The existing research has primarily focused on energy capacity constraints for a single mobile charger, neglecting emergency scenarios where multiple mobile chargers can be deployed simultaneously. Moreover, heterogeneous sensing capabilities among sensors affect the overall monitoring utility. To address these challenges, the scheduling problem of multiple mobile chargers in wireless rechargeable sensor networks with heterogeneous sensing was considered, under both energy capacity and time constraints. First, the problem was formulated to maximize the monitoring utility of heterogeneous sensors by scheduling multiple mobile chargers under given energy and time constraints. Second, the charging region and time slot were discretized, which helps transform the original problem into a submodular function maximization problem. A two-layer greedy algorithm was proposed to approximately solve the submodular problem with a theoretical approximation ratio guarantee. Finally, extensive simulations were conducted to compare the proposed approach with three baseline algorithms, demonstrating that the monitoring utility is improved by at least 10.76% and up to 1 089.34%.
To address the challenge information leakage of physically unclonable function (PUF) and the low security of conventional clustering-based quantization methods in Industrial Internet of Things device identity authentication, a PUF identity authentication method based on physical layer feature boundary quantization was proposed. A convolutional neural network autoencoder (CAE) was employed to extract low-dimensional representations of physical layer features, and multi-sphere support vector data description (MSVDD) was combined to construct the boundary of the legitimate feature space. The low-dimensional features were then mapped into challenge information through boundary quantization, thereby avoiding the direct transmission of challenge information and reducing the probability of attackers correctly guessing the generated challenge information. To compensate for quantization errors caused by imperfect channel reciprocity, a low-density parity-check code was introduced to reconcile the challenge sequences. The results showed that the mismatch rate between legitimate device sequences was 3.78% and decreased to 0.00% after error correction. The mismatch rates between the attacker’s sequence and the device-side and server-side sequences were 49.54% and 49.77%, respectively, close to the random-guessing level. The proposed authentication scheme exhibited a high level of security.
With the development of consortium blockchain technology, decentralized identity (DID) has been widely used in device authentication in Internet of things (IoT) scenarios. Despite the demand of cross-domain authentication, existing methods, on one hand, rely on centralized authorities, and, on the other hand, struggle to address the issue of untrusted issuers wantonly issuing credentials. The core challenge stems from the intrinsic contradiction between decentralized system design and the implementation of centralized regulation. To address the above problems, an efficient hierarchical blockchain heterogeneous interconnection framework was designed. Based on this framework, a trusted authentication method was proposed. This method not only realized decentralized cross-domain authentication but also mitigated the problem of credential over-issuance by untrusted issuers. Finally, experiments based on the Sepolia ethereum testnet were conducted. The simulation results demonstrate that the proposed method achieves secure cross-domain authentication without incurring significant overhead.
A localization system for passive Bluetooth low energy (BLE) backscatter tags was designed for low-power item-finding applications, where carrier-generation and transmission circuits increase the power consumption and hardware complexity of active tags. External excitation and downlink synchronization were provided by a Wi-Fi signal. BLE-compatible periodic advertising packets with a constant tone extension (CTE) were generated using a dual-circulator structure, a low-noise amplifier, and a field-programmable gate array. CTE in-phase and quadrature samples, received signal strength indicator measurements, and visual-inertial navigation system pose estimates were acquired at the receiver. Packet-level phase compensation, differential synthetic aperture radar (SAR) angle-of-arrival (AoA) estimation, and differential-prior-assisted near-field search were combined to estimate tag position, AoA, and range. Indoor and outdoor line-of-sight and non-line-of-sight tests showed that valid BLE observations could be continuously acquired. Across four scenarios, 95th-percentile ranging errors of 0.59-1.02 m and AoA errors of 13°-25° were achieved. The results indicate that the proposed method can support localization under multipath and blockage conditions.
The state-of-the-art technologies of the integrated circuit industry were adopted as the research basis, and the development status, common characteristics, technical bottlenecks, optimization approaches and application prospects of industrial chips were systematically analyzed. The domestic and global industrial development patterns were clarified in this research. The general law governing the cross-industry application of industrial chips was revealed, highly consistent requirements for chip architecture and reliability technologies were observed across various industrial sectors. On this basis, core technical shortcomings and systematic defects restricting industrial development were summarized from multiple dimensions including fundamental reliability theories, EDA tool support, chip design, tape-out processes, packaging technologies and inspection standard systems, and targeted breakthrough routes and optimization strategies were put forward. Meanwhile, combined with three typical application scenarios of electric power and energy, rail transit and automotive electronics, the implementation modes and application values of industrial chips were illustrated, and their supporting role as underlying core hardware was verified. Finally, the future evolution trends of industrial chips were predicted. It was indicated that industrial chips could be developed into the core fulcrum for the construction of new-type power systems by virtue of the advantages of hardware infrastructure, support the establishment of an integrated communication system integrating local, remote and satellite communications, and realize full-link intelligent upgrading with the assistance of artificial intelligence technologies. Theoretical references and technical references were provided by this study for the technological iteration, scenario deployment and industrial independent development of industrial chips applied in fields such as new-type power systems, rail transit and automotive electronics.
