This paper introduces a novel distributed approach for forming UAV-based multi-hop relay networks by adapting traditional flocking models to create relay chains between remote points. Our method modifies the standard flocking paradigm by incorporating dynamic agent roles, allowing UAVs to self-organize based solely on local state and neighbor information, and integrates networking information such as routing decisions directly into mobility control. A side contribution is the introduction of a Line-of-Sight (LOS) conservation force, which mitigates communication failures due to obstacles and is easily adaptable to the flocking model. The proposed algorithm is evaluated using a joint robotics and network co-simulator that combines realistic multi-rotor physics with ns-3-based network simulations. Simulation results across diverse environments and varying mission complexities demonstrate that our approach effectively maintains connectivity, enhances Quality of Service (QoS), and scales robustly, thereby bridging the gap between robotic control and aerial wireless network design.

Target Wake Time (TWT) is a key energy-saving mechanism in IEEE 802.11 WLANs, allowing stations (STAs) to reduce power consumption by restricting transmissions to scheduled service periods (SPs). Despite its potential, TWT remains underutilized due to concerns over performance degradation, especially under congested network conditions. In this paper, we address this limitation by proposing the Power Mode Selection Algorithm (PMSA), a lightweight and standard-compliant mechanism implemented at the Access Point (AP). PMSA operates on top of existing TWT schedulers and dynamically determines whether each STA should operate in power save (PS) mode or temporarily switch to active mode (and disable TWT) based on current network congestion. Our simulation results demonstrate that PMSA enhances the robustness of TWT scheduling by adapting to traffic conditions, maintaining low delays and avoiding packet losses even under heavy load, while preserving energy savings when feasible.

International audience

UAV-based wireless networks can be deployed to provide a network coverage to users who have no or poor network connection. Unlike traditional model-based approaches that require predefined assumptions before UAV deployment, reinforcement learning (RL) offers a promising alternative but requires a realistic simulator for training the proposed strategies. None of the existing open-source simulators provide both realistic wireless communications while enabling the training, in a cluttered environment, of multi-UAVs movement strategies using RL. Thus, in this paper, we present a simulator where we focus on improving the modeling of the network access part, i.e., the communications between the UAVs and the users, by integrating signal propagation, physical rate adaptation and medium access sharing models. We evaluate the performance of a standard independent RL algorithm trained in our simulator across various use case scenarios, and compare the results obtained using different learning objectives. Results show that the classical formulation, commonly found in the literature and based on a a simplified wireless network model, underperforms in terms of communication quality.

Experimental link quality assessment of recent Wi-Fi networks remains a challenge due to the rapid development of the Wi-Fi technology, the lack of availability of public datasets, and the difficulty to build such datasets. This paper addresses all three issues by first providing a publicly-available dataset using a custom-made Wi-Fi 5 experimental testbed. We then present an open-source framework for estimating the Frame Delivery Ratio (FDR) of a Wi-Fi link using the experimental data. The proposed solution relies on a small number of input features to build an estimation model of high accuracy, with an R2 coefficient of 0.89 and a mean absolute error of 0.06.

The Internet of Things (IoT) is transforming all economic sectors by connecting physical assets to the virtual world. The range of low-power connectivity options is continuously widening the range of possible IoT applications. However, too many possibilities often make it hard for industrial specialists to choose the right technology and configuration settings, yet these are crucial decisions. To deeply analyze and compare the performance and the scalability of various solution designs, one proven method is simulation. In this article, we show how IoT network simulation can help to future-proof an IoT connectivity design, without the burden of installing a lot of hardware and writing complicated scripts. Then, as the network simulation process is too complex for most IoT teams, we propose a no-code online IoT network simulation platform to make this powerful tool accessible to all. In particular, we explain how we hide the simulation workflow complexity via relevant abstractions and transform it into intuitive interactions. We illustrate the method and the usage of this promising approach, which can be integrated in a network digital twin. We show how it permits to easily evaluate what-if scenarios in order to answer a set of questions that may arise all along the life cycle of a smart connected solution.

The IEEE 802.11 protocol has become the de facto communication technology for WLANs (Wireless Local Area Networks). While considered reliable and efficient for applications requiring high datarate, IEEE 802.11 is often disregarded for energy-sensitive applications such as IoT (Internet of Things). In fact, the IEEE 802.11 standard and its amendments have introduced several energy-saving mechanisms over the years that are rarely used in practice. In this paper, we consider seven possible energy-saving strategies for the MAC layer of IEEE 802.11. Using two case studies, we evaluate and compare these energy-saving strategies with regard to their network performance and energy saving. We conclude that most of the energy-saving strategies manage to support the levels of workloads considered in our case studies, and at the same time, they succeed to cut energy consumption by a factor ranging from two to eight. In particular, the "DL slot'' strategy leads STAs to consume only half (or even less) of what they would without running any strategy, without trading off the attained levels of throughput. The "DL prompt + UL slot'' strategy is the most efficient energy-wise, but this can come at the expense of a loss of throughput.

The Internet of Things (IoT) is the convergence of the physical and the digital worlds. It enables a large spectrum of applications such as smart building, smart tracking, smart metering, predictive maintenance, remote control, augmented reality or video surveillance. The diversity of these applications has caused a profusion of the IoT communication technologies offerings for exchanging data between IoT devices and applications. The latter technologies come with different features in terms of range, throughput, latency, scalability, energy, etc. Each technology can fit several use cases and a use case can leverage several technologies. It is complex, yet critical, for an IoT architect to evaluate the adequacy and the limits of a network technology for a targeted application and to continuously optimize its configuration as the deployment evolves. This paper introduces ADIperf, a framework to simplify and systematize the evaluation of the performance of an IoT communication technology for a given IoT use case and context. The ADIperf approach pays special attention to the energy efficiency as well as to the ability of an IoT communication technology to properly scale up with the number of end-devices, with the ultimate goal of giving guidelines and tools for IoT architects to select the technology and configure the network that fulfill their application's needs over time.

In this paper, we study existing flocking models and propose extensions to improve their abilities to deal with environments having obstacles impacting the communication quality. Often depicted as robust systems, there is yet a lack of understanding how flocking models compare and how they are impacted by the communication quality when they exchange control data. We extend two standard models to improve their ability to stay connected while evolving in environments with different obstacles distributions. By taking into account the radio propagation, we model the obstacles impact on communications in a simulator that we use to optimize flocking parameters. The simulation results show the efficiency of the proposed models and how they adapt to different environmental constraints.

In this paper, we investigate the problem of optimizing the network performance of a fleet of unmanned aerial vehicles (UAVs) in static positions. More precisely, we allow each UAV to change its orientation in order to improve the quality of communication with its neighbours. This form of controlled mobility takes advantage of the effective radiation pattern of each UAV. We build a decentralized scheme based on the hill climbing optimization approach without a priori knowledge of the antennas radiation patterns. Then, we propose a simulation framework, based on ns--3, allowing to evaluate the gain in network performance. We provide results in several deployment scenarios involving different rate adaptation algorithms and network sizes.

With the rise of the complexity of the IEEE 802.11 standard, rate adaptation algorithms have to deal with a large set of values for all the different parameters which impact the network throughput. Simple trial-and-error algorithms can no longer explore solution space in reasonable time and smart solutions are required. Most of the WiFi controllers rely on proprietary code and the used rate adaptation algorithms in these controllers are unknown. Very few WiFi controllers provide their rate adaptation algorithms when they do not rely on the Minstrel-HT algorithm, which is implemented in the Linux kernel. Intel WiFi controllers come with their own rate adaptation algorithms that are implemented in the Intel IwlWifi Linux Driver which is open-source. In this paper, we have reverse-engineered the Intel rate adaptation mechanism from the source code of the IwlWifi Linux driver, and we give, in a comprehensive form, the underlying rate adaptation algorithm named Iwl-Mvm-Rs. We describe the different mechanisms used to seek the best throughput adapted to the network conditions. We have also implemented the Iwl-Mvm-Rs algorithm in the ns-3 simulator. Thanks to this implementation, we can evaluate the performance of Iwl-Mvm-Rs in different scenarios (static and with mobility, with and without fast fading). We also compare the performances of Iwl-Mvm-Rs with the ones of Minstrel-HT and IdealWifi, also implemented in the ns-3 simulator.

We consider a VoD (Video on-Demand) platform designed for vehicles traveling on a highway or other major roadway. Typically, cars or buses would subscribe to this delivery service so that their passengers get access to a catalog of movies and series stored on a back-end server. Videos are delivered through IEEE 802.11p Road Side Units deployed along the highway. In this paper, we propose a simple analytical and yet accurate solution to estimate (at the speed of a click) two key performance parameters for a VoD platform: (i) the total amount of data downloaded by a vehicle over its journey and (ii) the total "interruption time'', which corresponds to the time a vehicle spends with the playback of its video interrupted because of an empty buffer. After validating its accuracy against a set of simulations run with ns-3, we show an example of application of our analytical solution for the sizing of an IEEE 802.11p-based VoD platform.

Though SDN (Software Defined Network) provides the executive building blocks for programming data-plane appliances, controller decisions must be grounded in an accurate outlook on the network topology and performance. In this context, we focus on the possibility of providing accurate measurements for the end-to-end (E2E) delay in SDN networks. In practice, like many variable quantities, a good description of the E2E delay requires characterizing its first two moments, i.e., expectation and variance. We propose to estimate the E2E delay by making use only of measurements collected locally on each node of the network. We extend a procedure that has been proposed to estimate the E2E delay in the case of one flow to handle the case of multiple competing flows. We compare its accuracy using several scenarios, with different types of traffic following real traces, different topologies and bandwidth. Also, an analysis of the computational and networking costs of our solution is proposed.

With Software-Defined Networking (SDN), computer networks will gain a better control and management on their physical resources and on flows requiring a specific type of QoS. To fulfil these objectives, networks must be able to characterize the end-to-end performance of flows, which are usually unknown and not directly measurable. Instead, networks have typically at their disposal only local measurements, collected at each node. In this paper, we propose a new method to evaluate the variance of the end-to-end delay based only on measurements collected on nodes. The core of our solution is to link samples of waiting times at different nodes in order to approximate the corresponding covariance terms, needed to refine the approximate value of the sought variance. We evaluate the accuracy of our solution using two different scenarios. The obtained results show that the method is generally good, with a relative error on the estimated standard deviation of the end-to-end delay usually close to 5%, though it may exceed 10% when the network is facing high levels of load and experiencing packet losses.

Densification of Wi-Fi networks has led to the possibility for a station to choose between several access points (APs). On the other hand, the densification of APs generates interference, contention and decreases the global throughput as APs have to share a limited number of channels. Optimizing the association step between APs and stations can alleviate this problem and increase the overall throughput and fairness between stations. In this paper, we propose an original solution to this optimization problem based on two contributions. First, we present a mathematical model for the association optimization problem based on a realistic share of the medium between APs and stations and among APs when using the 802.11 DCF (Distributed Coordination Function) mode. Then, we introduce a local search algorithm to solve this problem through a suitable neighborhood structure. This approach has the benefit to be tuned according to the CPU and time constraints of the WLAN controller. Our evaluation, based on simulations, shows that the proposed solution improves the overall throughput and the fairness of the network.

In this paper, we propose an algorithm to estimate the second moment of the end-to-end delay experienced by the packets of a flow based only on delay measurements locally collected by the network nodes. Our solution estimates the standard deviation of the end-to-end delay in an easy and computationally efficient way. Based on thousands of simulations using a real-life trace, our solution is found to be accurate, typically differing by only a few percent from the actual value of the standard deviation of the end-to-end delay.

In this paper, we follow up an existing modeling framework to analytically evaluate the performance of multi-hop flows along a wireless chain of four nodes. The proposed model accounts for a non-perfect physical layer, handles the hidden node problem, and is applicable under workload conditions ranging from flow(s) with low intensity to flow(s) causing the network to saturate. Its solution is easily and quickly obtained and delivers estimates for the expected throughput and for the datagram loss probability of the chain with a good accuracy.

IEEE 802.11 is implemented in many wireless networks, including multi-hop networks where communications between nodes are conveyed along a chain. We present a modeling framework to evaluate the performance of flows conveyed through such a chain. Our framework is based on a hierarchical modeling composed of two levels. The lower level is dedicated to the modeling of each node, while the upper level matches the actual topology of the chain. Our approach can handle different topologies, takes into account Bit Error Rate and can be applied to multi-hop flows with rates ranging from light to heavy workloads. We assess the ability of our model to evaluate loss rate, throughput, and end-to-end delay experienced by flows on a simple scenario, where the number of nodes is limited to three. Numerical results show that our model accurately approximates the performance of flows with a relative error typically less than 10%.

Many methods have been proposed in the literature to perform admission control in order to provide a sufficient level of Quality of Service (QoS) to accepted flows. In this paper, we introduce a novel data-driven method based on a time-varying model that we refer to as Knowledge-Based Admission Control solution (KBAC). Our KBAC solution consists of three main stages: (i) collect measurements on the on-going traffic over the communication link; (ii) maintain an up-to-date broad view of the link behavior, and feed it to a Knowledge Plane; (iii) model the observed link behavior by a mono-server queue whose parameters are set automatically and which predicts the expected QoS if a flow requesting admission were to be accepted. Our KBAC solution provides a probabilistic guarantee whose admission threshold is either expressed, as a bounded delay or as a bounded loss rate. We run extensive simulations to assess the behavior of our KBAC solution in the case of a delay threshold. The results show that our KBAC solution leads to a good trade-off between flow performance and resource utilization. This ability stems from the quick and automatic adjustment of its admission policy according to the actual variations on the traffic conditions.

Multihop wireless networks are used to provide internet connectivity to the users and the level of performance and quality expected by these users are increasing. In order to meet these performance and quality requirements, wireless communications should be enhanced. Previous works from the literature show that the performance and quality provided by an IEEE 802.11-based multihop wireless network are far from optimal and that there exist different ways to increase the efficiency and the quality of service of such a network. Some studies show that using the medium state as a parameter to tune the behaviour of an IEEE 802.11-based multihop network is an appropriate way to proceed. A station in a IEEE 802.11-based multihop wireless network senses the medium either busy or idle. The durations of idle periods and busy periods and their distributions have a clear impact on the network and nodes performance. The understanding of the relationship between these indicators, namely idle and busy periods, the network topology and the traffic, would give new insights to enhance the performance and quality of multihop wireless networks. Due to its multihop and distributed nature, the characterisation of idle period durations is difficult in such a network. This paper explores the characterisation of idle period distribution by proposing a new analytical model and provides an application of this characterisation with the design of an adaptive backoff algorithm based on idle periods.

Vehicular communication for intelligent transportation systems will provide safety, comfort for passengers, and more efficient travels. This type of network has the advantage to warn drivers of any event occurred in the road ahead, such as traffic jam, accidents or bad weather. This way, the number of traffic accidents may decrease and many lives could be saved. Moreover, a better selection of non-congested roads will help to reduce pollution. Some other interesting services, such as downloading of multimedia services, would be possible and available through infrastructure along the roadside. Providing multimedia services over VANETs may require a QoS-aware routing protocol that often need to estimate available resources. In this paper, we study the performance, in realistic VANET urban scenarios, of an extension of AODV that includes the available bandwidth estimator ABE. AODV-ABE establishes forwarding paths that satisfy the bandwidth required by the applications. The results, obtained on the NCTUns simulator, show that AODV-ABE could be used in urban-VANETs where vehicles' speed is moderate.

Reducing the energy consumption of wired networks has become a key concern for manufacturers of network equipments and network providers. In this paper, we propose an energy-efficient data transfer framework that uses advance bandwidth provisioning and on/off algorithms to put unused nodes of wired networks into sleep mode. This framework is termed as High-level Energy-awaRe Model for bandwidth reservation in End-to-end networkS (HERMES). We explore centralized, decentralized and clustered approaches for managing network resources and bandwidth reservations in this framework. By applying these approaches to HERMES, we evaluate via simulation their efficiency in terms of performance and energy consumption.

Admission control is a mechanism used to restrict access to a computer network to some flows based on the current utilization level of the network resource. By regulating the number of on-going flows, admission control aims at preventing over loading, congestion and performance collapses, so that, accepted flows receive a sufficient level of Quality of Service (QoS). In this paper, we evaluate three existing measurement-based admission control (MBAC) solutions, and we compare their efficiency in the context of semantic networks. Semantic networks refer to networks that autonomously acquire a knowledge on the on-going traffic as well as on any new incoming flow requesting admission. In this framework, we configure the three MBAC solutions in a way they have an identical target in terms of maximum tolerable packet loss rate or maximum tolerable packet queueing delay. We evaluate the solutions performance analytically or by simulation, and compare them to the "ideal" admission control. The results show that one solution, outperforms the others in meeting the target performance.

Estimating the available bandwidth in IEEE 802.11-based multihop wireless networks is a very difficult task due to the medium sharing among contending nodes and collisions between hidden stations. Several methods have been proposed so far for these networks to compute the available bandwidth on wireless links. If some recent solutions such as ABE and IAB now take into account collisions and their impact on the mean backoff, none considers the packet retransmissions due to collisions although these retransmissions have an impact on the available bandwidth. In this article, we propose a new available bandwidth estimation for multihop wireless networks called RABE (Retransmission-based Available Bandwidth). This method integrates the average number of retransmission attempts in the available bandwidth estimation. RABE is evaluated by simulation and the obtained results show that RABE can achieve a mean error ratio of 17% in comparison with the real measurement. Furthermore, RABE is at least two times more accurate than ABE and ten times more accurate than IAB.

Wired networks are increasing in size and their power consumption is becoming a matter of concern. Evaluating the end-to-end electrical cost of new network architectures and protocols is difficult due to the lack of monitored realistic infrastructures. We propose an End-to-End energy Cost mOdel and simulator For Evaluating power consumption in large-scale Networks (ECOFEN) whose user's entries are the network topology and traffic. Based on configurable measurement of different network components (routers, switches, NICs, etc.), it provides the power consumption of the overall network including the end-hosts as well as the power consumption of each equipment over time.

Fairness in multihop ad hoc networks has received considerable attention in the literature. Many schemes have been proposed, which attempt to compute the ``optimal'' bit rates of the transmitting mobile nodes so that a certain fairness criterion is met. As the related literature indicates, there is a trade-off between fairness and efficiency, since fairness schemes typically reduce the channel utilization. Also, it is questionable whether certain fairness schemes have a positive or negative impact on the QoS of certain user services. So far, there has been limited research on the impact of the varying short-term allocations of these protocols, due to their inherent features and also nodes mobility, on the user-perceived QoS (and social welfare) for services of long duration. In this paper, we introduce an assessment framework, based on history-dependent utility functions that can be used as a holistic performance evaluation tool of these fairness schemes. These functions quantify the satisfaction that the ad hoc users obtain from the way their long-lived service sessions are allocated bandwidth, due to the behavior of the MANETs fair schemes. This way we can unambiguously compare the performance of various fair solutions whose maximization goals are inherently different (max-min fairness, proportional fairness, etc.). Finally, we demonstrate the usefulness of this framework by applying it on different protocols.

IEEE 802.11 is often considered as the underlying wireless technology of multihop wireless networks. But the use of 802.11 in such networks raises issues, like efficiency and/or fairness issues. Different kinds of solutions have been proposed to overcome these problems. One approach is to design new MAC protocols that provide alternatives to the IEEE 802.11 MAC protocol. Although these solutions are of some interest, it should probably take some time before new wireless network interface cards based on one of these solutions are developed and released. Another approach is to consider that 802.11 will remain the underlying wireless technology and to design solutions above it. Several solutions based on rate allocation have been proposed so far. The main drawback of the proposed solutions is that they rely on a radio medium sharing model that is difficult to compute in a wireless, distributed and mobile environment. Indeed, very few of these solutions have been derived into a network protocol. In this article, we propose a distributed and dynamic rate allocation solution that is based on a simple sharing model. Due to its simplicity, we can derive a network protocol that can be practically used in multihop wireless networks. This protocol provides a fair bandwidth sharing between end-to-end flows while maintaining an efficient overall throughput in the network. This solution has been implemented in NS2 and evaluated by simulations.

Since 2005, IEEE 802.11-based networks are able to provide a certain level of Quality of Service by the means of service differentiation, thanks to the IEEE 802.11e amendment. However, no mechanism or method has been standardized to accurately evaluate the amount of resources remaining on a given channel. Such evaluation would however be a good asset for bandwidth-constrained applications. In multi-hop ad hoc networks, such evaluation becomes even more difficult. Consequently, despite the various contributions around this research topic, the estimation of the available bandwidth still represents one of the main issues in this field. In this article, we propose an improved mechanism to estimate the available bandwidth in IEEE 802.11-based ad hoc networks. Through simulations, we compare the accuracy of the estimation we propose to the estimation performed by others state of the art QoS protocols, BRuIT, AAC and QoS-AODV.

In this paper, we propose a new cross-layer protocol named DRBT (dynamic regulation of Best Effort traffic) which supports QoS guarantees and provides a distributed regulation mechanism for Best Effort traffic in wireless ad hoc networks. By adapting the rate of best effort traffic at the MAC Layer, DRBT increases the acceptance rate of QoS flows through the network. The protocol also provides an accurate method to evaluate the available bandwidth in IEEE 802.11-based ad hoc networks which differentiates between QoS applications and those which are less exigent in term of bandwidth more commonly called Best Effort traffic. Through simulations, we compare the performance of our proposal scheme with AODV and ABE.

In this article, we propose a method to enhance accuracy of the available bandwidth estimation in IEEE 802.11-based ad hoc networks. This method combines medium state monitoring, probability of collision estimation and backoff time evaluation, improving the method described in C. Sarr et al., (2005). We evaluate our solution by simulation on different scenarios and compare it with different QoS routing protocols based on different available bandwidth estimation techniques

In the widely used 802.11 standard, the so-called performance anomaly is a well-known issue. Several works have tried to solve this problem by introducing mechanisms such as packet fragmentation, backoff adaptation, or packet aggregation during a fixed time interval. In this paper, we propose a novel approach solving the performance anomaly problem by packet aggregation using a dynamic time interval, which depends on the busy time of the wireless medium. Our solution differs from other proposition in the literature because of this dynamic time interval, which allows increasing fairness, reactivity, and in some cases efficiency. In this article, we emphasize the performance evaluation of our proposal.

Network measurement is essential for assessing performance issues, identifying and locating problems. Two common strategies are the passive approach that attaches specific devices to links in order to monitor the traffic that passes through the network and the active approach that generates explicit control packets in the network for measurements. One of the key issues in this domain is to minimize the overhead in terms of hardware, software, maintenance cost and additional traffic.In this paper, we study the problem of assigning tap devices for passive monitoring and beacons for active monitoring. Minimizing the number of devices and finding optimal strategic locations is a key issue, mandatory for deploying scalable monitoring platforms. In this article, we present a combinatorial view of the problem from which we derive complexity and approximability results, as well as efficient and versatile Mixed Integer Programming (MIP) formulations.

We experiment the rate offered by 802.11 on a multi-hops configuration constituted of a chain of mobiles. We show that the rate achieved on a four-hops chain is around 200 kb/s with wireless cards at 2 Mb/s and is very unstable. We also compare our experimental results to simulation results.

In this article, we propose a tool that enables the deployment of scenarios on real ad hoc networks in order to measure the effects of 802.11b in ad hoc situations. We describe the first results we obtained. From these experiments, we can extract the capacity of the radio medium, the asymmetry of the used cards, the effects of broadcast on unicast flows and the interfering range.

Abstract This paper describes efficient coarse‐grained parallel algorithms and implementations for a suite of interval graph problems. Included are algorithms requiring only a constant number of communication rounds for connected components, maximum weighted clique, and breadth‐first‐search and depth‐first‐search trees, as well as $O(log p)$ communication rounds algorithms for optimization problems such as minimum interval covering, maximum independent set and minimum dominating set, where $p$ is the number of processors in the parallel system. This implies that the number of communication rounds is independent of the problem size. Implementations of these algorithms are evaluated on parallel clusters, using both Fast Ethernet and Myrinet interconnection networks, and on a CRAY T3E parallel multicomputer, with extensive experimental results being presented and analyzed. Copyright © 2002 John Wiley & Sons, Ltd.

This paper presents a theoretical study on the bandwidth reservation problem for ad hoc networks. The proposed model is based on the spatial reuse and the existence of interferences. We show that in that case, the bandwidth reservation problem is NP-complete and we provide some bounds that compare solutions of the problems derived with greedy heuristics with an optimal one. We conclude with a discussion on the practical aspect of this model and its potential use in a practical protocol.