Applying Hadoop Cloud Computing Technique to Optimal Design of Optical Networks (Invited)

2015 ◽  
Author(s):  
Yongcheng Li ◽  
Gangxiang Shen ◽  
Bowen Chen ◽  
Mingyi Gao ◽  
Xiaodong Fu
Keyword(s):  
Cloud Computing ◽  
Optimal Design ◽  
Optical Networks ◽  
Computing Technique

scholarly journals Cloud Computing Technique Applied to Detect Cyber-Attacks on Web Application

2020 ◽  
Vol 9 (4) ◽  
pp. 1498-1500
Keyword(s):  
Cloud Computing ◽  
Web Application ◽  
Current System ◽  
Cyber Attacks ◽  
Individual Data ◽  
Computing Technique ◽  
Correct Number ◽  
Proposed Model

The targeted malignant emails (TME) for PC arrange misuse have become progressively deceptive and all the more generally common as of late. Aside from spam or phishing which is intended to fool clients into uncovering individual data, TME can misuse PC systems and accumulate touchy data which can be a major issue for the association. They can comprise of facilitated and industrious battles that can be terrible. Another email-separating procedure which depends on bowl classifier and beneficiary arranged highlights with an arbitrary backwoods classifier which performs superior to two conventional recognition techniques, Spam Assassin and Clam AV, while keeping up sensible bogus positive rates. This proposed model deals with how to recognize a pernicious bundle (email) for ordinary system into current system. We build up an undermined protocol of network detection that powerfully concludes the correct number of congestive loss of packets that is going to happen. On the chance that one damages the steering convention itself, at that point aggressor may make enormous segments of the system become untreatable. We build up an option shifting technique by utilizing TME explicit element extraction. Our conventions naturally anticipate clog in a deliberate manner, as it is vital in making any such flaw in network recognition reasonable.

Vehicular Cloud and Fog Computing Architecture, Applications, Services, and Challenges

2020 ◽  
pp. 268-296
Author(s):  
Priyanka Gaba ◽  
Ram Shringar Raw
Keyword(s):  
Cloud Computing ◽  
High Speed ◽  
Fog Computing ◽  
Detailed Comparison ◽  
Fast Response ◽  
Computing Technique ◽  
Vehicular Cloud ◽  
Network Bandwidth ◽  
Real Time Applications ◽  
Safety Features

VANET, a type of MANET, connects vehicles to provide safety and non-safety features to the drivers and passengers by exchanging valuable data. As vehicles on road are increasing to handle such data cloud computing, functionality is merged with vehicles known as Vehicular Cloud Computing(VCC) to serve VANET with computation, storage, and networking functionalities. But Cloud, a centralized server, does not fit well for vehicles needing high-speed processing, low latency, and more security. To overcome these limitations of Cloud, Fog computing was evolved, extending the functionality of cloud computing model to the edge of the network. This works well for real time applications that need fast response, saves network bandwidth, and is a reliable, secure solution. An application of Fog is with vehicles known as Vehicular Fog Computing (VFC). This chapter discusses cloud computing technique and its benefits and drawbacks, detailed comparison between VCC and VFC, applications of Fog Computing, its security, and forensic challenges.

Research Progress of Next Generation Optical Networks Technology for Cloud Computing

2015 ◽  
Vol 52 (7) ◽  
pp. 070003
Author(s):  
李明 Li Ming ◽  
张引发 Zhang Yinfa ◽  
任帅 Ren Shuai ◽  
王鲸鱼 Wang Jingyu ◽  
廖晓敏 Liao Xiaomin
Keyword(s):  
Cloud Computing ◽  
Optical Networks ◽  
Research Progress ◽  
Next Generation

Optimal Design of Wireless-Powered Hierarchical Fog-Cloud Computing Networks

2019 ◽  
Author(s):  
Jingxian Liu ◽  
Ke Xiong ◽  
Derrick Wing Kwan Ng ◽  
Pingyi Fan ◽  
Zhangdui Zhong
Keyword(s):  
Cloud Computing ◽  
Optimal Design

The Research on University Librarys "Four-in-One" Cloud Computing Services Social System

2013 ◽  
Vol 791-793 ◽  
pp. 1297-1300 ◽  
Author(s):  
Xu Fu Peng ◽  
Shu Dong Shi
Keyword(s):  
Cloud Computing ◽  
Social Services ◽  
Resource Sharing ◽  
Social System ◽  
System Function ◽  
Computing Technique ◽  
Information Platform ◽  
Computing Services ◽  
Cloud Computing Service ◽  
Cloud Computing Services

Aiming at the problems on the management system, function orientation, resource sharing, information platform construction, technical support in university social services, the characteristics of cloud computing technique and its influence on the library informatization were carefully analyzed. The four-in-one cloud computing service society system structures of university library about reading, borrowing, selling, and service were designed and constructed .The problems of how the library serve the society in all directions were solved.

scholarly journals Visibility estimation via deep label distribution learning in cloud environment

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mofei Song ◽  
Xu Han ◽  
Xiao Fan Liu ◽  
Qian Li
Keyword(s):  
Cloud Computing ◽  
Ground Truth ◽  
Learning Performance ◽  
Estimation Result ◽  
Cloud Environment ◽  
Computational Power ◽  
Computing Technique ◽  
Multiple Images ◽  
Label Distribution ◽  
Visibility Estimation

AbstractThe visibility estimation of the environment has great research and application value in the fields of production. To estimate the visibility, we can utilize the camera to obtain some images as evidence. However, the camera only solves the image acquisition problem, and the analysis of image visibility requires strong computational power. To realize effective and efficient visibility estimation, we employ the cloud computing technique to realize high-through image analysis. Our method combines cloud computing and image-based visibility estimation into a powerful and efficient monitoring framework. To train an accurate model for visibility estimation, it is important to obtain the precise ground truth for every image. However, the ground-truth visibility is difficult to be labeled due to its high ambiguity. To solve this problem, we associate a label distribution to each image. The label distribution contains all the possible visibilities with their probabilities. To learn from such annotation, we employ a CNN-RNN model for visibility-aware feature extraction and a conditional probability neural network for distribution prediction. The estimation result can be improved by fusing the predicting results of multiple images from different views. Our experiment shows that labeling the image with visibility distribution can boost the learning performance, and our method can obtain the visibility from the image efficiently.

Optical networks in cloud computing [Guest Editorial]

IEEE Network ◽  
2013 ◽  
Vol 27 (6) ◽  
pp. 4-5 ◽  
Author(s):  
Zuqing Zhu ◽  
S.J. Ben Yoo ◽  
Zhaohui Li ◽  
Nicolas Fontaine
Keyword(s):  
Cloud Computing ◽  
Optical Networks ◽  
Guest Editorial
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