Vehicular ad-hoc networks (VANETs) are characterized by high mobility, dynamic topology changes, and unstable connections, and additionally, they require stringent communication requirements. To make VANET communication more efficient, this poster proposes a Lagrange-based optimized forwarding strategy (LOFS) for information-centric VANETs. The LOFS accounts for several parameters, including link expiration time (LET), link congestion, quality of service (QoS), and traffic conditions to select the next vehicle for Interest and Data packet forwarding. In addition, LOFS mitigates the broadcast storm problem of the existing multicast forwarding strategy, designed for information-centric VANETs.

Real-time healthcare applications demand stringent communication resources to meet the QoS requirements. To meet the application resource demands, this poster proposes a Load and Bandwidth aware Forwarding strategy (LBF-ICN) in Information-Centric Networks (ICN). The LBF-ICN considers router interfaces' pending entries and available bandwidth resources in order to select the next hop for interest forwarding. The LBF-ICN strategy aims to distribute the network load along with bandwidth allocation in interest forwarding.

To efficiently allocate communication and computation resources among enhanced Mobile Broadband (eMBB) and ultra–Reliable Low Latency Communication (uRLLC) applications, this article proposes a joint communication and computation resource allocation scheme in 6th Generation (6G) Information-Centric Networks named: CCR-ICN. To achieve efficient communication and computation resources sharing, the CCR-ICN scheme designs a microservice-centric Interest naming structure to enable named-based communication. Furthermore, the CCR-ICN scheme designs a robust forwarding strategy specifically tailored to efficiently allocate communication resources such as bandwidth among eMBB and uRLLC application requests. In addition, for the allocation of computation resources, the proposed scheme designs a priority-driven computation resources allocation mechanism ensuring effective allocation of Multi-Access Edge Computing (MEC) computation resources. To evaluate the proposed scheme, we performed extensive simulations in a widely used ns-3-based ndnSIM simulator and the results reveal the CCR-ICN achieves 66.82% higher communication resource allocation, and a 17.51% lower communication overhead compared to the TS-6G scheme. Moreover, the CCR-ICN performs computation request satisfaction at 42.03% and 12.72% higher than the TS-6G and EWFQ/LC schemes respectively. Furthermore, the CCR-ICN achieves computation resource utilization of 35.54% and 21.63% lower than the EWFQ/LC and TS-6G schemes respectively.