Recent works have shown that deep learning (DL) models can effectively learn city-wide crowd-flow patterns, which can be used for more effective urban planning and smart city management. However, DL models have been known to perform poorly on inconspicuous adversarial perturbations. Although many works have studied these adversarial perturbations in general, the adversarial vulnerabilities of deep CFP models in particular have remained largely unexplored. In this paper, we perform a rigorous analysis of the adversarial vulnerabilities of DL-based CFP models under multiple threat settings, making three-fold contributions; 1) we propose CaV-detect by formally identifying two novel properties—ConsistencyandValidity—of the CFP inputs that enable thedetection of standard adversarial inputs with 0% false acceptance rate (FAR); 2) we leverage universal adversarial perturbations and an adaptive adversarial loss to present adaptive adversarial attacks to evade CaV-detect defense; 3) we propose CVP, aConsistent,Valid andPhysically-realizable adversarial attack, that explicitly inducts the consistency and validity priors in the perturbation generation mechanism. We find out that although the crowd-flow models are vulnerable to adversarial perturbations, it is extremely challenging to simulate these perturbations in physical settings, notably when CaV-detect is in place. We also show that CVP attack considerably outperforms the adaptively modified standard attacks in FAR and adversarial loss metrics. We conclude with useful insights emerging from our work and highlight promising future research directions.

Autonomous cooperative driving systems enable the safe operation of autonomous vehicles. However, the effectiveness of these systems is hindered by the challenge of promptly accessing necessary traffic data. High-definition (HD) maps serve as an extra sensor, providing advance information to autonomous vehicles about changes in the traffic surroundings. Therefore, it is crucial to keep the HD maps up to date. Our solution involves a service that notifies vehicles about updates in the traffic environment, aiming to minimize hazardous situations.

As making the right decision is a key element in autonomous driving systems, perfect knowledge of the traffic environment is necessary in order to avoid dangerous situations. Autonomous vehicles rely on a set of sensors to discover their local environment. However, these sensors are limited by range and weather conditions. Hence, they could not help for all conditions and roadway scenarios. Therefore, a new accurate and realistic technology for localization is needed. Recently, HD maps has emerged as a technology that increases the environment awareness of autonomous vehicles. Nevertheless, data of HD maps is highly dynamic and need to be always up-to-date. In this paper, we will review the used techniques for updating HD maps.

In this paper we address the challenge of inferring the road network of a city from crowd-sourced GPS traces. While the problem has been addressed before, our solution has the following unique characteristics: (i) we formulate the road network inference problem as a network alignment optimization problem where both the nodes and edges of the network have to be inferred, (ii) we propose both an offline (Kharita) and an online (Kharita) algorithm which are intuitive and capture the key aspects of the optimization formulation but are scalable and accurate. The Kharita in particular is, to the best of our knowledge, the first known online algorithm for map inference, (iii) we test our approach on two real data sets and both our code and data sets have been made available for research reproducibility.

In recent years, a combined utilization of ad-hoc communication and cellular mobile radio systems has been considered for vehicular networking in future Intelligent Transportation Systems (ITSs). The development of hybrid system protocols, algorithms and architectures require comprehensive performance investigations typically carried out by means of simulations. The main contribution of this article is to introduce a top-down design methodology for building realistic simulation scenarios tailored to the requirements in vehicular communication and suitable for multiple levels of abstraction in simulations. Within this paper the focus is set on the example city of Doha, Qatar: Building upon a macroscopic layer including static environmental data and a realistic cellular network, it is shown how to embed microscopic sub-scenarios with detailed modelling of individual user mobility into the macroscopic world. Exemplary sub-scenarios are derived with respect to applications considered for ITS. As a proof of concept, in the first part of the article, the design process is demonstrated for an LTE network in conjunction with IEEE 802.11p based vehicular communication. In the second part of the article, exemplary individual simulation results at the link-level are presented for both considered radio technologies.

Ultra dense networks and device-to-device communications are expected to play a major role in 5G networks to meet tremendous traffic requirements. In our work, we address traffic offloading in dense device-to-device cooperative heterogeneous networks with focus on use cases where a very large number of users request simultaneously common streaming content from a remote server with quality of service guarantees. We formulate an optimization problem to maximize the number of users served and reduce the number of access points deployed while satisfying a set of system constraints. The solution determines the best strategy for downloading the content either over long range connectivity from the access points or short range connectivity from peer mobile devices. Results are presented for various scenarios in a stadium setting to demonstrate the significant gains of optimized traffic offloading in ultra dense wireless networks.

The planning procedure of 802.11 WLAN networks is specific to each type of venue. In the case of large venues with high number and dense Wi-Fi devices, the network planning requires a deep investigation on: available channels, number of devices to associate, throughput per channels, etc. In addition, the WLAN planning of dense Wi-Fi devices becomes more complicated when adding collaboration between devices. The collaboration between devices is achieved by forwarding and sharing data through neighboring devices, named relays. In this paper, we provide guidelines for WLAN planning in high-dense collaborative environments. In addition, we study the network performance gains when content is distributed in cooperative manner through both unicast and multicast mode. Results show that using cooperative content distribution in dense environments leads to notable gain in network performance.

The Wi-Fi Direct technology was proposed by Wi-Fi Alliance in order to facilitate device-to-device communications in Wi-Fi. The Wi-Fi Direct technology offers new possibilities to deploy opportunistic and cooperative networks. The actual state of the Wi-Fi Direct specification lacks optimization for P2P grouping and creating opportunistic networks. In this paper, we present a new P2P group formation method for opportunistic networks and we introduce the concept of nominating a backup group owner that can replace the group owner of a broken P2P group. In addition, we investigate required times to form a P2P group of variable number of nodes and we evaluate the efficiency of the backup group owner. Results show that our proposed P2P group formation method, in addition to the introduction of the backup group owner, can facilitate and accelerate opportunistic P2P grouping.

Mobility in a city is represented as traffic flows in and out of defined urban travel or administrative zones. While the zones and the road networks connecting them are fixed in space, traffic flows between pairs of zones are dynamic through the day. Understanding these dynamics in real time is crucial for real time traffic planning in the city. In this paper, we use real time traffic flow data to generate dense functional correlation matrices between zones during different times of the day. Then, we derive optimal sparse representations of these dense functional matrices, that accurately recover not only the existing road network connectivity between zones, but also reveal new latent links between zones that do not yet exist but are suggested by traffic flow dynamics. We call this sparse representation the time-varying effective traffic connectivity of the city. A convex optimization problem is formulated and used to infer the sparse effective traffic network from time series data of traffic flow for arbitrary levels of temporal granularity. We demonstrate the results for the city of Doha, Qatar on data collected from several hundred bluetooth sensors deployed across the city to record vehicular activity through the city's traffic zones. While the static road network connectivity between zones is accurately inferred, other long range connections are also predicted that could be useful in planning future road linkages in the city. Further, the proposed model can be applied to socio-economic activity other than traffic, such as new housing, construction, or economic activity captured as functional correlations between zones, and can also be similarly used to predict new traffic linkages that are latently needed but as yet do not exist. Preliminary experiments suggest that our framework can be used by urban transportation experts and policy specialists to take a real time data-driven approach towards urban planning and real time traffic planning in the city, especially at the level of administrative zones of a city.

We present a scalable mobile multimedia streaming system with device-to-device cooperation that enables common content distribution in dense wireless networking environments. This is particularly applicable to use cases such as delivering real-time multimedia content to fans watching a soccer game in a stadium or to participants attending a major conference in a large auditorium. The key novel characteristics of our system include seamless neighbor discovery and link quality estimation, intelligent clustering and channel allocation algorithms based on constrained minimum spanning trees, robustness against device mobility, and device centric operation with no changes to existing wireless systems. We demonstrate the functionality of the proposed system on Android devices using heterogeneous networks (cellular/WiFi/WiFi-Direct) and show the formation of multiple clusters to allow for scalable operation. The gained insights will help bridge the gap between theoretical and simulation based research conducted in this area and practical operation taking into account the capabilities and limitations of existing wireless technologies and smartphones/tablets.

Global warming, environmental pollution, and fuel shortage are currently major worldwide challenges. Ecorouting is one of several tools that attempt to address this challenge by minimizing network-wide vehicle fuel consumption and emission levels. Eco-routing systems select the most environmentally friendly route. The subpopulation feedback eco-routing (SPF-ECO) algorithm that is implemented in the INTEGRATION software can produce a reduction in fuel consumption levels by approximately 17%. However, in some cases, due to delayed updates or the lack for updates, its performance degrades. In this paper, we propose the ant colony based eco-routing technique (ACO-ECO), which is a novel feedback eco-routing and cost updating algorithm to overcome these shortcomings. In the ACO-ECO algorithm, real-time performance measures on various roadway links are shared. Vehicles build their minimum path routes using the latest real-time information to minimize their fuel consumption and emission levels. ACO-ECO is also able to capture randomness in route selection, pheromone updating, and pheromone evaporation. The results show that the ACO-ECO algorithm and SPF-ECO have similar performances in normal cases. However, in the case of link blocking, the ACO-ECO algorithm reduces the network-wide fuel consumption and CO2 emission levels in the range of 2.3% to 6.0%. It also reduces the average trip time by approximately 3.6% to 14.0%.

Reliable vehicular communication is considered an important precondition for future intelligent transportation systems (ITSs). Recently, a combination of ad-hoc direct communication and infrastructure based cellular networks are considered to enable seamless connectivity and sufficient Quality of Service (QoS) for all types of vehicular applications. Within this paper a novel algorithm to enable data traffic steering between ad-hoc IEEE 802.11p based dedicated short range communication and LTE for Vehicle-to-X (V2X) communication is presented. Based on the system-level evaluation of cell loads and radio channel congestion the network based performance of the proposed algorithm is analyzed and compared to the conservative approach of using exclusively IEEE 802.11p for message dissemination. First simulation results in a realistic urban intersection scenario show significant improvement of the quality of service.

In Vehicular Ad-hoc Networks (VANETs), any vehicle uses a location service to get an up-to-date data of all vehicles' positions in its vicinity. Many location services rely on infrastructures to perform location update and location query tasks. However, the infrastructure penetration rate may differ from one region to another. We propose in this paper a new location service called Vehicle-Aided Location Service in urban environment (VALS) which resolves the problem of the shortage of infrastructure in some city districts. VALS replaces the missing Road-Side Units (RSU) with vehicles offering RSUs functionalities. It is based on a hierarchical and cluster-based design. Simulation results show that VALS achieves a high success ratio (86%), get most vehicles' data (82%) and a good position information level accuracy (less than 20 m) with a low RSU penetration rate (40%).

Vehicular ad hoc networks (VANETs) are a special case of mobile ad hoc networks (MANETs). The distinctive characteristics of VANETs include high-speed vehicular nodes and significant variability in node density. Collecting data from VANETs is important in monitoring, controlling, and managing road traffic. However, efficient collection of the needed data is challenging because vehicles are continuously moving and generating a significant amount of events and data. The focus of this paper is on vehicle data collection using 3G/LTE. Initially, a comparison of proactive and reactive data collection schemes is conducted using simulation. The results show that proactive schemes produce the lowest delay and bandwidth usage but the highest loss ratio. To efficiently use the available bandwidth, an adaptive data collection scheme is developed and described. This adaptive data collection scheme is based on a proactive scheme using variable polling periods depending on the vehicle positions in the network and travel time to provide accurate traffic and travel time information to the Traffic Management Center (TMC). Simulation results, using taxi traces in Qatar, show that the proposed algorithm consumes an acceptable amount of megabytes (≈31 MB) per month when the basic polling interval is set to 10 s. Furthermore, traffic simulation results demonstrate that the proposed scheme has a minimum impact on delay and travel time estimates (relative error less than 2.5%), but can produce significant degradations in fuel consumption and emission estimates if computations are made at the TMC (relative error greater than 28% and 65%, respectively). These errors can be eliminated if computations are done on the vehicle.

Cooperative Intelligent Transport Systems (C-ITS) communication technology is expected to be the near-future pioneer in the traffic management and road-safety control area by provisioning timely accurate and location-aware information. The data generated by connected vehicles may be privacy-sensitive and could be hacked by intrusive receivers. In order to prevent malicious sources from injecting untrusted data content, relevant ITS standards included security processes and protocols to deal with the potential architecture-imposed security vulnerabilities. In this paper we study the impact of these processes on time-sensitive and safety related applications. In this regard, we deeply investigate the ITS architecture integrating the security components and evaluate its performance through extensive simulations for sparse to dense network of vehicles in terms of delay and packet delivery ratio. We consider this work as an important step towards understanding the tradeoff between security and communication efficiency in V2X networks.

The number of vehicles on roads keeps increasing continuously, making the management of traffic flow, especially in big cities more and more challenging. One of the key enablers for having smooth traffic flows and better mobility is to rely on real-time traffic monitoring systems. These systems allow road operators to implement intelligent traffic management strategies such as the dynamic adjustment of timing and phasing of traffic lights and the adaptive road congestion charging. Moreover, better informed travelers will plan smartly their journeys and hence potentially contribute in reducing traffic jams. Traditional real-time traffic monitoring usually get real-time data from GPS-equipped fleets and fixed sensors installed in specific locations. In this paper, a new real-time traffic monitoring based on emerging vehicular communication systems is proposed. The system enables traffic monitoring with higher reliability, accuracy, and granularity. The cluster-based V2X traffic data collection mechanism is able to gather more than 99% of the available data and reduce the overhead to one quarter when compared to other approaches.

Cooperative vehicle-to-vehicle (V2V) communications for real-time video streaming of scalable video coded (SVC) videos is investigated, and a novel clustering method is proposed. In the proposed method, moving vehicles are grouped into cooperative clusters to enhance the distribution of the video to the cluster members. Within each cluster, vehicles communicate over IEEE 802.11p, whereas the long term evolution (LTE) system is used to send the data over long range cellular links. The simulation results show that the collaborative V2V video streaming method significantly outperforms the non collaborative case.

There has been a growing need to integrate communication technologies with transport infrastructure and vehicles. The proposed approach would spur an array of vehicular safety, traffic efficiency and infotainment applications. To address this, majority of the research has been focusing on IEEE 802.11p based vehicular communication. However, despite the efforts from standardization bodies and research consortium development and large-scale deployment of an effective framework still remained a challenge. Given the diverse performance requirements from wide spectrum of vehicular networking applications, several advocate the feasibility of LTE technology as an emerging solution. The goal of this paper is to evaluate the performance of the IEEE 802.11p standard and LTE technology for vehicular networks under various network conditions and parameter values. The results indicate that LTE outperforms IEEE 802.11p in terms of delay, reliability, and scalability, whereas IEEE 802.11p offers acceptable performance for sparse network topologies.

Named Data Networking (NDN) gives more importance to content instead of its location. On the other hand, V2X networks carry a wide variety of content such as events, traffic information and infotainment content. Therefore, NDN native capabilities in terms of caching and multicast can reduce traffic load in V2X networks and consequently decrease congestion risk. However, the communication in NDN is based on a request-response pattern while it is event based in V2X. Thus, this paper extends NDN with a Pub/Sub capability in order to provide an efficient data collection and dissemination in V2X networks. In this paper, we study the limitations of using NDN and the challenges of extending it with Pub/Sub and propose a new protocol that handles V2X characteristics. Simulation results of data dissemination shows that the number of Subscribe messages generated in vehicles present at most the one tenth of the total received Publish messages while, without the Pub/Sub extension, the number of Interests will be equal to the number of Data messages without considering message losses.

This paper presents an analysis of link asymmetry in 5.9GHz vehicular communication by means of on-road experiments, and using a standard compliant vehicular communication platform. Similar works have been conducted in the last decades, especially by relevant industrial stakeholders, but none or only little information has been disclosed to the public. The link asymmetry may have considerable impact on the performance of the adopted communication protocols, therefore it is highly important to study such a topic and share the outcomes with the researcher community; this is one of the main motivations behind this contribution. The importance of the results is twofold: first we show that the antenna position on the car roof has a considerable impact on the communication link, and second we demonstrate that the link symmetry is not as worst as can be imagined since the experiments show that a link can still have a good symmetry up to 300 meters of distance between two connected vehicles.

Cooperative schemes for critical content distribution over vehicular networks are presented and analyzed. The first scheme is based on unicasting from the base station, whereas the second is based on threshold based multicasting. Long Term Evolution (LTE) is used for long range communications with the base station (BS) and 802.11p is considered for inter-vehicle collaboration on the short range. A high mobility environment with correlated shadowing is adopted. Both schemes are shown to outperform non-cooperative unicasting and multicasting, respectively, when the appropriate 802.11p power class is used. The first scheme achieves the best performance among the compared methods, and a practical approximation of that scheme is shown to be close to optimal performance. © 2012 IEEE.

This paper designs a complete framework that anticipates QoS/QoE (Quality of Experience) degradation and proactively defines policies for LTE-connected cars (UEs) to select the most adequate radio access out of WiFi and LTE. For a particular application, the proposed framework considers the application type, the mobility feature (e.g., speed, user mobility entire/partial path, user final/intermediate destination), and the traffic dynamics over the backhauls of both LTE and WiFi networks in order to predict and allow the UE to select the best network that maximize user QoE throughout the mobility path. Simulations are conducted to evaluate the performance of the proposed framework in achieving its design objectives and encouraging results are obtained.

There is a general trend towards the decentralization of mobile operator networks. Such network decentralization will not be efficient without rethinking mobility management schemes, particularly for users moving for a long distance and/or at a high speed (e.g., vehicles). To support such highly mobile users, this paper introduces a data anchor gateway relocation method based on user mobility, history information, and user activity patterns. The performance of the proposed schemes is evaluated through simulations and encouraging results are obtained.

This paper describes a new topology management and access control technique for wireless networks developed during Daniel's Camara PhD. The main purpose of the technique is to provide a stable and well managed topology, so that other protocols can be built on the top of it. Having a stable and predictable topology is a fundamental step to enable the real utilization of wireless networks, mainly for ad hoc and sensor networks. The proposed method is based on the economy concept of free market, more specifically, in the laws of supply and demand. Each role in the defined topology has a cost; nodes trade their attachment and role in the network. The system eventually reaches a Pareto optimal allocation, what is a fair and stable configuration for all the participants. The method is distributed and flexible. Just by changing a small vector of basic prices, we can shape drastically different network topologies. The method permits even the modification of the topology characteristics of already deployed networks. This kind of feature is specially appreciated in the context of Public Safety Networks (PSN). In this kind of network, the same rescue team may have drastically different needs, depending on the kind of disaster they are attending.

Nowadays, wireless 802.11 access points (APs) are increasingly widespread in urban and sub-urban areas. Besides part of them offer free access, hence such infrastructure can provide intermittent Internet access to vehicles for opportunistic applications like software or digital maps updates, vehicle diagnostic reporting, and certificates/pseudonyms renewing.

Vehicular communication systems are becoming one of the most emerging research areas. Many efforts have been made to provide new applications and communication protocols adapted to this new kind of networks. The performance evaluation of these proposals is a crucial step for their validation. Therefore, the need of a new open-source, realistic and integrated simulation environment for vehicular networks is a fundamental and extremely pervasive motivation behind this work. In this paper, we propose simITS, an open-source simulation platform, aiming at a realistic evaluation of protocols for large scale vehicular networks. SimITS aims to simulate properly both road traffic conditions and wireless communications characteristics and at the same time to ensure the real time exchange of simulation data between them. Additionally, a new communication protocol stack designed for vehicular communications has been implemented. Finally, we validate the platform by a basic simulation study.

The IEEE Task Group has approved recently the 802.11p amendment to enable efficient short range communications for vehicular networks by introducing multiple enhancements at the physical and MAC layer. It defines a control frequency channel for control and most critical data packets and one or several service frequency channels for less critical packets. In this paper, we propose an analytical model for the 802.11p operations in the control frequency. It captures all suggested enhancements important for exchanging data packets generated by road safety applications. We showed through diverse simulations scenarios that our proposed model is able to reproduce expected results. We consider this work as an important step toward understanding the performance of 802.11p-based vehicular communications and the model can be employed in the simulations of safety applications in large scenarios.

This work presents an auxiliary mechanism to aid in the distribution of warning messages for Emergency Alert Systems (EAS). The main objectives of the proposed mechanism are to speed up and broaden the warning messages distribution process to provide to the public faster access to crucial information. EAS are public safety message systems designed to enable authorities to address the population in case of an emergency. This kind of system has been in use for a long time, however traditionally they are composed of radio/TV broadcast messages or sirens spread through endangered regions. This system on the other hand addresses the next generation of EAS systems that will be based on wireless computer networks and satellite technologies. The method proposed here is a complementary way to spread warning messages that not only successfully broadens the EAS reachability but also significantly speeds up the messages distribution process.

This paper presents the implementation and evaluation of a distributed topology management algorithm for public safety networks (PSNs) to implement the CHORIST architecture. Topology management for this kind of network is a mission critical problem, for a mission critical network. PSNs are the networks installed by the authorities to coordinate relief/rescue efforts in case of disasters. The main concerns for PSNs are rapid deployment and survivability. The whole operation and teams coordination schema depends on how well deployed the network was and how stable and reliable the network is during its lifetime. The more stable the network structure is in a rescue operation field the better. The proposed algorithm is able to dynamically adapt to the nodes mobility thus maintaining the desired topology.

This work focuses on increasing the network coverage for stream traffic in disaster scenarios, which is often critical for preventing damages to property and, most importantly, loss of life. The technique described here, based on the so-called virtual access points (VAPs), and increases the network coverage in a non intrusive and transparent way. It creates a distributed and cooperative cache among the mobile nodes in the affected area. When using the VAP technique, nodes cooperatively work as virtual access points rebroadcasting messages they have in their own cache helping nodes that didn't have access to those pieces of message. The main advantages include that the proposed technique does not rely on any specific characteristic of the network, is transparent, and achieves highly improves the efficiency of stream traffic dissemination resulting in much lower message loss. Our results show that VAPs greatly enhance network coverage. In fact, for some of the scenarios presented, it allows the system to remain operational under conditions it would otherwise be inadequate for stream traffic.

We consider a wireless sensor network with n sensor nodes. The sensed data needs to be transferred in a multi-hop fashion to a common processing center. We consider the standard data sampling/sensing scheme where the sensor nodes have a sampling process independent of the transmission scheme. In this paper, we study the problem of optimizing the end-to-end delay in a multi-hop single-sink wireless sensor network. We prove that the delay-minimization objective function is strictly convex for the entire network. We then provide a distributed optimization framework to achieve the required objective. The approach is based on distributed convex optimization and deterministic distributed algorithm without feedback control. Only local knowledge is used to update the algorithmic steps. Specifically, we formulate the objective as a network level delay minimization function where the constraints are the reception-capacity and service-rate probabilities. Using the Lagrangian dual composition method, we derive a distributed primal-dual algorithm to minimize the delay in the network.We further develop a stochastic delay control primal-dual algorithm in the presence of noisy conditions. We also present its convergence and rate of convergence. The proposal is extensively evaluated by analysis and simulations.

In this paper we consider the problem of dissemination of stream based traffic using access points as roadside equipment. We consider how areas outside direct coverage can still be reached by means of other vehicles acting as virtual access points (VAPs). The developed technique, allows transparently extending the reach of roadside access points to uncovered road areas. VAPs are designed to avoid interference, operating in regions bounded outside any AP. The simulations show the presented mechanism to exhibit gain, in terms of received messages, of 30% and perhaps more significantly, that streaming data delivery becomes feasible.

Stability and delay constraints have significant impact on the design and operation of wireless sensor networks. In this paper, we propose a closed architecture for data sampling in wireless sensor networks. Examples show that the proposed scheme outperforms the traditional layered scheme, both in terms of stable operating region as well as the end-to-end delays. We then propose a distributed routing scheme for a broad class of wireless sensor networks which converges (in the Cesaro sense) to the set of Cesaro-Wardrop equilibria. The scheme is based on multiple time-scale stochastic approximation algorithms. Convergence is established using standard results from the related literature and validated by simulation results. Our algorithm can adapt to changes in the network traffic and delays.

Underwater acoustic sensor networks (UASNs) consist of sensors that are deployed to perform collaborative monitoring of tasks over a given volume of water. The quality of the underwater acoustic link is highly unpredictable, since it mainly depends on fading and multipath, which are not easily modeled phenomena. This is return severely degrades the performance at higher layers such as extremely long and variable propagation delays. In addition, this variation is generally larger in horizontal links than in vertical ones. In this paper, we analyze a modulation scheme and associated receiver algorithms. This receiver design take advantage of the time reversal (phase conjugation) and properties of spread spectrum sequences known as Gold sequences. This technique improves the signal-to-noise ratio (SNR) at the receiver and reduces the bit error rate (BER). We then applied the phase conjugation to the case of network communication. We show that this approach can give almost zero BER for a 2-hop communication compared to single hop. This link layer information can be used at the network layer to formalize routing decisions. We show these improvements by means of analytical analysis and simulations.

Wireless sensor networks are commonly used to monitor and control the physical world. To provide a meaningful service such as disaster and emergency surveillance, meeting real-time constraints and the stability of transmit queues are the basic requirements of communication protocols in such networks. In this paper, we propose a closed architecture with two transmit queues at each sensor i, i.e., one for its own generated data, and the other for forwarding traffic. Our first main result concerns the stability of the forwarding queues at the nodes. It states that whether or not the forwarding queues can be stabilized (by appropriate choice of weighted fair queueing weights) depends only on routing and channel access rates of the sensors. Further, the weights of the weighted fair queues play a role in determining the tradeoff between the power allocated for forwarding and the delay of the forwarding traffic. We finally propose a distributed routing scheme for a broad class of wireless sensor networks. Each link is assigned a weight and the objective is to route through minimum weight paths using iterative updating scheme. The proposal is validated by analytical analysis and simulations.

Distributed systems based on networked sensors and actuators with embedded computation capabilities are commonly used to monitor and control the physical world. To provide a meaningful service such as disaster and emergency surveillance, meeting real-time-and-energy constraints and the stability of transmit queues are the basic requirements of communication protocols in such networks. In settings with sparse distribution of actuator nodes, multi-hop routing is traditionally used to relay information to a remote sink. A problem with this approach is that the loss of connectivity of actuator nodes may lead to partitioning of the network. In this paper, we address the problem of minimizing power consumption at each actuator node and minimizing assignment overhead at each sensor node while ensuring network connectivity. We propose that each actuator is enabled with two wireless interfaces: one to communicate with its assigned sensor network, and the other to communicate with the network of neighboring actuators. At any instant of time, an actuator can adjust its transmit power level to ensure connectivity and pro-actively inform its attached sensor network in case of mobility. These strategies have an associated cost. We show in this paper that at any instant of time, the strategy chosen by an actuator to adjust power and control-overhead due to mobility are optimal subject to constraints. The proposal is validated by means of analysis and simulations.

In this paper, we evaluate the performance bounds of 802.16 technology under different physical and MAC parameters settings. The saturation throughput that can be reached in 802.16 networks is investigated through several scenarios in which we vary for instance the frame duration, the channel bandwidth, and the modulation and coding scheme in use. An original analytical framework was developed based on technical properties and system profiles specified by the IEEE 802.16 standard for systems using the Wireless MAN-OFDM (Orthogonal Frequency Division Multiplexing) air interface. The obtained results outline the importance of considering the MAC and physical overhead when evaluating the performance of 802.16 networks. They also highlight the impact of packing and fragmentation techniques, proposed by IEEE 802.16 standard, on the MAC performance and show the trade-off between decreasing the channel bandwidth and increasing the resulting saturation throughput.

Delay and energy constraints have a significant impact on the design and operation of wireless sensor-actuator networks (SANETs). Furthermore, preventing sensor nodes from being inactive is very critical. The problem of sensor inactivity arises from the path loss and fading that degrades the quality of the signals transmitted from actuators to sensors, especially in anisotropic deployment areas, e.g., rough and hilly terrains. Sensor data transmission in SANETs heavily relies on the scheduling information that each sensor node receives from its associated actuator. Therefore if the signal containing scheduling information is received at a very low power due to the impairments introduced by the wireless channel, the sensor node might be unable to decode it and consequently it will remain inactive. In this paper, it is proposed that each sensor node transmits its data to only one of the actuators. However all actuators cooperate and jointly transmit scheduling information to sensors with the use of beamforming. This results to an important reduction in the number of inactive sensors comparing to single actuator transmission for a given level of transmit power. The reduction is due to the resulting array gain and the exploitation of macro-diversity that is provided by the actuator cooperation. In order to maximize network lifetime and attain minimum end-to-end delays, it is essential to optimally match each sensor node to a particular actuator and find an optimal routing solution. A distributed solution for optimal actuator selection subject to energy-delay constraints is also provided.

This paper describes a technique to apply formal methods to verify protocols for mobile ad hoc networks. In contrast to other related proposals, our solution does not attempt to model any particular network configuration. Instead, our solution focuses on the possible implications caused by network configurations to the behavior of a routing protocol for MANETs. Following this strategy we were able to find design errors in some well established protocols. The proposed technique uses formal verification, more specifically model checking, to detect, in a simple way, problems such as routing loops, delivery message failures and errors in the protocol state machine.

Within the extent of research activity in the field of vehicular networking, notwithstanding the quantity of simulative studies carried out on protocols performance, the impact of vehicular mobility characterization has been often overlooked. Realistic mobility models are seldom employed, and when used, no comment is usually provided on the different effects that such models have on the results with respect to simpler mobility descriptions. In this paper, we address this issue, and analyze the impact that various levels of details in vehicular mobility modeling have on the simulation of networking protocols.

In this paper, we propose a new QoS architecture for PMP 802.16 systems operating in TDD mode over wirelessMAN-OFDM physical layer. It includes a call admission control policy and a hierarchical scheduling algorithm. The CAC policy we propose adopts a min-max fairness approach making efficient and fair use of available resources. The proposed scheduling algorithm flexibly adjusts uplink and downlink bandwidth to serve unbalanced traffic while considering adaptive modulation and coding (AMC) scheme. The efficiency of the proposed QoS architecture is revealed through simulation.

Sensor-actuator networks are often limited in battery capacity and processing power. Therefore, it is exigent to develop solutions that are both energy and delay efficient. In this paper, we propose a low-energy and delay-sensitive TDMA based MAC for wireless sensor-actuator networks (SANETs). These networks are organized into clusters and each cluster is managed by a single actuator. To avoid inter- cluster downlink interference, we introduce an easy use of CDMA codes. The actuators schedule sensors to reduce the total network energy consumption per successful transmission. We identify the advantages of our proposal over existing TDMA-MAC schemes for cluster-based sensor networks. Our simulation results demonstrate that the proposed MAC greatly improves the SANET lifetime and achieves a good trade-off between the packet delay and sensor energy consumption.

Geo-localization information is a key component for providing location-based services for Intelligent Transportation Systems (ITS). Generally obtained by GPS devices and transmitted by Wireless Vehicular Communications, geo-localization in ITS represents a promising approach to reach objectives such as an increased road safety, transport efficiency, or on-the-road services. Despite its popularity, the issue of the overhead generated by the transmission of geo-localization data has not been addressed by the ITS community. In this paper, we first discuss the format of the information provided by GPS devices and propose a flexible message structure for exchanging geo-localization data. Then, we illustrate the significant overhead generated by the transmission of such information and propose a compression method achieving up to 70% overhead reduction without loss of precision. We finally test our method on the OLSR routing protocol.

Nowadays, researchers show more and more interests to vehicular ad hoc networks (VANETs), which are a specific instance of mobile ad hoc networks (MANETs) where nodes are vehicles. In VANETs, vehicles have no energy resource constraint which could extend coverage and network lifetime, but have a high mobility patterns that cause frequent and fast topology changes. Consequently, VANETs have particular research interests, like dedicated MAC and routing optimization. In our previous work, we have proposed movement prediction-based routing (MOPR) concept for VANETs, which improves the routing process by selecting the most stable route in terms of lifetime with respect to the movement of vehicles. And in this paper, we present how this MOPR concept can be applied to position-based routing protocols, and how it improves their performances. Based on simulation results we compare MOPR with the position-based routing protocol GPSR and another movement-based routing protocol called MORA.

In order to exploit the properties of multimedia applications in IEEE 802.11-based wireless networks in more appropriate ways, we interest in the dynamic and efficient tuning of the MAC protocol by taking into account the inherent characteristics of this kind of applications. We focus on the try limit parameter used at the 802.11 MAC layer to limit the number of retransmissions of a data frame by a source until the reception of a link-level acknowledgment from the destination. Based on analytical preliminaries, we determine the optimal value of this parameter in order to achieve an expected average end-to-end delay or a maximum packet loss rate. Moreover, an approximated value of the try limit parameter optimizing both QoS criteria (delay and packet loss rate) could also be obtained. Furthermore, these values are approximated dynamically using a simple algorithm that is easily implementable in 802.11 protocol.

Satellites are expected to have an important role in providing the Internet protocol (IP) multicast service to complementing next-generation terrestrial networks. In this paper, we focus on the deployment of IP multicast over the next generation of digital video broadcasting-based geosynchronous earth orbit satellites supporting multiple spot beams and on-board switching technologies. We propose a new encapsulation scheme optimized for IP multicast, which has two distinct modes enabling two alternative on-board switching approaches: the self-switching and the label-switching. We also detail a set of mechanisms and protocols for ground stations, as well as for the on-board processor to allow an efficient multicast forwarding in this type of environment, while reducing the load of control and data messages in the satellite segment, and building efficient multicast delivery trees reaching only the spot beams containing at least one member of the corresponding multicast session. To integrate satellite links in the terrestrial Internet, we present satellite multicast adaptation protocol (SMAP), a protocol which is implemented in satellite stations to process incoming protocol independent multicast-sparse mode (PIM-SM) messages sent by terrestrial nodes to the satellite system. SMAP helps to update the tables required for the mapping between IP packets and MPEG-2 data segments, their switching on board the satellite, and their filtering at the satellite receivers.

Despite a decade of research and development, multicast has not yet been deployed on a global scale. Among the difficulties with the current infrastructure are inter-multicast fairness support, multicast congestion control, and multicast routing. We focus on the inter-multicast fairness issue which addresses the way how the network resources are shared between competing multicast flows. We propose a simple and scalable single FIFO queue-based active queue management mechanism called MFQ (multicast fair queuing) to achieve the desired inter-multicast fairness. MFQ interacts with an external multicast bandwidth allocation module which implements a pre-defined inter-multicast fairness function. To guarantee a fine-grained packet queuing/dropping, MFQ uses a novel bandwidth sharing notion, called multicast allocation layer (MAL). Based on this notion, MFQ classifies multicast packets into layers and adjusts their weights in order to provide a bandwidth sharing being as close as possible to that given by the fluid model algorithm. Simulation results demonstrate that MFQ achieves the expected allocation for both responsive and non-responsive multicast flows. We validate our findings by analyzing the impact of network and groups dynamics on the expected bandwidth allocation and comparing it to that obtained by MFQ. Furthermore, we show that MFQ converges very fast to a stable state and easily adapts itself to the dynamic change of the flows weights.

As the satellite technology will be one of the main components of the next generation Internet (NGI), a naturally occurring question concerns the feasibility of providing an efficient satellite-based Internet access. In this paper, we are interested in the problem of the planning of satellite-terrestrial hybrid networks for the multicast transfer. We first develop an architectural model for such type of networks, then we define the problem and we propose a planning heuristic that determines the suboptimal positions of satellite uplinks in a given terrestrial network. The proposed method minimizes the mean cost (the number of branches) of multicast trees for the unreliable multicast and the mean packet transfer delay for the reliable multicast. In addition, we develop a configuration policy of PIM-SM in hybrid networks concerning the choice of the list of rendezvous points (RPs) and the switching from the RP-routed tree to the shortest path tree. The obtained results demonstrate the ability of the proposed methods (the planning heuristic and the PIM-SM configuration policy) to improve the multicast performance criteria and to determine effectively the satellite uplink positions using PIM-SM combined with UDLR (unidirectional link routing).

Our main focus here is to study the IP multicast service behaviour over the next-generation of satellite-terrestrial hybrid networks for which we develop a general architecture and we enumerate their main characteristics. We first focus on the Internet Group Membership Protocol (IGMP) feedback implosion problem and we present the exponential feedback raise that able to provide sufficiently stable expectation values across a large group size. Then, we propose and compare different approaches that can be used to enable the multicast in the on-board satellite switch. We show that the approach based on maintaining a multicast beams table (MBT) containing the list of spot beams concerned by each multicast group is the most suitable approach because it allows an efficient and transparent integration of satellite links in the Internet. In fact, the on-board switch monitors the IGMP reports and queries sent over the satellite link and update the MBT entries. We also turn our attention to multicast routing protocols. We present some undesirable behaviour of DVMRP, PIM-DM, and PM-SM. For DVMRP and PIM-DM, we identify some configurations where the satellite receivers may receive duplicated packets and we propose a method to overcome this problem. We then develop a configuration policy of PIM-SM in hybrid networks concerning the choice of the list of rendezvous point (RPs) and the switching from the RP-routed tree to the shortest path tree.