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Task-Based Resource Allocation Bid in Edge Computing Micro Datacenter
No full textEdge computing attracts online service providers (SP) to offload services to edge computing micro datacenters that are close to end users. Such offloads reduce packet-loss rates, delays and delay jitter when responding to service requests. Simultaneously, edge computing resource providers (RP) are concerned with maximizing incomes by allocating limited resources to SPs. Most works on this topic make a simplified assumption that each SP has a fixed demand; however, in reality, SPs themselves may have multiple task-offloading alternatives. Thus, their demands could be flexibly changed, which could support finer-grained allocations and further improve the incomes for RPs. Here, we propose a novel resource bidding mechanism for the RP in which each SP bids resources based on the demand of a single task (task-based) rather than the whole service (service-based) and then the RP allocates resources to these tasks with following the resource constraints at edge servers and the sequential rule of task-offloading to guarantee the interest of SPs. We set the incomes of the RP as our optimization target and then formulate the resource allocation problem. Two typical greedy algorithms are adopted to solve this problem and analyze the performance differences using two different bidding methods. Comprehensive results show that our proposal optimizes resource utilization and improves the RP’s incomes when resources in the edge computing datacenter are limited
Identification of phytohormone changes and its related genes under abiotic stresses in transgenic rice
No full textAbiotic stresses, such as drought and salinity, adversely affect plant growth and productivity. Comparison
between non transgenic and transgenic rice harboring CaMsrB2 gene, which induces tolerance to abiotic stress, is
important to observe response of gene under abiotic stress. Phytohormone showed a tendency to increase under
the drought stress or salinity stress in the transgenic plant. RT-PCR analysis showed that gene expression and
phytohormone levels under abiotic stress, to be closely related. The CaMsrB2 gene is related to the expression of JA and
ABA hormones. Therefore, the level of expression of these genes and hormones was observed. The transcription levels
of LOX2 and OsWRKY45 were substantially higher in the wild type rice in comparison to the transformants, which
suggested that phytohormone are also required for the regulation of leaf and root. Comparison between control and
transgenic rice overexpressing a CaMsrB2 gene, resulted in different pattern of ABA, JA levels under different stress
condition. In both drought and salinity stresses, the expression of OsWRKY45 gene was similar in both treatments with
time. These results suggest that gene involved in the plant physiology response in mechanism to abiotic stress
Feasible design for electricity generation from <i>Chlorella vulgaris</i> using convenient photosynthetic conditions
No full textMany recent studies are concerned with low cost, easy to handle and alternative renewable energy as a
feasible solution for the upcoming crisis of energy shortage. Microalgae are unicellular entities the can only depend
on CO2, water and solar power to cover their nutritional needs. The current study is concerned with using algal cells
in a polymeric hydrogel, as a cheap source of energy for electricity generation. Chlorella vulgaris has been proved to
be a promising algal species for electricity generation, as compared with Micractinium reisseri. PVA hydrogel has been
used for the immobilization of both algal species in order to protect them from the adverse surrounding conditions
in addition to its ability to slowly release the required water molecules according to needs. Under these conditions,
C. vulgaris showed the ability to generate 60 mV compared with 15 mV generated by M. reisseri. Scanning electron
micrographs showed nano-threads that bind the C. vulgaris cells to each other, indicating the ability of algae to create
nanowires that facilitate the electron transfer among algal cells and from cells to the nearest electrode. However, we
would expect an increase in the produced potential with simultaneous amendment of environmentally polluted water,
such as sewage or waste water. Both of FTIR and raman spectroscopy proved the presence of the characteristic groups
of PVA hydrogel and proved the proper integration of the algal cells inside the hydrogel cavitie
A Study on the Optimal Offset Distance Between a Welding Torch and the Infrared Thermometers
Get PDFDetection of weld defects using real-time monitoring and controlling algorithm is of the significant task in manufacturing industries due to the increased production and liability costs that result when weld defects are not identified early in the production cycle. Monitoring and controlling for robotic arc welding process employed should be reliable, flexible and cost-effective in non-clean, high-volume production environments. Also, the robotic welding system has been utilized a complex jigging and mechanical devices to move the workpiece which related to the stationary welding head for getting higher efficiency and lower costs. To develop the fully robotic welding system, people make use of their senses of sound and/or sight to collect welding information, and take the necessary corrective measurements to ensure the weld quality after processing is satisfactory. Therefore, it is really required that the monitoring and controlling algorithm of sensors for increasing effectiveness in the robotic welding process has been developed. In this paper, bead-on-plate welding using an infrared thermography in the robotic GMA (Gas Metal Arc) welding process has been performed to study the effects of welding parameters on thermal profile characteristics and find the optimal offset distance which applied for monitoring and controlling of welding quality such as bead height. The analysis for correlation between temperature distributions at three offset distance and bead height which based on the regression analysis such as Standard Error of Estimate (SEE), the coefficient of correlation (R) and coefficient of determination (R2) and (Predictive Ability of Model) has been done. The infra-red sensor is useful for monitoring the isotherm radii that arise during the robotic welding process and identifying bead height as welding quality
Research on the Relationship Between Garlic and Young Garlic Shoot Based on Big Data
Get PDFIn view of the problems such as frequent fluctuation of garlic price, lack of efficient forecasting means and difficulty in realizing the steady development of garlic industry, combined with the current situation of garlic industry and the collected data information. Taking Big Data platform of garlic industry chain as the core, using the methods of correlation analysis, smoothness test, co-integration test, and Granger causality test, this paper analyzes the correlation, dynamic, and causality between garlic price and young garlic shoot price. According to the current situation of garlic industry, the garlic industry service based on Big Data is put forward. It is concluded that there is a positive correlation between garlic price and young garlic shoot price, and there is a long-term stable dynamic equilibrium relationship between young garlic shoot price and garlic price fluctuation, and young garlic shoot price can affect garlic price. Finally, it is proposed to strengthen the infrastructure construction of garlic Big Data, increase the technological innovation and application of garlic Big Data technology, and promote the safety and security ability of the whole industry to promote the development of garlic industry
Research on the Signal Reconstruction of the Phased Array Structural Health Monitoring Based Using the Basis Pursuit Algorithm
Get PDFThe signal processing problem has become increasingly complex and demand high acquisition system, this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal. The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals. According to the principles of the compressive sensing and signal processing method, non-sparse ultrasonic signals are converted to sparse signals by using sparse transform. The sparse coefficients are obtained by sparse decomposition of the original signal, and then the observation matrix is constructed according to the corresponding sparse coefficients. Finally, the original signal is reconstructed by using basis pursuit algorithm, and error analysis is carried on. Experimental research analysis shows that the signal reconstruction method can reduce the signal complexity and required the space efficiently
Social-Aware Based Secure Relay Selection in Relay-Assisted D2D Communications
Get PDFRelay-assisted transmission could effectively enhance the performance of Device-to-Device (D2D) communications when D2D user equipments (UEs) are too far away from each other or the quality of D2D channel is not good enough for direct communications. Meanwhile, security is one of the major concerns for proximity services. The secure relay selection problem for D2D communications underlaying cellular network is studied in this paper. Firstly, we define a relay selection area and derive the closed-form of outage probability in D2D links using a Poisson Point Process (PPP) method. Next, in the defined relay selection area, we propose a secure relay selection scheme for the relay-assisted D2D communication system by exploiting the social relation as a security factor. Simulation results show that the scheme based on social relation can greatly improve the security performance of relay-assisted D2D communications
Investigation on the Chinese Text Sentiment Analysis Based on Convolutional Neural Networks in Deep Learning
Get PDFNowadays, the amount of wed data is increasing at a rapid speed, which presents a serious challenge to the web monitoring. Text sentiment analysis, an important research topic in the area of natural language processing, is a crucial task in the web monitoring area. The accuracy of traditional text sentiment analysis methods might be degraded in dealing with mass data. Deep learning is a hot research topic of the artificial intelligence in the recent years. By now, several research groups have studied the sentiment analysis of English texts using deep learning methods. In contrary, relatively few works have so far considered the Chinese text sentiment analysis toward this direction. In this paper, a method for analyzing the Chinese text sentiment is proposed based on the convolutional neural network (CNN) in deep learning in order to improve the analysis accuracy. The feature values of the CNN after the training process are nonuniformly distributed. In order to overcome this problem, a method for normalizing the feature values is proposed. Moreover, the dimensions of the text features are optimized through simulations. Finally, a method for updating the learning rate in the training process of the CNN is presented in order to achieve better performances. Experiment results on the typical datasets indicate that the accuracy of the proposed method can be improved compared with that of the traditional supervised machine learning methods, e.g., the support vector machine method
Collaborative Filtering Recommendation Algorithm Based on Multi-Relationship Social Network
Get PDFRecommendation system is one of the most common applications in the field of big data. The traditional collaborative filtering recommendation algorithm is directly based on user-item rating matrix. However, when there are huge amounts of user and commodities data, the efficiency of the algorithm will be significantly reduced. Aiming at the problem, a collaborative filtering recommendation algorithm based on multi-relational social networks is proposed. The algorithm divides the multi-relational social networks based on the multi-subnet complex network model into communities by using information dissemination method, which divides the users with similar degree into a community. Then the user-item rating matrix is constructed by choosing the k-nearest neighbor set of users within the community, in this case, the collaborative filtering algorithm is used for recommendation. Thus, the execution efficiency of the algorithm is improved without reducing the accuracy of recommendation
Enabling Comparable Search Over Encrypted Data for IoT with Privacy-Preserving
Get PDFWith the rapid development of cloud computing and Internet of Things (IoT) technology, massive data raises and shuttles on the network every day. To ensure the confidentiality and utilization of these data, industries and companies users encrypt their data and store them in an outsourced party. However, simple adoption of encryption scheme makes the original lose its flexibility and utilization. To address these problems, the searchable encryption scheme is proposed. Different from traditional encrypted data search scheme, this paper focuses on providing a solution to search the data from one or more IoT device by comparing their underlying numerical values. We present a multi-client comparable search scheme over encrypted numerical data which supports range queries. This scheme is mainly designed for keeping the confidentiality and searchability of numeric data, it enables authorized clients to fetch the data from different data owners by a generated token. Furthermore, to rich the scheme’s functionality, we exploit the idea of secret sharing to realize cross-domain search which improves the data’s utilization. The proposed scheme has also been proven to be secure through a series of security games. Moreover, we conduct experiments to demonstrate that our scheme is more practical than the existed similar schemes and achieves a balance between functionality and efficiency