scholarly journals A Trust-Based Defensive System Model for Cloud Computing

2011 ◽  
pp. 146-159 ◽  
Author(s):  
Qian Zhou ◽  
Jiong Yu ◽  
Feiran Yu
Keyword(s):  
Cloud Computing ◽  
System Model

scholarly journals Towards Fast Response, Reduced Processing and Balanced Load in Fog-Based Data-Driven Smart Grid

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3345 ◽  
Author(s):  
Rasool Bukhsh ◽  
Nadeem Javaid ◽  
Zahoor Ali Khan ◽  
Farruh Ishmanov ◽  
Muhammad Afzal ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Smart Grid ◽  
Data Center ◽  
Smart Grids ◽  
Data Centers ◽  
Residential Buildings ◽  
System Model ◽  
Data Driven ◽  
Efficient Allocation ◽  
Selection Of

The integration of the smart grid with the cloud computing environment promises to develop an improved energy-management system for utility and consumers. New applications and services are being developed which generate huge requests to be processed in the cloud. As smart grids can dynamically be operated according to consumer requests (data), so, they can be called Data-Driven Smart Grids. Fog computing as an extension of cloud computing helps to mitigate the load on cloud data centers. This paper presents a cloud–fog-based system model to reduce Response Time (RT) and Processing Time (PT). The load of requests from end devices is processed in fog data centers. The selection of potential data centers and efficient allocation of requests on Virtual Machines (VMs) optimize the RT and PT. A New Service Broker Policy (NSBP) is proposed for the selection of a potential data center. The load-balancing algorithm, a hybrid of Particle Swarm Optimization and Simulated Annealing (PSO-SA), is proposed for the efficient allocation of requests on VMs in the potential data center. In the proposed system model, Micro-Grids (MGs) are placed near the fogs for uninterrupted and cheap power supply to clusters of residential buildings. The simulation results show the supremacy of NSBP and PSO-SA over their counterparts.

Design of Peer-to-Peer Traffic Classification System Model Based on Cloud Computing

2012 ◽  
Vol 182-183 ◽  
pp. 1347-1351 ◽  
Author(s):  
Xi Zi Liu ◽  
Ya Bin Xu
Keyword(s):  
Cloud Computing ◽  
Parallel Computing ◽  
Classification System ◽  
Peer To Peer ◽  
System Model ◽  
Traffic Classification ◽  
Current Application ◽  
Advantages And Disadvantages ◽  
Network Bandwidth ◽  
Distributed Parallel Computing

The advantages and disadvantages of mainstream peer-to-peer (P2P) traffic classification technology in the current application are analyzed. As existing traffic classification tools fail to meet the super flow, as well as continuous increasing of network bandwidth, a cloud-based P2P traffic classification system model is proposed, which use the distributed parallel computing architecture named MapReduce based on hadoop.

Research of University Comprehensive Information System Based on Cloud Computing

2012 ◽  
Vol 433-440 ◽  
pp. 4857-4860
Author(s):  
Wei Li ◽  
Hai Duan Huang ◽  
Jie Lu ◽  
Gang Tian
Keyword(s):  
Cloud Computing ◽  
Information System ◽  
Customer Service ◽  
Data Storage ◽  
System Model ◽  
System Construction ◽  
Software Application ◽  
Comprehensive Information ◽  
Application Mode ◽  
Definition Of

The paper introduces the definition of cloud computing, characteristics and service mode. In view of the present situation of university information system construction, this paper presents a university comprehensive information system model based on cloud computing, which consists of infrastructure layer, business data processing layer, application system layer and customer service layer. The high effectiveness and advancement of information system model in infrastructure utilization ratio, information sharing degree, the security of data storage, software application mode etc are discussed.

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