A vehicular ad hoc network (VANET) is composed mainly of fixed roadside entities (RSUs) and mobile entities (vehicles). In order to exchange information and data relating to the safety and comfort of road users, these different entities must establish communications between them. In these communications, one of the main problems is related to congestion and saturation of RSUs. In this paper, we first study the main protocols that involve RSUs in their strategy of routing by classifying them according to four levels. Furthermore, to deal with the problem of saturation of RSUs, we present a new approach of cooperation between the RSUs of a VANET in order to reduce its congestion and avoid as much as possible the saturation of these entities. This approach, called "D2A2RS" (defensive alliance-based approach for reducing RSUs saturation), is based on the concept of defensive alliances in graphs that ensures effective collaboration between RSUs. To evaluate the performance of the proposed approach, we conduct a comparative analysis by using both analytical models and simulations. The obtained comparison results have shown the efficiency and the performance of our approach compared with other concurrent approaches in the literature in terms of packet loss/success rate, end-to-end transmission delay, and network scalability. KEYWORDSanalytical model, congestion, cooperation, defensive alliance of data processing, roadside unit (RSU), saturation, simulation, vehicular ad hoc network (VANET) Int J Commun Syst. 2020;33:e4245.wileyonlinelibrary.com/journal/dac
The traditional transportation system is based on a fixed-timed strategy to control the traffic congestion on urban roads. However, the increase of vehicle density in a smart city implies the variation and the conflict on the demand pattern of the drivers. The smart city development requires to create an efficient control plan for an intelligent traffic management system. In this paper, we aim to reduce the congestion at signalized intersections, and satisfy the needs of drivers according to their degree of displacement urgency. We use two optimization methods, namely the synchronization and the Genetic Algorithm (GA), where we develop three scheduling protocols. The first is the intelligent context-aware negotiation protocol (ICANP). This protocol allows the negotiating vehicles to cross the intersection. It enables each traffic light at the signalized intersection to negotiate the green time assigned to its phase. ICANP uses GA to optimize the crossing time in order to minimize the total waiting time of negotiating vehicles. Moreover, we introduce a negotiation protocol based on reputation (NPBR), which minimises the congestion effect from incoming dishonest drivers. Finally, we propose an intelligent context-aware priority protocol (ICAPP), that considers the existence of priority vehicles. Upon arrival of at least one priority vehicle at the signalized intersection, ICAPP interrupts the green time of negotiating vehicles. A series of simulation showed that the proposed protocols reduce the total waiting time and the emissions of CO 2 of vehicles at signalized intersection, in comparison with circular, ITLC and CATLS scheduling algorithms. Furthermore, formal complexity analysis and performance evaluation show the effectivity of our protocols.
Smart hospital is a healthcare infrastructure that uses IoT technology. This intelligent space allows to collaborate a several health actors via their IoT devices. This coordination improves the quality and continuity of health services for better patient care. However, uncontrolled access to patient information can disrupt the smooth running of hospital services. In this paper, we aim to secure the information of patient exchanged and shared, using the privacy and access control based on the context. We develop two protocols, the first is a context-aware pseudonym service. It protects the patient's personal and health information in two smart space hospital and home. Furthermore, we prevent the disclosure of the patient's location during his hospital stay. The second is an authorization and delegation protocol based on trust, context and role. It oversees the actions and interactions of health body with the smart bracelet object of patient. Our protocol uses the context to generate a set of roles with their trust values. Only one role is activated if its trust value is greater than or equal to a trust threshold. A dynamic delegation mechanism is created to better manage the interactions between health bodies. We demonstrate through the practical analysis as well as generation time overhead, storage overhead and response time requirement the efficiency and robustness of our proposed protocols.
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