Secure Routing and Medium Access Protocols inWireless Multi-hop Networks

While the rapid proliferation of mobile devices along with the tremendous growth of various applications using wireless multi-hop networks have significantly facilitate our human life, securing and ensuring high quality services of these networks are still a primary concern. In particular, anomalous protocol operation in wireless multi-hop networks has recently received considerable attention in the research community. These relevant security issues are fundamentally different from those of wireline networks due to the special characteristics of wireless multi-hop networks, such as the limited energy resources and the lack of centralized control. These issues are extremely hard to cope with due to the absence of trust relationships between the nodes. To enhance security in wireless multi-hop networks, this dissertation addresses both MAC and routing layers misbehaviors issues, with main focuses on thwarting black hole attack in proactive routing protocols like OLSR, and greedy behavior in IEEE 802.11 MAC protocol. Our contributions are briefly summarized as follows. As for black hole attack, we analyze two types of attack scenarios: one is launched at routing layer, and the other is cross layer. We then provide comprehensive analysis on the consequences of this attack and propose effective countermeasures. As for MAC layer misbehavior, we particularly study the adaptive greedy behavior in the context of Wireless Mesh Networks (WMNs) and propose FLSAC (Fuzzy Logic based scheme to Struggle against Adaptive Cheaters) to cope with it. A new characterization of the greedy behavior in Mobile Ad Hoc Networks (MANETs) is also introduced. Finally, we design a new backoff scheme to quickly detect the greedy nodes that do not comply with IEEE 802.11 MAC protocol, together with a reaction scheme that encourages the greedy nodes to become honest rather than punishing them

Secure Routing and Medium Access Protocols inWireless Multi-hop Networks

While the rapid proliferation of mobile devices along with the tremendous growth of various applications using wireless multi-hop networks have significantly facilitate our human life, securing and ensuring high quality services of these networks are still a primary concern. In particular, anomalous protocol operation in wireless multi-hop networks has recently received considerable attention in the research community. These relevant security issues are fundamentally different from those of wireline networks due to the special characteristics of wireless multi-hop networks, such as the limited energy resources and the lack of centralized control. These issues are extremely hard to cope with due to the absence of trust relationships between the nodes. To enhance security in wireless multi-hop networks, this dissertation addresses both MAC and routing layers misbehaviors issues, with main focuses on thwarting black hole attack in proactive routing protocols like OLSR, and greedy behavior in IEEE 802.11 MAC protocol. Our contributions are briefly summarized as follows. As for black hole attack, we analyze two types of attack scenarios: one is launched at routing layer, and the other is cross layer. We then provide comprehensive analysis on the consequences of this attack and propose effective countermeasures. As for MAC layer misbehavior, we particularly study the adaptive greedy behavior in the context of Wireless Mesh Networks (WMNs) and propose FLSAC (Fuzzy Logic based scheme to Struggle against Adaptive Cheaters) to cope with it. A new characterization of the greedy behavior in Mobile Ad Hoc Networks (MANETs) is also introduced. Finally, we design a new backoff scheme to quickly detect the greedy nodes that do not comply with IEEE 802.11 MAC protocol, together with a reaction scheme that encourages the greedy nodes to become honest rather than punishing them

FLSAC: A new scheme to defend against greedy behavior in wireless mesh networks

The most commonly used medium access mechanism in wireless mesh networks is based on the CSMA/CA protocol. This protocol schedules properly the access to the medium among all the competing nodes. However, in a hostile environment, such as wireless mesh networks (WMNs), selfish or greedy behaving nodes may prefer to decline the proper use of the protocol rules in order to increase their bandwidth shares at the expense of the well-behaving nodes. In this paper, we focus on such misbehavior and in particular on the adaptive greedy misbehavior of a node in the context of WMN environment. In such environment, wireless nodes compete to gain access to the medium and communicate with a mesh router (MR). In this case, a greedy node may violate the protocol rules in order to earn extra bandwidth share upon its neighbors. In order to avoid its detection, this node may adopt different techniques and switch dynamically between each of them. To counter such misbehavior, we propose to use a fuzzy logicbased detection scheme. This scheme, dubbed FLSAC, is implemented in the MR/gateway to monitor the behavior of the attached wireless nodes and report any deviation from the proper use of the protocol. The simulation results of the proposed FLSAC scheme show robustness and its ability to detect and identify quickly any adaptive cheater. © 2009 John Wiley & Sons, Ltd

A Multi-Agent Based Vehicles Re-routing System for Unexpected Traffic Congestion Avoidance

As urbanization has been spreading across the world for decades, the traffic congestion problem becomes increasingly serious in most of the major cities. Among the root causes of urban traffic congestion, en route events are the main source of the sudden increase of the road traffic load, especially during peak hours. The current solutions, such as on-board navigation systems for individual vehicles, can only provide optimal routes using current traffic data without considering any traffic changes in the future. Those solutions are thus unable to provide a better alternative route quickly enough if an unexpected congestion occurs. Moreover, using the same alternative routes may lead to new bottlenecks that cannot be avoided. Thus a global traffic load balance cannot be achieved. To deal with these problems, we propose a Multi Agent System (MAS) that can achieve a trade-off between the individual and global benefits by giving the vehicles optimal turn suggestions to bypass a blocked road ahead. The simulation results show that our strategy achieves a substantial gain in average trip time reduction under realistic scenarios. Moreover, the negative impact of selfish re-routing is investigated to show the importance of altruistic re-routing applied in our strategy

An Altruistic Prediction-Based Congestion Control for Strict Beaconing Requirements in Urban VANETs

Periodic Beacon Messages are one of the building blocks that enable the operation of VANET applications. In vehicular networks environments, congestion and awareness control mechanisms are key for a reliable and efficient functioning of vehicular applications. In order to control the channel load, a reliable mechanism allowing real time measurements of parameters like the local density of vehicles is a must. These measurements can then serve as an input to perform a fast adaptation of the transmit parameters. In this context, considerable efforts have been directed in the recent years towards designing flexible yet robust protocols solving this problem; yet, very few have considered a proactive adaptation of the transmit parameters as a preventive measure from channel load peaks. To this end, we take the opportunity to introduce P&A-A, a new congestion control protocol that performs a joint adaptation of the transmit rate and power, relying on an altruistic short-term prediction algorithm that estimates the vehicular density around a given vehicle within the next short while. Additionally, P&A-A adapts the transmit parameters in a way that guarantees the strict beaconing requirements and satisfies the level of awareness required for the operation of most critical VANET applications. The results of the simulations performed in a realistic scenario justify our theoretical considerations and confirm the efficiency and the effectiveness of our protocol by showing significant improvements in terms of network performance (up to 8% and 14% improvement in collision rate; and up to 10% and 20% increase in busy ratio compared to our previous scheme and the ETSI schemes respectively) as well as the achieved level of awareness (higher coverage with higher transmission rate and power in dense scenarios, and up to 8% and 55% improvement in density perception accuracy compared to our previous scheme and the ETSI schemes respectively)

Smart Beacons Transmission Rate and Power Control for Enhanced Vehicular Awareness in VANETs.

In this work, we are interested in periodic beacons transmission, the main cause of the Control Channel (CCH) congestion and the major obstacle delaying the progress of safety messages dissemination in VANETs. In order to offload the network, solutions that range from transmit rate to transmit power adaptations including hybrid solutions have been proposed. Although some of these solutions have managed to successfully reduce the load on the wireless channel, none, to the best of our knowledge, have considered the impact of the applied adaptation scheme on the overall level of awareness among vehicles and its quality. ETSI TS released a technical specification stating a limit for the minimum beacons transmit rate in order to maintain a good level of awareness among vehicles and ensure a certain accuracy in VANET applications. In this paper, we propose to jointly adapt both transmit rate and power in a new smart way that guarantees a strict beaconing frequency as well as a good level of awareness in closer ranges, while maintaining a marginal beacons collision rate and a good level of channel utilisation. First, the transmit rate is adapted to meet the channel requirements in terms of collision rate and channel load; then, once the minimum beacon transmit rate, set by ETSI, has been reached, transmit power is adapted in a way that guarantees a good level of awareness for closer neighbours. The simulation results show a significant enhancement in terms of the quality as well as the level of awareness

An Adaptive and VANETs-based Next Road Re-routing System for Unexpected Urban Traffic Congestion Avoidance

Unexpected road traffic congestion caused by en-route events, such as car crashes, road works, unplanned parades etc., is a real challenge in today's urban road networks as it considerably increases the drivers' travel time and decreases travel time reliability. To face this challenge, this paper extends our previous work named Next Road Rerouting (NRR) by designing a novel vehicle rerouting strategy that can adapt itself to the sudden change of urban road traffic conditions. This is achieved through a smart calibration of the algorithmic and operational parameters of NRR without any intervention from traffic managers. Specifically, a coefficient of variation based method is used to assign weight values to three factors in the routing cost function of NRR, and the k-means algorithm is applied periodically to choose the number of NRR enabled agents needed. This adaptive-NRR (a-NRR) strategy is supported by vehicular ad-hoc networks (VANETs) technology as this latter can provide rich traffic information at much higher update frequency and much larger coverage than induction loops used in the previously proposed static NRR. Simulation results show that in the city center area of TAPASCologne scenario, compared to the existing vehicle navigation system (VNS) and static NRR, our adaptive-NRR can achieve considerable gain in terms of trip time reduction and travel time reliability improvement

A framework for efficient communication in hybrid sensor and vehicular networks

Fast transmission of event-driven warning messages and energy conservation are primary concerns to design robust Hybrid Sensors and Vehicular Networks (HSVNs). In last few years, several protocols have been proposed to address these issues. However, the tradeoff between energy consumption and latency has not been carefully studied and sometimes it is given higher priority than event detection efficiency which remains the first objective of HSVNs. Unlike the existing works, we propose a framework that provides equilibrium between the following three metrics of HSVNs; dangerous events detection, energy consumption and transmission delay. The main advantage of our framework is its ability to ensure an effective detection of dangers on the road and timely transmission of the corresponding warning messages towards the passing by vehicles. This is achieved through the proposed mechanism to switch the sensors' status between sleep and active modes as well as the devised communication scheme between WSN-Gateway and the vehicles cluster head. The preliminary simulation results confirm the effectiveness of our framework and encourage us to pursue further investigation to extend it. © 2012 IEEE

A short-term vehicular density prediction scheme for enhanced beaconing control.

Channel congestion is a well-known problem in wireless networks in general and Vehicular Ad Hoc Networks (VANETs) in particular. Literature solutions propose to alleviate this problem by controlling the network load based on parameters like vehicle density or packet collision rate. In other words, each vehicle will observe the density of vehicles (or the packet collision rate) around itself in a certain time interval, and use this information to adjust its transmit parameters i.e. transmit rate and/or power, the next time it has a beacon to transmit (in the following time window). However, the information collected in the current time window might not still be valid in the next one. In fact, in a highly dynamic network like VANETs, vehicle density, and consequently the busy ratio and the collision rate, might vary a great deal even in the smallest time intervals. To cope with this newly identified problem, we propose a novel vehicle-centric short-term density prediction scheme that estimates the vehicular density around a given vehicle within the next time window allowing each vehicle to adapt its transmit parameters based on the current state of the network (as opposed to the previous state). The accuracy and the efficiency of our proposed scheme is demonstrated in a proof-of-concept case study, showing a significant improvement in terms of network performance

A robust congestion control scheme for fast and reliable dissemination of safety messages in VANETs

In this paper, we address the beacon congestion issue in Vehicular Ad Hoc Networks (VANETs) due to its devastating impact on the performance of ITS applications. The periodic beacon broadcast may consume a large part of the available bandwidth leading to an increasing number of collisions among MAC frames, especially in case of high vehicular density. This will severely affect the performance of the Intelligent Transportation Systems (ITS) safety based applications that require timely and reliable dissemination of the event-driven warning messages. To deal with this problem, we propose an original solution that consists of three phases as follows; priority assignment to the messages to be transmitted /forwarded according to two different metrics, congestion detection phase, and finally transmit power and beacon transmission rate adjustment to facilitate emergency messages spread within VANETs. Our solution outperforms the existing works since it doesn't alter the performance of the running ITS applications unless a VANET congestion state is detected. Moreover, it ensures that the most critical and nearest dangers are advertised prior to the farther and less damaging events. The simulation results show promising results and validate our solution. © 2012 IEEE