Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Chemical composition of aerosol particles and light extinction apportionment before and during the heating season in Beijing, China

Abstract: Despite extensive efforts into characterization of the sources and formation mechanisms of severe haze pollution in the megacity of Beijing, the response of aerosol composition and optical properties to coal combustion emissions in the heating season remain poorly understood. Here we conducted a 3 month real-time measurement of submicron aerosol (PM1) composition by an Aerosol Chemical Speciation Monitor and particle light extinction by a Cavity Attenuated Phase Shift extinction monitor in Beijing, China, from 1 October to 31 December 2012. The average (±σ) PM1 concentration was 82.4 (±73.1) µg/m3 during the heating period (HP, 15 November to 31 December), which was nearly 50% higher than that before HP (1 October to 14 November). While nitrate and secondary organic aerosol (SOA) showed relatively small changes, organics, sulfate, and chloride were observed to have significant increases during HP, indicating the dominant impacts of coal combustion sources on these three species. The relative humidity-dependent composition further illustrated an important role of aqueous-phase processing for the sulfate enhancement during HP. We also observed great increases of hydrocarbon-like OA (HOA) and coal combustion OA (CCOA) during HP, which was attributed to higher emissions at lower temperatures and coal combustion emissions, respectively. The relationship between light extinction and chemical composition was investigated using a multiple linear regression model. Our results showed that the largest contributors to particle extinction were ammonium nitrate (32%) and ammonium sulfate (28%) before and during HP, respectively. In addition, the contributions of SOA and primary OA to particle light extinction were quantified. The results showed that the OA extinction was mainly caused by SOA before HP and by SOA and CCOA during HP, yet with small contributions from HOA and cooking aerosol for the entire study period. Our results elucidate substantial changes of aerosol composition, formation mechanisms, and optical properties due to coal combustion emissions and meteorological changes in the heating season.

Privacy-Preserving and Lightweight Key Agreement Protocol for V2G in the Social Internet of Things

Abstract: The concept of the Social Internet of Things (SIoT) can be viewed as the integration of prevailing social networking and the Internet of Things, which is making inroads into the daily operation of many industries. Smart grids, which are cost-effective and environmentally friendly applications, are a promising field of the SIoT. However, security and privacy concerns are the dark aspects of smart grids. The goal of this paper is to address the security and privacy issues in the vehicle-to-grid (V2G) networks with the intention of promoting a more extensive deployment of V2G networks for smart grids. Driven by this motivation, in this paper, we propose a robust key agreement protocol that can achieve mutual authentication without exposing the real identities of users. Efficiency is also a major concern in resource-constrained environments. By leveraging only hash functions and bitwise exclusive-OR operations, the proposed protocol is highly efficient compared with pairing-based protocols. In addition, we define a formal security model for our privacy-preserving key agreement protocol for V2G networks. Using this model, a formal security analysis shows that the proposed protocol is secure. Moreover, an informal security analysis demonstrates that our protocol can withstand different types of attacks.

Trust-Oriented IoT Service Placement for Smart Cities in Edge Computing

Abstract: Smart city is gradually forming a large scope of Internet of Things (IoT) networks with diffusely deployed IoT devices that produce quantities of services. Considering the large-scale and widely distributed features of IoT networks, edge computing is emerged as a powerful and suitable paradigm to provide computing abilities for the IoT devices at the edge of the networks. In edge computing, the IoT services could be placed on the edge computing units (ECUs) for execution, which provides low latency and eases the burden of bandwidth. However, it is still challenging to improve the overall ECU execution performance (i.e., the resource usage, the load balance levels, and the power consumption of ECUs) and meanwhile prevent privacy leakage of the IoT devices for service placement. To tackle this challenge, a trust-oriented IoT service placement method, abbreviated as TSP, is proposed for smart cities in edge computing. Technically, improving the strength Pareto evolutionary algorithm (SPEA2) is leveraged to acquire the balanced placement strategies for the tradeoffs among the execution performance metrics with privacy preservation. Additionally, the technique for order preference by similarity to ideal solution (TOPSIS) and multicriteria decision-making (MCDM) techniques are employed to identify the optimal placement strategy among the obtained service placement strategies. Eventually, systematic experiments are conducted to verify the efficiency and reliability of TSP.