Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

2D Sine Logistic modulation map for image encryption

Linear-space best-first search

Because of the enormous potential to guarantee road safety and improve driving experience, social Internet of Vehicle (SIoV) is becoming a hot research topic in both academic and industrial circles. As the ever-increasing variety, quantity, and intelligence of on-board equipment, along with the ever-growing demand for service quality of automobiles, the way to provide users with a range of security-related and user-oriented vehicular applications has become significant. This paper concentrates on the design of a service access system in SIoVs, which focuses on a reliability assurance strategy and quality optimization method. First, in lieu of the instability of vehicular devices, a dynamic access service evaluation scheme is investigated, which explores the potential relevance of vehicles by constructing their social relationships. Next, this work studies a trajectory-based interaction time prediction algorithm to cope with an unstable network topology and high rate of disconnection in SIoVs. At last, a cooperative quality-aware system model is proposed for service access in SIoVs. Simulation results demonstrate the effectiveness of the proposed scheme.

A Cooperative Quality-Aware Service Access System for Social Internet of Vehicles

Cybersecurity challenges in vehicular communications

Keyed hash function based on a chaotic map

Animal-Vehicle Collisions (AVCs) have been a challenging problem since the creation of cars. Consequently, such collisions cause hundreds of human and animal deaths, thousands of injuries, and billions of dollars in property damage every year. To cope with this challenge, vehicles have to be equipped with smart systems able to detect animals (e.g., moose), which cross roadways, and warn drivers about the imminent danger. In this paper, we develop a new animal detection system following two criteria: detection accuracy and detection speed. To achieve these requirements, a two-stage strategy system is investigated. In the first stage, we use the LBP-Adaboost algorithm which supplies the second stage by a set of ROIs containing moose and other similar-objects. Whereas the second stage is based on an adapted version of HOG-SVM classifier. In this stage, the non-moose ROIs are rejected. To train and test our system, we create our own dataset, which is frequently updated by adding new images. Through an extensive set of simulations, we show that our system is able to detect more than 83% of moose.

An efficient animal detection system for smart cars using cascaded classifiers

Vehicular ad hoc networks have emerged as a promising research area. Designing a realistic coverage protocol for RSU deployment in vehicular networks presents a challenge due to different service area, assorted mobility patterns, and resource constraints. In order to resolve these problems, this paper proposes a geometry-based sparse coverage protocol GeoCover , which aims to consider the geometrical attributes of road networks, movement patterns of vehicles and resource limitations. By taking the dimensions of road segments into account, GeoCover provides a buffering operation to suit different types of road topology. By discovering hotspots from trace files, GeoCover is able to depict the mobility patterns and to discover the most valuable road area to be covered. To solve the resource-constrained coverage problem, we provide two variants of sparse coverage which take into consideration budget constraints and quality constraints, respectively. The coverage problem is resolved by both genetic algorithm and greedy algorithm. The simulation results verify that our coverage protocol is reliable and scalable for urban vehicular networks.

GeoCover: An efficient sparse coverage protocol for RSU deployment over urban VANETs

Vehicular ad hoc networks have emerged as a promising field in wireless networking research. Unlike traditional wireless sensor networks, vehicular networks demand more consideration due to their assorted road topology, the high mobility of vehicles and the irregularly placed feasible region of deployment. As one of the most complex issues in vehicular networks, coverage strategy has been researched extensively, especially in complex urban scenarios. However, most existing coverage approaches are based on an ideal traffic map consisting of straight lines and nodes. These simplifications misrepresent the road networks. In order to provide more realistic vehicular networks deployment, this paper proposes a geometry-based coverage strategy to handle the deployment problem over urban scenarios. By taking the shape and area of road segments into account, our scheme suits different kinds of road topology and effectively solves the maximum coverage problem. To evaluate the effectiveness of our scheme, we compare this coverage strategy with α-coverage algorithm. The simulation result verifies that geometry-based coverage strategy culminates in a higher coverage ratio and a lower drop rate than α-coverage under the same constraints. The results also show that the deployment of Road Side Units (RSUs) in regions with high traffic flow is able to cover the majority of communication, so that less RSUs are able to provide better communication performance.

A geometry-based coverage strategy over urban VANETs

IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. However, the long handoff latency of the standard handoff scheme for IEEE 802.11 has become an important issue for seamless roaming in vehicular environments, because more handoffs may be triggered due to the higher mobility of vehicles. This paper presents a new and fast location-based handoff scheme particularly designed for vehicular environments. With the position and movement direction of a vehicle and the location information of the surrounding access points (APs), our protocol is able to accurately predict several APs that the vehicle may possibly visit in the future and to assign these APs different priority levels. APs on higher priority levels will be scanned first. A blacklist scheme is also used to exclude those APs that showed no response to the scanning during previous handoffs. Thus, time spent on scanning APs is supposed to be significantly reduced. The simulation results show that the proposed scheme attains not only a lower prediction error rate but also lower link layer handoff latency and that it has a smaller influence on jitter and throughput. Moreover, these results show that the proposed scheme has a smaller total number of handoffs than other handoff schemes.

Mohammed Almulla

Papers

Keyed hash function based on a chaotic map

An efficient animal detection system for smart cars using cascaded classifiers

GeoCover: An efficient sparse coverage protocol for RSU deployment over urban VANETs

A geometry-based coverage strategy over urban VANETs

Design of a Fast Location-Based Handoff Scheme for IEEE 802.11 Vehicular Networks