A kernel's address space design can significantly bottleneck multi-threaded applications, as address space operations such as mmap() and munmap() are serialized by coarsegrained locks like Linux's mmap_lock. Such locks have long been known as one of the most intractable contention points in memory management. While prior works have attempted to address this issue, they either fail to sufficiently parallelize operations or are impractical for real-world kernels.

The growing congruence of gadgets today resulted in a numerous type of cyber attacks. A similar trend occurs with the industrial Internet of Things (IIoT), wherein increasing data created by connected equipment offers up new opportunities for enhancing service quality for new applications. But, security has become a major design priority for smart devices since the introduction of the IIoT. However, data providers have significant challenges in exchanging their data between different cyber physical systems due to privacy and security concerns (e.g., data imbalance and leakage). In this article, we developed a safe data sharing architecture for various IIoT devices using federated learning (FL). The proposed architecture incorporates FL into the edge computing consensus process, allowing the consensus computing activity to be used for federated training as well. The proposed framework achieves high efficiency, and better security, according to numerical findings generated by experimenting deep learning models. More precisely, the proposed framework named as SecureIIoT, is able to achieve 99.79% accuracy by detecting attacks as a binary classification problem.

Full Duplex(FD) network is considered as efficient scheme which could service both downlink(DL) and uplink(UL) users by same resource while HD can serve only DL or UL user for each resource. By optimized user scheduling with power control, optimal spectral efficiency could be achieved but optimization problem is non-linear and complex thus it is hard to implement. Low complexity relaxed optimization problem is proposed to solve resource allocation to minimize the transmission completion time in FD network. By adopting proposed scheme, suboptimal solution can be found in linear problem with significantly lower complexity.