Energy-efficient device discovery is vital in public-safety systems. We investigate the problem of maximizing the number of discovered users under the major constraint of overlay interference, which occurs in device-to-device (D2D) communications, from users simultaneously accessing the resources. To solve this problem, we propose a D2D discovery maximization (D2D-DM) iterative algorithm, which provides the capability to switch the discovery mode from half-duplex to in-band full-duplex, when signal-to-interference-noise ratio falls below a predefined threshold. Moreover, the open-loop power control scheme is adopted for power-limited users. Simulation results demonstrate that the proposed D2D-DM scheme significantly enhances the number of discovered users as compared to conventional static resource allocation and the random backoff schemes.

The Intelligent Transportation System (ITS) has the potential to significantly improve communication reliability, efficiency, and manageability in transportation systems. Vehicular ad hoc networks (VANETs) are particularly valuable for sustaining ITS features in dynamic, high-density environments. Integrating the Internet of Things (IoT) into modern transportation systems can further enhance ITS capabilities by providing real-time data and connectivity. Challenges like insufficient spectrum utilization and increased end-to-end latency in single-radio data transmission systems have led to the development of advanced techniques such as dual-radio multi-channel systems. However, these approaches often compromise network performance due to interference. To address these limitations, this paper proposes drone-assisted cooperative routing (DACR), incorporating IoT elements for improved connectivity and data exchange. Performance evaluation, based on comparative analysis with the existing state-of-the-art schemes, indicates that the proposed DACR outperforms in packet delivery ratio, end-to-end delay, and control message overhead.

The configuration is essential to diagnose the status of the grounding grid, but the orientation of the unknown grounding grid is ultimately required to diagnose its configuration explicitly. This paper presents a transient electromagnetic method (TEM) to determine grounding grid orientation without excavation. Unlike the existing pathological solutions, TEM does not enhance the surrounding electromagnetic environment. A secondary magnetic field as a consequence of induced eddy currents is subjected to inversion calculation. The orientation of the grounding grid is diagnosed from the equivalent resistivity distribution against the circle perimeter. High equivalent resistivity at a point on the circle implies the grounding grid conductor and vice versa. Furthermore, various mesh configurations including the presence of a diagonal branch and unequal mesh spacing are taken into account. Simulations are performed using COMSOL Multiphysics and MATLAB to verify the usefulness of the proposed method.

Multicore architectures offer an amount of parallelism that is often underutilized, as a result these underutilized resources become a liability instead of advantage. Inefficient resource sharing on the chip can have a negative impact on the performance of an application and may result in greater energy consumption. A large body of research now focuses on reconfigurable multicore architectures in order to support algorithms to find optimal solutions for improved energy and throughput balance. An ideal system would be able to optimize such reconfigurable systems to a level that optimum resources are allocated to a particular workload and all the other underutilized resources remain inactive for greater energy savings. This paper presents a fuzzy logic based reconfiguration engine targeted to optimize a multicore architecture according to the workload requirements for optimum balance between power and performance of the system. The proposed fuzzy logic reconfiguration engine is designed around a 16-core SCMP architecture comprising of reconfigurable cache memories, power gated cores and adaptive on-chip network routers for minimizing leakage energy effects for inactive components. A coarse grained architecture was selected for being able to reconfigure faster, thus making it feasible to be used for runtime adaptation schemes. The presented architecture is analyzed over a set of OpenMP based parallel benchmarks and results show significant energy savings in all cases.