About Omnet Project Team

Intelligent Transportation Systems (ITS) are fundamental in order to improve safety and road efficiency. In this framework inter-vehicle communications play a primary role. To this aim several vehicle-to-vehicle (V2V) communication standards have been developed. The most important is IEEE 802.11p that operates in ISM band (5.85-5.92) GHz. Unfortunately at these frequencies communication ranges are limited and Doppler effect could not be neglected, especially when the carrier spacing of the adopted modulation techniques is close to 1 kHz, as it happens in modern standard for digital mobile communications.

In order to overcome these issues, a possible solution could be the adoption of a dynamic spectrum access model able to identify frequency holes in UHF band. In this framework, this paper presents a novel approach to spectrum sensing based on the application of a dual step energy detection algorithm. It has been designed and tailored to be effective in identifying DVB-T signals. A test campaign carried out in simulation environment has confirmed the goodness of the proposal.

This paper discusses one of the route security problems called the black hole attack. In the network, we can capture some AODV route tables to gain a rank sequences by using the FP-Growth, which is a data association rule mining. We choose the rank sequences for detecting the malicious node because the rank sequences are not sensitive to the noise interfered. A suspicious set consists of nodes which are selected by whether the rank of a node is changed in the sequence. Then, we use the DE-Cusum to distinguish the black hole route and normal one in the suspicious set.

In this paper, the FP-Growth reflects an idea which is about reducing data dimensions. This algorithm excludes many normal nodes before the DE-Cusum detection because the normal node has a stable rank in a sequence. In the simulation, we use the NS2 to build a black hole attack scenario with 11 nodes. Simulation results show that the proposed algorithm can reduce much vain detection.

Vehicular Ad-hoc Network (VANET) is a wireless communication network with frequent changes in its topology due to unpredictable movements of vehicles. The frequent changes of network topology make the data packet transmission and routing process very difficult. Among various routing algorithms available for VANET, different position based routing algorithms which use the position information of neighbor nodes have been proposed. However, dynamic movement direction and speed of vehicles can easily break the communication between nodes.

Nonetheless, due to various aspects (i.e. neighbor nodes locate at the edge of sender’s transmission range or change their mobility between beacon transmission intervals.) that have not been considered in the existing methods, there still exists a possibility of communication disconnection. In this paper, we propose a reliable and effective intermediate node selection algorithm to improve the routing problem. The key component of the proposed algorithm is selecting the reliable intermediate node from the mobility information included in beacons. Extensive number of simulation results show that the proposed algorithm outperforms the existing methods in terms of end-to-end delay and packet delivery ratio.

In this paper we intend to use vehicular ad hoc network to together and assemble real -time speed and position information on single vehicles to optimize signal control at traffic byroad. first specify systematically the vehicular traffic signal control difficulty as a job scheduling difficulty on processors with job equivalent to platoons of vehicles. Then jobs are planned using an online algorithm called Oldest Job First (OJF) algorithm to reduce the interruption across the roundabout. The OJF algorithm is 2-competitive imply that the intrusion is less than or equivalent to twice the interruption of an optimal offline schedule with just right knowledge of the arrivals.

It show that, how a VANET is used to group vehicles into about equal-sized platoons, which can then be schedule using OJF. The two-phase advance are used, where first advance is to collection the vehicular traffic into platoons and then apply the OJF algorithm, i.e. the oldest arrival first (OAF) algorithm. Our simulation (.Net ) result shows that, However, further analysis is needed in order to obtain the useful information for traffic management such as real time traffic density and number of vehicle types transient these roads. This paper presents tragedy vehicle alert and traffic density calculation methods used.

IEEE 802.11 Distributed Coordination Function (DCF) is based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). However, the CSMA-based access protocol with omnidirectional antennas can cause the serious unfairness or flow starvation. By exploiting the multiple channels and using the directional antennas, nodes located in each other’s vicinity may communicate simultaneously. This helps to increase the spatial reuse of the wireless channel and thus increase the network performance.

In this paper, we propose a Multi-channel MAC protocol with Directional Antennas (MMAC-DA) that adopts IEEE 802.11 Power Saving Mechanism (PSM) and exploits multiple channel resources and directional antennas. Nodes have to exchange control packets during the Announcement Traffic Indication Message (ATIM) window to select data channels and determine the beam directions which are used to exchange data packets during the data window. The simulation results show that MMAC-DA can improve the network performance in terms of aggregate throughput, packet delivery ratio and energy efficiency.

In vehicular ad-hoc network (VANET), the reliability of communication is associated with driving safety. However, research shows that the safety-message transmission in VANET may be congested under some urgent communication cases. More spectrum resource is an effective way to solve transmission congestion. Hence, we introduce cognitive radio enabled VANET (CR-VANET), where CR device can detect possible idle spectrum for VANET communications and assist to timely broadcast safety-message. Given high-speed mobility of vehicles and dynamically-changing availability of channels, a novel prediction algorithm is proposed to pick out the channel with the greatest probability of availability, which can meet the quality of service (QoS) requirement of urgent communications and effectively avoid conflict with licensed users.

Specifically, the spatiotemporal correlations among historical spectrum sensing data are exploited to form prior knowledge of channel availability probability, and Bayesian inference is used to derive posterior probability of channel availability. Comparing with other spectrum detection methods, the proposed algorithm has more than 8% detection performance improvement at false alarm probability 0.2, and thus can avoid access conflict with licensed users dramatically. Furthermore, the proposed algorithm always has larger packet reception probability (PRP) and lower transmission delay compared with conventional VANET broadcasting. Hence, the proposed algorithm can improve reliability of safety-message transmission and enhance driving safety significantly.

This paper evaluates three inter-vehicle spacing models based on exponential, Generalized Extreme Value, and Exponential with robustness factor statistical distributions [1], [2], [3]. Vehicles adjust transmission range as a function of its spatial density on a road segment to increase its network connectivity with other vehicles.

This connectivity can be secured by deploying this scheme [4] which secures communications among vehicles through trusted road-side units that distribute secret keys to vehicles under their coverage.

Normally, authentication in vehicular ad hoc networks (VANETs) uses public key infrastructure to verify the integrity of messages and the identity of message senders. The issues considered in the authentication schemes include the level of security and computational efficiency in the verification processes. Most existing schemes mainly focus on assuring the security and privacy of VANET information. However, these schemes may not work well in VANET scenarios. For instance, it is difficult for a roadside unit (RSU) to verify each vehicle’s signature sequentially when a large number of vehicles emerge in the coverage areas of an RSU. To reduce the computational overhead of RSUs, we propose a proxy-based authentication scheme (PBAS) using distributed computing.

In the PBAS, proxy vehicles are used to authenticate multiple messages with a verification function at the same time. In addition, the RSU is able to independently verify the outputs from the verification function of the proxy vehicles. We also design an expedite key negotiation scheme for transmitting sensitive messages. It is shown from the analysis and simulations that an RSU can verify 26 500 signatures per second simultaneously with the help of the proxy vehicles. The time needed to verify 3000 signatures in the PBAS can be reduced by 88% compared with existing batch-based authentication schemes.

As the number of vehicles increases significantly, traffic congestion has become a major social problem in recent years. Such a situation can be alleviated effectively with the emerging of vehicular ad hocnetwork (VANET)-based real-time path planning systems. However, existing systems face the challenges of poor anti-congestion capability and high complexity. To address the related issues, an road side unit (RSU)-based architecture is proposed in this paper, in which a city is divided into different areas, each with an RSU.

Based on the architecture, a decentralized and hierarchical real-time path planning algorithm is proposed. The path planning problem is formulated from two layers, i.e., area path selection in upper layer and intra-area routing in bottom layer, both of which target to minimize the average travel time. Numerical results show that, our proposed algorithm inherits the anti-congestion capability and owns the advantage of low complexity, as compared with the shortest path algorithm and centralized algorithm.

In hardware-constrained cognitive radio (CR) ad hoc networks, secondary users (SUs) with limited sensing capabilities strive to discover and share available spectrum resources without impairing primary user (PU) transmission. Sensing strategy design objectives include high CR network throughput, resolved SU competition, distributed implementation, and reliable performance under node mobility. However, these objectives have not been realized by previously investigated sensing strategies. A novel sensing strategy is analyzed where the reward is adapted to the SU link channel state information (CSI) prior to sensing, thus randomizing sensing decisions and boosting the network throughput.

Moreover, CSI-aided sensing is combined with a novel first-come-first-served (FCFS) medium access control (MAC) scheme that resolves SU competition prior to sensing. Finally, a pilot-based CSI prediction method is developed to enable the proposed CSI-aided sensing strategies for mobile scenarios. Analytical and numerical results demonstrate that the proposed sensing and access methods significantly outperform non adaptive sensing strategies for practical mobile CR scenarios with CSI mismatch and pilot overhead.