and run network experiments on a single machine. In most cases, running experiments on one machine is adequate but for resource intensive applications one machine may not be sufficient. For that reason we propose Distrinet, a way to distribute Mininet over multiple hosts. Distrinet uses the same API than Mininet, granting full compatibility with Mininet programs. Distrinet is generic and can optimally deploy experiments in Linux clusters or in public clouds and automatically minimizes the resource consumed in the experimental infrastructure.

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.

International audience; The trend today is to deploy applications and more generally Service Function Chains (SFCs) in public clouds. However, before being deployed in the cloud, chains were deployed on dedicated infrastructures where software, hardware, and network components were managed by the same entity, making it straightforward to provide robustness guarantees. By moving their services to the cloud, the users lose their control on the infrastructure and hence on the robustness. In this paper, we provide an online algorithm for robust placement of service chains in data centers. Our placement algorithm determines the required number of replicas for each function of the chain and their placement in the data center. Our simulations on large data-center topologies with up to 30,528 nodes show that our algorithm is fast enough such that one can consider robust chain placements in real time even in a very large data center and without the need of prior knowledge on the demand distribution.

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; We describe a demonstration run on R2lab, an open wireless testbed located in an anechoic chamber at Inria Sophia Antipolis. The demonstration consists in easily deploying a Wi-Fi mesh network. The nodes provisioning, configuration and the scenario orchestration and control are automatically done using the nepi-ng experiment orchestration tool. A performance comparison of two wireless mesh routing protocols in presence of controlled interference is shown.

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.

We describe a demonstration run on R2lab, an anechoic chamber located at Inria Sophia Antipolis, France. The demonstration consists in deploying a standalone 5G network in less than 5 minutes. All the network components (base station, subscriber management, serving and packet gateways, network traffic analyzers) were run automatically using the nepi-ng experiment orchestration tool. Download and upload performance to the Internet from a commercial phone located in the anechoic chamber are shown.

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.

International audience; Over the last two decades several efforts have been made to provide adequate experimental environments, aiming to ease the development of new network protocols and applications. These environments range from network simulators providing a highly controllable evaluation conditions, to live testbeds providing realistic evaluation environment. While these different approaches foster network development in different ways, there is no simple way to gradually transit from one to another, or to combine their strengths to suit particular evaluation needs. We believe that enabling a gradual transition from a pure simulated environment to a pure realistic one, where the researcher can decide which aspects of the environment are realistic and which are controllable, allows improving network solutions by simplifying the problem analysis and resolution. In this paper, we propose a new network experimentation framework where simulated and real components can be arbitrarily combined to build custom test environments, allowing refining and improving new protocols and applications implementations by gradually increasing the level of realism of the evaluation environment. Moreover, we present a testbed architecture specifically adapted to support the proposed concept, and discuss the design choices we made based on our previous experience in the area of network testbeds. These choices address key issues in network testbed development, such as ease of experimentation, experiment reproducibility, and testbed federation, to enable scaling the size of experiments beyond what a single testbed would allow.

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.

We present an efficient message delivery framework, called MeDeHa, which enables communication in an internet connecting heterogeneous networks that is prone to disruptions in connectivity. MeDeHa is complementary to the IRTF's Bundle Architecture: besides its ability to store messages for unavailable destinations, MeDeHa can bridge the connectivity gap between infrastructure-based and multi-hop infrastructure-less networks. It benefits from network heterogeneity (e.g., nodes supporting more than one network and nodes having diverse resources) to improve message delivery. For example, in IEEE 802.11 networks, participating nodes may use both infrastructure- and ad-hoc modes to deliver data to otherwise unavailable destinations. It also employs opportunistic routing to support nodes with episodic connectivity. One of MeDeHa's key features is that any MeDeHa node can relay data to any destination and can act as a gateway to make two networks inter-operate or to connect to the backbone network. The network is able to store data destined to temporarily unavailable nodes till the time of their expiry. This time period depends upon current storage availability as well as quality-of-service needs (e.g., delivery delay bounds) imposed by the application. We showcase MeDeHa's ability to operate in environments consisting of a diverse set of interconnected networks and evaluate its performance through extensive simulations using a variety of scenarios with realistic synthetic and real mobility traces. Our results show significant improvement in average delivery ratio and a significant decrease in average delivery delay in the face of episodic connectivity. We also demonstrate that MeDeHa supports different levels of quality-of-service through traffic differentiation and message prioritization.

Communication networks, whether they are wired or wireless, have traditionally been assumed to be connected at least most of the time. However, emerging applications such as emergency response, special operations, smart environments, VANETs, etc. coupled with node heterogeneity and volatile links (e.g. due to wireless propagation phenomena and node mobility) will likely change the typical conditions under which networks operate. In fact, in such scenarios, networks may be mostly disconnected, i.e., most of the time, end-to-end paths connecting every node pair do not exist. To cope with frequent, long-lived disconnections, opportunistic routing techniques have been proposed in which, at every hop, a node decides whether it should forward or store-and-carry a message. Despite a growing number of such proposals, there still exists little consensus on the most suitable routing algorithm(s) in this context. One of the reasons is the large diversity of emerging wireless applications and networks exhibiting such “episodic” connectivity. These networks often have very different characteristics and requirements, making it very difficult, if not impossible, to design a routing solution that fits all. In this paper, we first break up existing routing strategies into a small number of common and tunable routing modules (e.g. message replication, coding, etc.), and then show how and when a given routing module should be used, depending on the set of network characteristics exhibited by the wireless application. We further attempt to create a taxonomy for intermittently connected networks. We try to identify generic network characteristics that are relevant to the routing process (e.g., network density, node heterogeneity, mobility patterns) and dissect different “challenged” wireless networks or applications based on these characteristics. Our goal is to identify a set of useful design guidelines that will enable one to choose an appropriate routing protocol for the application or network in hand. Finally, to demonstrate the utility of our approach, we take up some case studies of challenged wireless networks, and validate some of our routing design principles using simulations.

Evaluating new network protocols, applications, and architectures uses many kinds of experimentation environments: simulators, emulators, testbeds, and sometimes, combinations of these. As the functionality and complexity of these tools increases, mastering and efficiently using each of them is becoming increasingly difficult. In this paper, we consider how to make it easier to use multiple tools separately and together to improve the productivity of network researchers. We show how a single object model which encompasses every aspect of a typical experimentation workow can be used to completely describe experiments to be run within very different experimentation environments. Although Nepi is still in early design and prototyping stage, we expect that its ability to describe and automate easily complex mixed experiments will enable further experimentation with heterogenous networks.

The analysis and evaluation of new wireless network protocols is a long process that requires mathematical analysis, simulations, and increasingly experimentations under real conditions. Measurements are essential to analyze the performance of wireless protocols such as IEEE 802.11 networks in real environments, but experimentations are complex to perform and analyze. Usually, network researchers develop their own tools, sometimes from scratch, to fit the requirements of their experimentations, and these tools are then abandoned when the paper is published. In this study, we emphasize the importance, for the network research community, to use and contribute to the development of open source measurement tools. In this regard, we propose a survey and classification of IEEE 802.11 wireless parameters and open source tools available to collect or estimate these parameters. We highlight the parameters that can be extracted from wireless traffic probes and those that are available through the driver of wireless cards. Then, we introduce and compare open source tools that can be used to make the measurements, with special attention to the flexibility of the tools and their application scope. Finally, we discuss with several case studies the combination of tools that best suit the needs of the wireless experiments and provide a list of common pitfalls to avoid.

Communication networks are traditionally assumed to be connected. However, emerging wireless applications such as vehicular networks, pocket-switched networks, etc., coupled with volatile links, node mobility, and power outages, will require the network to operate despite frequent disconnections. To this end, opportunistic routing techniques have been proposed, where a node may store-and-carry a message for some time, until a new forwarding opportunity arises. Although a number of such algorithms exist, most focus on relatively homogeneous settings of nodes. However, in many envisioned applications, participating nodes might include handhelds, vehicles, sensors, etc. These various "classesrdquo have diverse characteristics and mobility patterns, and will contribute quite differently to the routing process. In this paper, we address the problem of routing in intermittently connected wireless networks comprising multiple classes of nodes. We show that proposed solutions, which perform well in homogeneous scenarios, are not as competent in this setting. To this end, we propose a class of routing schemes that can identify the nodes of "highest utilityrdquo for routing, improving the delay and delivery ratio by four to five times. Additionally, we propose an analytical framework based on fluid models that can be used to analyze the performance of various opportunistic routing strategies, in heterogeneous settings.

In upcoming very high-speed wireless LANs (WLANs), the physical (PHY) layer rate may reach 600 Mbps. To achieve high efficiency at the medium access control (MAC) layer, we identify fundamental properties that must be satisfied by any CSMA-/CA-based MAC layers and develop a novel scheme called aggregation with fragment retransmission (AFR) that exhibits these properties. In the AFR scheme, multiple packets are aggregated into and transmitted in a single large frame. If errors happen during the transmission, only the corrupted fragments of the large frame are retransmitted. An analytic model is developed to evaluate the throughput and delay performance of AFR over noisy channels and to compare AFR with similar schemes in the literature. Optimal frame and fragment sizes are calculated using this model. Transmission delays are minimized by using a zero-waiting mechanism where frames are transmitted immediately once the MAC wins a transmission opportunity. We prove that zero-waiting can achieve maximum throughput. As a complement to the theoretical analysis, we investigate the impact of AFR on the performance of realistic application traffic with diverse requirements by simulations. We have implemented the AFR scheme in the NS-2 simulator and present detailed results for TCP, VoIP, and HDTV traffic. The AFR scheme described was developed as part of the IEEE 802.11n working group work. The analysis presented here is general enough to be extended to proposed schemes in the upcoming 802.11n standard. Trends indicated in this paper should extend to any well-designed aggregation schemes.

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.

This paper addresses the issue of the security of Internet Coordinate Systems,by proposing a general method for malicious behavior detection during coordinate computations. We first show that the dynamics of a node, in a coordinate system without abnormal or malicious behavior, can be modeled by a Linear State Space model and tracked by a Kalman filter. Then we show, that the obtained model can be generalized in the sense that the parameters of a filtercalibrated at a node can be used effectively to model and predict the dynamic behavior at another node, as long as the two nodes are not too far apart in the network. This leads to the proposal of a Surveyor infrastructure: Surveyor nodes are trusted, honest nodes that use each other exclusively to position themselves in the coordinate space, and are therefore immune to malicious behavior in the system.During their own coordinate embedding, other nodes can thenuse the filter parameters of a nearby Surveyor as a representation of normal, clean system behavior to detect and filter out abnormal or malicious activity. A combination of simulations and PlanetLab experiments are used to demonstrate the validity, generality, and effectiveness of the proposed approach for two representative coordinate embedding systems, namely Vivaldi and NPS.

Multicast video streaming over multirate wireless LANs imposes strong demands on video codecs and the underlying network. It is not sufficient that only the video codec or only the underlying protocols adapt to changes in the wireless link quality. Research efforts should be applied in both and in a synchronized way. Cross layer design is a new paradigm that addresses this challenge by optimizing communication network architectures across traditional layer boundaries. This paper presents cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs where layer-specific information is passed in both directions, top-down and bottom-up. The authors jointly consider three layers of the protocol stack: the application, data link and physical layers. The authors analyze the performance of the proposed architecture and extensively evaluate it via simulations. The results show that the real-time video quality of the overall system can be greatly improved by cross-layer signaling.

We are witnessing a considerable amount of research work related to data center and cloud infrastructures but evaluations are often limited to small-scale scenarios as very few researchers have access to a real infrastructure to confront their ideas to reality. In this demo we will reveal our experiment automation tool, DiG (Data centers in the Grid), which explicitly allocates physical resources in grids to emulate data center and cloud networks. DiG allows one to utilize grid infrastructures to evaluate research ideas pertaining to data centers and cloud environments at massive scale and with real traffic workload. We have automated the procedure of building target network topologies while respecting available physical resources in the grid against the demand of links and hosts in the experiment. We will present a showcase where DiG automatically builds a large data center topology composed of hundreds of servers executing various Hadoop intensive workloads.

Nowadays, content retrieval is marking the Internet usage. User communications are no longer tied up to host interconnection. Information Centric Networking (ICN) models are proposed to cope with these changes. The new paradigm redesigns the Internet architecture to bring out content to the first level. Over the last decade, many key projects have proposed a large solution spectrum to rebuilt networking primitives focused on the content. One important and direct challenge of this shift is the large amount of routing states due to identifying contents rather than hosts. In this paper, we focus especially on DONA, one of the first ICN architecture, and analyse the required memory space to store routing states. Our study shows that today's technologies are not able to satisfy the content routing needs. Thus, we propose an enhancement of DONA called BADONA to deal with this problem. It uses the Bloom filter to drastically reduce the usage of the memory space. Finally, we evaluate our proposal performances to underscore its contribution.

International audience; ns-3 is a flexible simulator whose capabilities go beyond running purely synthetic simulations in a local desktop. Due to its ability to run unmodified Linux applications, to execute in real time mode, and to exchange traffic with live networks, ns-3 can be combined with live hosts to run distributed simulations or to transparently integrate live and simulated networks. Nevertheless, setting up ns-3 multi-host experiment scenarios might require considerable manual work and advanced system administration skills. The NEPI experiment management framework is capable of automating deployment, execution, and result collection of experiment scenarios that combine ns-3 with multiple hosts in various ways, reducing the burden of manual scenario setup. In this paper we describe the internals of the NEPI framework that provides support for automation of ns-3 experiments, and demonstrate its usage for ns-3 multi-host scenarios with three example cases: a) running parallel simulations on a cluster of hosts, b) running distributed simulations spanning multiple hosts, and c) integrating live and simulated networks.