The aim of this paper was to study issues of network connectivity in vehicular ad hoc networks (VANETs) to avoid traffic congestion at a toll plaza. An analytical model was developed for highway scenarios where the traffic congestion could have the vehicles reduce their speed instead of blocking the flow of traffic. In this model, nearby vehicles must be informed when traffic congestion occurs before reaching the toll plaza so they can reduce their speed in order to avoid traffic congestion. Once they have crossed the toll plaza they can travel on at their normal speed. The road was divided into two or three sub-segments to help analyze the performance of connectivity. The proposed analytical model considered various parameters that might disturb the connectivity probability, including traveling speed, communication range of vehicles, vehicle arrival rate, and road length. The simulation results matched those of the analytical model, which showed the analytical model developed in this paper is effective.
In today’s world, millions of transactions are connected to online businesses, and the main challenging task is ensuring the privacy of sensitive information. Sensitive association rules hiding (SARH) is an important goal of privacy protection algorithms. Various approaches and algorithms have been developed for sensitive association rules hiding, differentiated according to their hiding performance through utility preservation, prevention of ghost rules, and computational complexity. A meta-heuristic algorithm is a good candidate to solve the problem of SARH due to its selective and parallel search behavior, avoiding local minima capability. This paper proposes simple genetic encoding for SARH. The proposed algorithm formulates an objective function that estimates the effect on nonsensitive rules and offers recursive computation to reduce them. Three benchmark datasets were used for evaluation. The results show an improvement of 81% in execution time, 23% in utility, and 5% in accuracy.
Vehicular ad hoc networks (VANETs) provide alternative technology solutions to various transportation problems, and they provide a communication solution in intelligent transportation systems. However, the reliability and connectivity of VANET networks are subjects of concern. In building any routing protocol, a minimum level of network reliability must be ensured, which requires conducting a reliability analysis in order to investigate the different factors that affect reliability. Conducting a real-world reliability analysis is very expensive, and it requires significant preparation. Simulations are computationally costly due to the high number of available paths between the source node and the destination. In this article, a simplified approach is conducted that is mainly based on a simulation model of a road-type environment for a VANET network. A heuristic approach is developed for calculating the reliability based on the highest probability paths using the Dijkstra algorithm and the inclusion-exclusion approach for calculating the reliability of a given path. For vehicle-to-vehicle (V2V) communication, short-range protocols were considered-ZigBee (802.15.4), WiFi (IEEE 802.11), and Bluetooth (802.15.1)-as well as their standards for data rates, association time, and transmission range. On the other hand, the IEEE 802.11b was used for vehicle-toroadside (V2R) communications. Another parameter that was considered was the speed limit of the road environment, and three types of road environments were evaluated: highway, urban, and mixed. Other factors that were considered were the number of vehicles, the number of roadside units, and the type of message that was transmitted. The effects of all of these elements on the connectivity of the network were studied.
Typically, the production data centers function with various risk factors, such as for instance the network dynamicity, topological asymmetry, and switch failures. Hence, the load-balancing schemes should consider the sensing accurate path circumstances as well as the reduction of failures. However, under dynamic traffic, current load-balancing schemes use the fixed parameter setting, resulting in suboptimal performances. Therefore, we propose a multi-level dynamic traffic load-balancing (MDTLB) protocol, which uses an adaptive approach of parameter setting. The simulation results show that the MDTLB outperforms the state-of-the-art schemes in terms of both the flow completion time and throughput in typical data center applications.
Vehicular ad-hoc network (VANET) is the name of technology, which uses 'mobile internet' to facilitate communication between vehicles. The aim is to ensure road safety and achieve secure communication. Therefore, the reliability of this type of networks is a serious concern. The reliability of VANET is dependent upon proper communication between vehicles within a given amount of time. Therefore a new formula is introduced, the terms of the new formula correspond 1 by 1 to a class special ST route (SRORT). The new formula terms are much lesser than the Inclusion-Exclusion principle. An algorithm for the Source-to-Terminal reliability was presented, the algorithm produced Source-to-Terminal reliability or computed a Source-to-Terminal reliability expression by calculating a class of special networks of the given network. Since the architecture of this class of networks which need to be computed was comparatively trivial, the performance of the new algorithm was superior to the Inclusion-Exclusion principle. Also, we introduce a mobility metric called universal speed factor (USF) which is the extension of the existing speed factor, that suppose same speed of all vehicles at every time. The USF describes an exact relation between the relative speed of consecutive vehicles and the headway distance. The connectivity of vehicles in different mobile situations is analyzed using USF i.e., slow mobility connectivity, static connectivity, and high mobility connectivity. It is observed that probability of connectivity is directly proportional to the mean speed µ till specified threshold µ , and decreases after µ. Finally, the congested network is connected strongly as compared to the sparse network as shown in the simulation results.
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