Nowadays, due to the advances in mobile and wireless communication, mobile devices are widely used in our daily life. Meanwhile, in the mobile devices, there exits diverse applications which are ...developed to satisfy the various requirements of mobile users. Correspondingly, a large number of services are produced by the mobile devices. Since the mobile devices have limitations on the battery capacity, physical size, etc., they can hardly complete all the services. To relieve this problem, driven by edge computing, the central units (CUs) in fifth-generation wireless systems (5G) could be enhanced into edge nodes (ENs) for processing. However, during the transmission of edge services, the privacy leakage may occur, and the overall performance of the networks needs to be taken into consideration. In this paper, an optimization problem is defined to improve the resource utilization and load balance for all the ENs while protecting the privacy information and satisfying the time requirement. Then, a balanced service offloading method, abbreviated BSOM, is proposed. Finally, abundant experiments and evaluations are conducted to validate our proposed method is both effective and feasible.
Cyber-Physical Systems(CPS) serves as an interdisciplinary effort that incorporates cyber vector as well as physical vector. The latter can generate exponentially growing amounts of data. How to ...process CPS big data systematically and efficiently is the key to the breakthrough of offering prospective and personalized services for each individual user and entity involved. In recent years, much research has been proactively conducted on advancing specific scenario or algorithm. However, few surveys value their integration. For good measure, the synthesis remains a fundamental challenge. Subsequently, we fill the gap in the literature by constructing cloud computing, fog computing and edge computing as a whole to inspire on new architectures and cross utilizations. Moreover, bringing the enthusiasm of traditionally solitude entities into play is crucial. In this exploratory study, we examine definitions of CPS as well as the three aforementioned computing paradigms and then shed new light on comprehensively established frameworks. We also survey on the application level of Cloud-Fog-Edge Computing in CPS respectively and dive into diversified algorithms and strategies to embed big data applications into a more intelligent and convenient society with current deficiencies and future research directions followed.
Unreasonable irrigation and nitrogen application reduce tomato yield and waste resources. This study explored the effects of water conservation and nitrogen reduction on tomato yield, dry matter, ...quality, water productivity and nitrogen use efficiency in Northeast China. Experiments were conducted during 2020 and 2021 at three irrigation levels (85–95 %, 75–85 %, and 65–75 % θFC) and three nitrogen application levels (120, 180, and 240 kg hm−2). The optimal water and nitrogen supply patterns were obtained by establishing a newly evaluated Entropy Weight Method−Technique for Order Preference by Similarity to Ideal Solution−Adversarial Interpretive Structure Model (EWM−TOPSIS−AISM). The results showed that the amount of irrigation and nitrogen application significantly affected tomato quality (P ≤ 0.5). Proper deficit irrigation improved tomato quality. Reducing the nitrogen application rate improved nitrogen use efficiency but decreased the tomato yield. Increasing the amount of irrigation increased tomato yield and nitrogen use efficiency. Tomato yield was negatively correlated with water productivity (R= −0.25 in 2020 and R= −0.37 in 2021) and nitrogen use efficiency (R= −0.30 in 2020 and R= −0.20 in 2021). The evaluation results showed that the best water and nitrogen supply mode for our experiment was irrigation at 75–85 % θFC and nitrogen application rate of 180 kg hm−2. The study could promote the sustainable production of greenhouse tomatoes in Northeast China.
Over the past years, with the development of hardware and software, the intelligent sensors, which are deployed in the wearable devices, smart phones, and etc., are leveraged to collect the data ...around us. The data collected by the sensors is analyzed, and the corresponding measures will be implemented. However, due to the limited computing resources of the sensors, the overload resource usage may occur. In order to satisfy the requirements for strong computing power, edge computing, which emerges as a novel paradigm, provides computing resources at the edge of networks. In edge computing, the computing tasks could be offloaded from the sensors to the other sensors for processing. Despite the advantages of edge computing, during the offloading process of computing tasks between sensors, private data, including identity information and address, may be leaked, which threatens personal security. Hence, it is important to avoid privacy leakage in edge computing. In addition, the time consumption of offloading computing tasks affects the using experience of customers, and low time consumption makes contributions to the development of applications which are strict with time. To satisfy the above requirements, a time-efficient offloading method (TEO) with privacy preservation for intelligent sensors in edge computing is proposed. Technically, the time consumption and the offloading of privacy data are analyzed in a formalized way. Then, an improved of Strength Pareto Evolutionary Algorithm (SPEA2) is leveraged to optimize the average time consumption and average privacy entropy jointly. At last, abundant experimental evaluations are conducted to verify efficiency and reliability of our method.
With the development of the Internet of Things (IoT) technology, a vast amount of the IoT data is generated by mobile applications from mobile devices. Cloudlets provide a paradigm that allows the ...mobile applications and the generated IoT data to be offloaded from the mobile devices to the cloudlets for processing and storage through the access points (APs) in the Wireless Metropolitan Area Networks (WMANs). Since most of the IoT data is relevant to personal privacy, it is necessary to pay attention to data transmission security. However, it is still a challenge to realize the goal of optimizing the data transmission time, energy consumption and resource utilization with the privacy preservation considered for the cloudlet-enabled WMAN. In this paper, an IoT-oriented offloading method, named IOM, with privacy preservation is proposed to solve this problem. The task-offloading strategy with privacy preservation in WMANs is analyzed and modeled as a constrained multi-objective optimization problem. Then, the Dijkstra algorithm is employed to evaluate the shortest path between APs in WMANs, and the nondominated sorting differential evolution algorithm (NSDE) is adopted to optimize the proposed multi-objective problem. Finally, the experimental results demonstrate that the proposed method is both effective and efficient.
Aiming to meet the growing demand for observation and analysis in power systems that based on Internet of Things (IoT), machine learning technology has been adopted to deal with the data-intensive ...power electronics applications in IoT. By feeding previous power electronic data into the learning model, accurate information is drawn, and the quality of IoT-based power services is improved. Generally, the data-intensive electronic applications with machine learning are split into numerous data/control constrained tasks by workflow technology. The efficient execution of this data-intensive Power Workflow (PW) needs massive computing resources, which are available in the cloud infrastructure. Nevertheless, the execution efficiency of PW decreases due to inappropriate sub-task and data placement. In addition, the power consumption explodes due to massive data acquisition. To address these challenges, a PW placement method named PWP is devised. Specifically, the Non-dominated Sorting Differential Evolution (NSDE) is used to generate placement strategies. The simulation experiments show that PWP achieves the best trade-off among data acquisition time, power consumption, load distribution and privacy preservation, confirming that PWP is effective for the placement problem.
In order to enlarge and improve the application of phase changing materials (PCM) composite wall in Chinese solar greenhouse (CSG), the effect of thermal parameters on heat storage and release ...performance of PCM composite wall were systematically and scientifically investigated by available CFD code of commercial software ANSYS-Fluent, which was almost determined by the parameters such as density, thermal conductive, latent heat fusion and specific heat capacity. The numerical simulation was reasonably validated by the experimental result under the same condition, which was conducted by error analysis of interval analysis (IA) method. The result is shown that IA result between numerical simulation and experiment is 0.96, while the numerical simulation of PCM composite wall is significantly accurate and reliable. The maximum temperature of the center point in interior surface is completely dependent on the contrary tendency changing of thermal parameters at heating time, of which is directly proportional to thermal parameters changing at cooling time, except the specific heat capacity. While only the thermal conductivity increasing is benefit for increasing interior surface temperature of PCM composite wall at final cooling time. The effect of solely thermal parameter on the heat storage and release performance changing of PCM composite wall is from strength to weaken: density changing (
Δ
ρ
) > thermal conductivity changing (
Δ
K
m
) > latent heat fusion of liquid changing (
Δ
H
) > specific heat capacity changing (
Δ
C
p
).
The Intelligent Evaluation System for Calligraphy Characters (IESCC) is used for teaching calligraphy, and users can learn calligraphy through the modifications given by the system. Chinese character ...skeleton extraction is an important step in the intelligent evaluation algorithm of calligraphic characters. The skeletons of Chinese characters extracted by traditional refinement algorithms are prone to redundant branches and deformed skeletons, which can lead to skeleton extraction results that do not conform to the topology of the original character. In this study, the focus lies on hard‐pen regular script, and skeleton repair and extraction are performed for these characters. According to the writing characteristics of regular script, the redundant burs are removed and the deformation zone of the thinned skeleton is detected, and then the idea of first splitting is used, then restructuring, to propose a skeleton extraction algorithm based on stroke characterization and ambiguous zone detection for hard‐pen regular script, referred to as SCAD. First, a thinning algorithm is used to extract the skeleton of Chinese characters and remove redundant pixels. By analyzing the stroke characteristics of regular script, the burrs are classified and different conditions are set to detect and remove the burrs. Then the ambiguous zones are detected according to the different kinds of junction points. Then, curvature, stroke width and direction deviation are used to analyze the continuity of stroke segments, and the decision function is used to classify the stroke segments. Finally, the stroke segments with optimal pairings were compensated by interpolation according to the direction trend. This concludes the skeleton extraction. Skeleton extraction is performed on 1000 sample characters, and the SCAD algorithm can extract the skeleton of Chinese characters with an accuracy of up to 98.37%. It is proved that the SCAD method proposed here is a practical and effective method to extract the skeleton of hard‐pen regular script.
SCAD removes burrs based on the stroke characteristics of hard‐pen regular script, then finds the skeleton of Chinese characters that need to be repaired by ambiguous zone detection algorithm, then analyzes the continuity of the stroke segments connected to the ambiguous zones, and finally completes the repair and extraction of the skeleton of Chinese characters by stroke reconstruction.
Three irrigation treatments were set up in northeast China to investigate soil water movement and root water uptake of greenhouse tomatoes, and the collected experimental data were simulated by ...HYDRUS-2D. The computation and partitioning of evapotranspiration data into soil evaporation and crop transpiration was carried out with the double-crop coefficient method. The HYDRUS-2D model successfully simulated the soil water movement, producing RMSE ranging from 0.014 to 0.027, an MRE ranging from 0.062 to 0.126, and R2 ranging from 79% to 92%, when comparing model simulations with two-year field measurements. Under different water treatments, 83–90% of the total root quantity was concentrated in 0–20 cm soil layer, and the more the water deficit, the more water the deeper roots will absorb to compensate for the lack of water at the surface. The average area of soil water shortage in W1 was 2.08 times that in W2. W3 treatment hardly suffered from water stress. In the model, parameter n had the highest sensitivity compared with parameters α and Ks, and sensitivity ranking was n > Ks > α. This research revealed the relationships between soil, crop and water under drip irrigation of greenhouse tomatoes, and parameter sensitivity analysis could guide the key parameter adjustment and improve the simulation efficiency of the model.
Workflow is one of the most typical applications in distributed computing, which makes a variety of complex computing work orderly. However, assigning workflow tasks to nodes in the process of ...multi-node collaboration is still a challenge, because there are some unpredictable emergencies, i.e., uncertainty, in the process of workflow scheduling. The paper proposes a blockchain-powered resource provisioning (BPRP) method to solve the above problems. Technically, we use the directed acyclic graph in the graph theory to represent the workflow task and optimize the workflow scheduling strategy in the presence of uncertainty. The processing time and energy consumption of workflow tasks are also optimized by using non-dominated sorting genetic algorithm III (NSGA-III). Finally, we carry out experimental simulations to verify the effectiveness of the proposed method.
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