Ahmad Sardouk

Crisis management using MAS-based wireless sensor networks

Wireless communication is increasingly used to manage large-scale crises (e.g., natural disasters or a large-scale city fire). Communication has traditionally been based on cellular networks. However, real-life experience has proven that the base stations of these networks may collapse or become unreachable during a crisis. An incident commander must also know as much information as possible about the occurring events to control them quickly and efficiently. This paper thus proposes a crisis management approach that overcomes the problems encountered by the base stations and insures relevant, rich and real-time information about events. This approach is based on wireless sensor networks, which are distributed in nature with no need for infrastructure and could be deployed in dangerous and inaccessible zones to gather information. Our proposal uses a multi-agent system as a software layer. The multi-agent system aims to improve the wireless sensor network performance by allowing cooperation between sensor nodes, offering better lifetime management and virtualizing the application layer. This virtualization supports several required applications simultaneously, including event monitoring and object tracking. Through successive simulations, we prove the importance of our approach in crisis management using several criteria to estimate the positions error in object tracking, end-to-end delay and wireless sensor network lifetime management.

Traffic adaptation in wireless mesh networks: Fuzzy-based model

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.

Toward Fuzzy Traffic Adaptation Solution in Wireless Mesh Networks

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.

An efficient and fair congestion control protocol for IEEE 802.11-based Wireless Mesh Networks

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.

Factors that May Influence the Performance of Wireless Sensor Networks

The Wireless Sensor Networks (WSNs) are penetrating more and more our daily life. They are used in a large type of applications as supervision, tracking and control in military, environmental, medical and several other domains. Therefore, new approaches and protocols are proposed every day in order to optimise the performance of the WSNs and to increase their reliability and quality of service. These new protocols take into consideration the challenges of the WSN and they are built up some key factors (parameters and concepts) to achieve their goals.

Neighborhood-Aware and Overhead-Free Congestion Control for IEEE 802.11 Wireless Mesh Networks

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.

A Multi-criterion Data Aggregation Scheme for WSN

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

WIRS: Resource Reservation and Traffic Regulation for QoS Support in Wireless Mesh Networks

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.

Information-Importance Based Communication for Large-Scale WSN Data Processing

Gathering information in an energy-efficient and scalable manner from a wireless sensor network is always a basic need. In this work, we use the multi-agent approach in order to build an Information-Importance Based Communication for large scale wireless sensor network data processing. The principal goal of our proposition is to tackle the problem of network density and scalability in an energy efficient manner. Simulation results are provided to illustrate the efficiency of our proposition.

A Strategy for Multi-Agent Based Wireless Sensor Network Optimization

The multi-agent approach has been proposed in the literature as a solution for data gathering, and routing in Wireless Sensor Networks (WSNs). In these propositions, the knowledge of an agent is generally limited to a single parameter such as the energy of the sensor node and/or to the address of its next hop in a routing protocol proposition. In this paper, we propose a strategy for the agent to make a more appropriate decision to cooperate or not in a data gathering session. This strategy uses, in addition to the energy of the node, several parameters from the local view of the agent as the position of the node within the network, the network density, and the information importance degree. Through successive simulations, this strategy has proved its ability to manage cleverly the power consumption of the sensor nodes and hence to extend the WSN life time.