International audience

Wireless technologies are becoming an essential part of our daily life. These technologies are expected to provide a wide variety of real-time applications; hence, there is a vital need to provide quality-of-Service (QoS) support. One of the key mechanisms to support QoS is traffic regulation. The basic idea behind traffic regulation is to measure the network state (e.g., load) in order to adapt the rate of carefully selected application flows. In this paper, we propose a novel model, called FuzzyWMN, which can be used to implement traffic adaptation in Wireless Mesh Networks (WMNs).The objective of FuzzyWMN is to compute the rate adaptation to apply to application flows according to the current network state; it relies on two parameters to meet this objective: (1) packet delays between sources and destinations; and (2) buffer occupancy of network nodes. The proposed model combines the essential notions of both fuzzy logic theory and Petri nets; this enables FuzzyWMN to realize traffic adaptation in networks characterized by information uncertainty and imprecision due to the dynamic traffic behavior, channel interferences, etc. Extensive simulations show that FuzzyWMN achieves stable end-to-end delay and good throughput under different network conditions.

It has been reported that the IEEE 802.11 MAC protocol and the TCP congestion control are highly problematic in terms of flow starvation in wireless mesh networks (WMNs). However, the economic features of IEEE 802.11 make it the commonly-used MAC protocol in WMNs. Therefore, solving starvation at the transport layer seems to be more appropriate. Indeed, the main starvation cause in TCP is that congestion is managed as a link-based problem. However, since bandwidth is a spatially-shared resource in WMNs, congestion is a neighborhood phenomenon that should be handled using mutual cooperation within a congested neighborhood. Such cooperation considerably consumes the already scarce bandwidth of WMNs causing more congestion. In this paper, we propose a neighborhood-aware and overhead-free congestion control scheme (NICC) that solves the starvation problem without impacting the scarce bandwidth of WMNs. NICC makes use of some underexploited fields in the IEEE 802.11 frame header, without modifying the standard frame size, to provide an overhead-free multi-bit congestion feedback; being overhead-free, this feedback allows performing neighborhood cooperation without generating control overhead. Furthermore, being multi-bit, it yields source nodes a fine-grained indication of the congestion degree, providing accurate rate control. The NICC performance in terms of starvation avoidance and bandwidth efficiency is proven through extensive simulations.

Wireless mesh networks (WMNs) have recently emerged as a promising technology for next-generation of wireless communications. In WMNs, admission control is deployed to control traffic loads and to prevent the wireless mesh backbone from being overloaded. Existing admission control protocols could be classified as either stateful or stateless approaches, based on network state information. Both the approaches have their limitations; the stateful models suffer from the scalability issue, while the stateless ones have the false admission problem. This paper introduces a hybrid admission control model for WMNs, based on a temporal resource reservation and three traffic regulation schemes. In particular, we propose an analytical model to compute the appropriate regulation ratio for accepted flows and to guarantee that the congestion at intermediate nodes does not exceed a threshold value. In our model, the congested node may specify the moment of session re-establishment, besides of the new rate at which the session should transmit its data packets. Using extensive simulations, we demonstrate that our model achieves high resource utilization by computing new sessions rates in a dynamic traffic-load environment, and by satisfying the quality of service (QoS) constraints in terms of delay and packets loss.

Severe unfairness and even complete starvation may occur when using TCP-like congestion control in IEEE 802.11-based Wireless Mesh Networks (WMNs). Indeed, IEEE 802.11 is inherently unfair; however, economies of scale make it the commonly used MAC protocol in WMNs. Moreover, TCP-like protocols do not account for links interdependency within a neighborhood. In WMNs, congestion should be mutually handled using explicit coordination among neighboring contending links. Furthermore, the set of flows that should be regulated, to control congestion, must include all those traversing a congested neighborhood. However, neighborhood coordination and flows notification significantly consume the already scarce bandwidth. In this paper, we propose NICC as neighborhood-based and overhead-free congestion control protocol aiming to avoid starvation without disturbing the bandwidth resources. Instead of experiencing IEEE 802.11 as a handicap, NICC proposes a lightweight optimization of some underexploited fields in the 802.11 frames header so as to provide implicit multi-bit congestion feedback. Such feedback ensures accurate rate control without inducing additional overhead. The effectiveness of NICC in terms of starvation avoidance and bandwidth efficiency is proved through in-depth simulation.

Wireless mesh networks (WMNs) are expected to be a next step toward future generation of wireless networks due to their rapidly deployable nature and to the wide variety of their potential use. On the other hand, the daily increase of multimedia applications over wireless networks has generated a vital need to provide Quality of Service (QoS) support in WMNs, and works in this area are not sufficient for the moment. In this paper, we propose a QoS model, named WiRS, to support real time traffic over WMNs. WiRS consists of an admission control and two traffic regulation schemes. The admission control is based on a temporary reservation process allowing multiple flows to opportunistically benefit from reserved resources when they are not used by their correspondent flow. The traffic regulation schemes aim to dynamically adjust the injected traffic into the mesh backbone in order to avoid the congestion and to maintain the QoS requirements. A service differentiation mechanism is provided also through one of the regulation schemes in order to control the best effort traffic. Extensive simulations show that our proposal is able to provide stable end-to-end delay, high throughput and improved packet delivery ratio.

The emergence of real-time applications and their widespread usage in communication have generated the need to provide quality-of-Service (QoS) support in wireless networks environments. One of the most crucial mechanisms of a model for providing QoS support is the traffic regulation. In the aim of better representing and analyzing the decision making policy of the traffic adaptation process in wireless mesh networks (WMN), we propose a novel model named FuzzyWMN. The proposed model combines the essential notions of both fuzzy logic theory and Petri nets; this enables FuzzyWMN to achieve the traffic adaptation process in the context of dynamic network events characterized by the uncertainty and imprecision information, due to the dynamic traffic behavior, channels interference, etc. The evaluation of FuzzyWMN performances, compared to AIMD-SWAN and IEEE 802.11, was studied under different network and traffic conditions. The promising results obtained from extensive simulations confirm that the traffic adaptation based on the fuzzy design can achieve stable end-to-end delay, and good throughput under different network conditions.

Nowadays, real time traffic over wireless networks is increasing sharply. In addition, network scale is larger due to new facilities as offered by wireless mesh networks. However, the differences between (1) the infrastructure capacities, (2) the end users devices technologies, (3) the number of users, and (4) the number of real time applications are implying the need of more dynamic quality of service (QoS) models. Traditional QoS models are not always suitable to fill out the gap between the four cited points. We are mentioning more QoS degradation due to network congestion. Therefore, in this paper, we propose a novel, dynamic and persistent traffic adaption model, called FTAM. Its main role is to avoid as maximum as possible network congestion. FTAM is based on the fuzzy logic, which is known by its dynamicity and efficiency in uncertain environment. By monitoring the nodes queues evolution, FTAM estimates network congestion and makes the suitable traffic adaptation step. Extensive simulations have proved the efficiency of FTAM in terms of real time traffic QoS guarantee and preventive congestion control.

In the context of forest fire management, wireless communication is an indispensable tool. It insures events information transmission and communication between fire defenders. Traditionally, cellular networks (CNs) are used during crisis. However due to the lack of population in far forests, CNs suffer from coverage problems. In addition, the experience has proved some reachability and capacity problems of CNs. In this paper, we propose a mesh and sensor network model as a wireless communication support for forest fire management. The sensor nodes (SNs) penetrate dangerous zones to aggregate events' data and to guide rescuers to safe paths. The mesh nodes (MNs) insure communication between rescuers, and data and video transfer. Our models are empowered by a multi-agent system (MAS) to enforce the autonomy of the nodes and a fuzzy logic model to guarantee the quality of service (QoS). The simulations have proved the efficiency of our models to help in the management of forest fire.

During a crisis situation, the incident commanders have to tackle several problems simultaneously, e.g., (1) the monitoring of a crisis evolution, (2) guiding and tracking of rescue persons and intervention robots, (3) monitoring rescue persons' health, etc. Thus, several solutions based on wireless sensor networks (WSNs) and cellular networks have been proposed. However, the real life experience has proved that the cellular networks' base stations may be collapsed or unreachable during a crisis situation. In addition, the WSNs have been generally deployed for one application, e.g., monitoring of an occurring event. However, today technologies offer sensor nodes (SN) with higher processing and communication capacity. Based on these capacities, this paper proposes a WSN solution, for crisis management, which is not based on any base station infrastructure. This solution proposes a tracking and data aggregation methods that could be run simultaneously to treat the three above mentioned problems. It is also empowered by a multi-agent system (MAS), which allows the SNs to cooperate and to better manage their batteries. Finally, the proposed solution has proved, through successive simulations, its efficiency in terms of tracking precision, end-to-end communication delay and power optimization.

The basic role of a wireless sensor network (WSN) is to collect information from the environment by many sensor nodes (SNs). The SN typically has a finite battery life and nodes' failures can lead to network partition. Therefore, it is important to minimize the energy usage of each sensor node and to manage the power of SN in critical position that their failure could divide the network. The current paper proposes a data aggregation scheme based on a multi-agent system to reduce the amount of communicated information and hence to reduce the power consumption. In addition, this approach manages the power of each SN following several criteria like its resident power, the importance of its information, the network density and its position within the WSN. Through successive simulations, in different network scales, the proposed algorithm proved interesting results in term of power consumption optimization and power management of nodes in critical positions.