Les défis de l'émulation Wi-Fi à base des traces

Wi-Fi link is unpredictable and it has never been easy to measure it perfectly; there is always bound to be some bias. As wireless becomes the medium of choice, it is useful to capture Wi-Fi traces in order to evaluate, tune, and adapt the different applications and protocols. Several methods have been used for the purpose of experimenting with different wireless conditions: simulation, experimentation, and trace-driven emulation. In this paper, we argue that trace-driven emulation is the most favourable approach. In the absence of a trace-driven emulation tool for Wi-Fi, we evaluate the state-of-the-art trace driven emulation tool for Cellular networks and we identify issues for Wi-Fi: interference with concurrent traffic, interference with its own traffic if measurements are done on both uplink and downlink simultaneously , and packet loss. We provide a solid argument as to why this tool falls short from effectively capturing Wi-Fi traces. The outcome of our analysis guides us to propose a number of suggestions on how the existing tool can be tweaked to accurately capture Wi-Fi traces.La liaison Wi-Fi est imprévisible et il n'a jamais été facile de la mesurer parfaitement ; il y a toujours un risque de biais. Comme le sans fil devient le moyen de communication de choix, il est utile de capturer les traces Wi-Fi afin d'évaluer, de régler et d'adapter les différentes applications et protocoles. Plusieurs méthodes ont été utilisées pour expérimenter différentes conditions sans fil : la simulation, l'expérimentation et l'émulation de traces. Dans cet article, nous soutenons que l'émulation pilotée par les traces est l'approche la plus favorable. En l'absence d'un outil d'émulation piloté par trace pour le Wi-Fi, nous évaluons l'outil d'émulation piloté par trace de pointe pour les réseaux cellulaires et nous identifions les problèmes pour le Wi-Fi : interférence avec le trafic concurrent, interférence avec son propre trafic si les mesures sont effectuées simultanément sur la liaison montante et la liaison descendante, et perte de paquets. Nous fournissons un argument solide pour expliquer pourquoi cet outil ne parvient pas à capturer efficacement les traces Wi-Fi. Le résultat de notre analyse nous guide pour proposer un certain nombre de suggestions sur la manière dont l'outil existant peut être modifié pour capturer avec précision les traces Wi-Fi

How far can we go? Towards Realistic Software-Defined Wireless Networking Experiments

International audienceSoftware-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

JamLab: Augmenting Sensornet Testbeds with Realistic and Controlled Interference Generation

Radio interference drastically affects the performance of sensor-net communications, leading to packet loss and reduced energy-efficiency. As an increasing number of wireless devices operates on the same ISM frequencies, there is a strong need for understanding and debugging the performance of existing sensornet protocols under interference. Doing so requires a low-cost flexible testbed infrastructure that allows the repeatable generation of a wide range of interference patterns. Unfortunately, to date, existing sensornet testbeds lack such capabilities, and do not permit to study easily the coexistence problems between devices sharing the same frequencies. This paper addresses the current lack of such an infrastructure by using off-the-shelf sensor motes to record and playback interference patterns as well as to generate customizable and repeat-able interference in real-time. We propose and develop JamLab: a low-cost infrastructure to augment existing sensornet testbeds with accurate interference generation while limiting the overhead to a simple upload of the appropriate software. We explain how we tackle the hardware limitations and get an accurate measurement and regeneration of interference, and we experimentally evaluate the accuracy of JamLab with respect to time, space, and intensity. We further use JamLab to characterize the impact of interference on sensornet MAC protocols

How to Validate Traffic Generators?

Abstract-Network traffic generators are widely used in networking research and they are validated by a very broad range of metrics (mainly traffic characteristics). In this paper we overview the state of the art of these metrics and unveil that there is no consensus in the research community how to validate these traffic generators and which metric to choose for validation purpose. This situation makes it extremely difficult to evaluate validation results and compare different traffic generators. We advocate the research for finding a common set of metrics for the validation and comparative evaluation of traffic generators