Radio frequency (RF) power-harvesting technology is widely used by the temperature sensors inside high-voltage power-distribution cabinets, which avoids the safety risks caused by the use of batteries. Although the RF electromagnetic wave generated by high-voltage electric fields inside the cabinet can serve as the power supply, it suffers from unstable energy density. As a result, an external device is usually required to power up and read the temperature sensor, such as the near-field communication (NFC) reader of a smartphone. In this case, the RF harvester of the temperature sensor should be sensitive enough to enable a safe operating distance between the external reader and cabinet. Traditional methods combined an AC-DC rectifier and a DC-DC converter to provide a sufficient-high supply voltage for the sensing circuits, but the sensitivity was limited to −21dBm. In this work, an oscillator-enhanced energy-fusion power-harvesting technique is proposed to extend the power-transfer range of NFC. The harvester picks up the NFC energy to start up an oscillator, which enhances the power-harvesting sensitivity of other RF electromagnetic waves such as the 433MHz component in the cabinet. Then, the harvested DC voltage can be increased due to the power superposition of both the 13.56MHz and 433MHz tones. The proposed technique is implemented in a power-harvesting chipset fabricated in 55nm CMOS and 65nm CMOS processes. Measurement results show that the sensitivity of 433MHz power harvester is improved by 4.1dB due to the enhancement of the NFC excited oscillator, which also extends the NFC power-transfer range to 9cm.

Battery-free tags offer a power-efficient solution for the wireless connection in Internet of Things (IoT), where the backscatter communication that is compatible with widely-deployed protocols such as Bluetooth Low Energy (BLE) significantly reduces the hardware cost thanks to the seamless integration into the existing infrastructure. However, there are three main shortcomings in the existing battery-free BLE tags: 1)The tag-to-access point (AP, uplink) communication ranges are limited to 97 meters at -10dBm incident power, which are not long enough for some outdoor scenes. 2) The AP-to-tag (downlink) communication in the state of the arts has not exceeded a 1Mbps data rate and a 4m range, disabling remote tag configuration. 3)The tag-to-tag communication has not been realized in a battery-free way, which cannot construct a passive IoT network. In this work, we demonstrate an integrated bidirectional passive BLE chip that conducts battery-free BLE communication in tag-to-tablet/smartphone, tablet/smartphone-to-tag, and tag-to-tag modes. The chip is implemented in a 65nm CMOS process. An all-digital intermediate frequency (IF) shaping technique is proposed to extend the tag-to-tablet/smartphone (uplink) communication range to 160m at$7.16\mu $W power consumption and a -10dBm incident tone. In addition, a$2^{nd}$-order intermodulation (IM2) based charge-domain GFSK demodulation technique is proposed to enable 1Mbps 12m downlink communication at$6.8\mu $W power consumption, which realizes both tablet/smartphone-to-tag and tag-to-tag communication in a fully battery-free way. As a result, the bidirectional passive BLE chip offers a potential solution for future battery-free IoT mesh network.

Blockchain transaction verification is fundamental to decentralized financial applications, ensuring both transaction authorization and integrity. Most existing verification schemes utilize an equal weight model that grants identical rights to all participants. However, these schemes fail to capture real-world scenarios like Proof-of-Stake blockchains, where participants have right discrepancies. Additionally, many schemes depend on trusted third parties for key generation, introducing single points of failure and compromising security. To address these limitations, we propose WBlock that is a weighted and decentralized verification scheme. WBlock involves a distributed key generation protocol that embeds each entity's weight into its secret share, eliminating the need for trusted third parties. It further employs a Schnorr-type weighted threshold signing protocol, enabling distributed transaction authorization while reflecting participant weight in signature shares. Security analysis shows that WBlock achieves both correctness and unforgeability. Comparative theoretical analysis shows that our key generation and signing protocols outperform existing methods in terms of round complexity, communication overhead and data size. Experimental results confirm that WBlock achieves a balance between security and efficiency, with acceptable overhead for real-world blockchain deployment.

Extracting local variable refactoring is frequently employed to replace one or more occurrences of a complex expression with simple accesses to a newly introduced variable. To facilitate refactoring, most IDEs can automate the extract local variable refactorings when the to-be-extracted expressions are selected by developers. However, refactoring tools usually replace all expressions that are lexically identical to the selected one without a comprehensive analysis of the safety of the refactoring. The automatically conducted refactorings may lead to serious software defects. Besides that, existing refactoring tools rely heavily on software developers to spot to-be-extracted expressions although it is often challenging for inexperienced developers and maintainers to make the selection. To this end, in this article, we propose an automated approach, called ValExtractor+ , to recommending extract local variable refactoring opportunities and to automatically and safely conduct the refactorings. ValExtractor+ is composed of two parts, i.e., solutionAdvisor and opportunityAdvisor . Given a to-be-extracted expression, solutionAdvisor leverages lightweight static source code analysis to validate potential side effects of the expression, and to identify expressions that could be extracted together with the selected expression as a single variable without changing the semantics of the program or introducing any new exceptions. The static code analysis significantly improves the safety of automated extraction of local variables. To free programmers from manually selecting to-be-extracted expressions, opportunityAdvisor leverages solutionAdvisor to automatically retrieve all expressions that could be extracted safely as well as their refactoring solutions. It then leverages a learning-based classifier to predict which of the retrieved expressions should be extracted. Evaluations on open-source applications suggest that solutionAdvisor successfully avoided all defects (more than two hundred) caused by extracting local variable refactorings conducted by Eclipse (243 defects) or IntelliJ IDEA (263 defects). Additionally, opportunityAdvisor was able to effectively recommend expressions for extraction, achieving 307 true positives (TP) and 21,121 true negatives (TN). Four pull requests from our work (PR IDs: 66, 333, 439, and 360) were successfully merged into the Eclipse community repository, showcasing the practical impact and robustness of our approach as recognized by the wider developer community.

Extract local variable is a well-known and widely used refactoring. It is frequently employed to replace one or more occurrences of a complex expression with simple accesses to a newly added variable. Although most IDEs provide tool support for extract local variables, such tools without deep analysis of the refactorings may result in semantic errors. To this end, in this paper, we propose a novel and more reliable approach, called ValExtractor, to conduct extract variable refactorings automatically. The major challenge of automated extract local variable refactorings is how to efficiently and accurately identify the side effect of the extracted expressions and the potential interaction between the extracted expressions and their contexts without time-consuming dynamic execution of the involved programs. To resolve this challenge, ValExtractor leverages a lightweight static source code analysis to validate the side effect of the selected expression, and to identify which occurrences of the selected expression could be extracted together without changing the semantics of the program or introducing potential new exceptions. Our evaluation results on open-source Java applications suggest that Eclipse and IntelliJ IDEA, the state-of-the-practice refactoring engines, resulted in a large number of faulty extract variable refactorings whereas ValExtractor successfully avoided all such errors. The proposed approach has been merged into (and distributed with) Eclipse to improve the safety of extract local variable refactoring.