Analysis of Cloud Computing Algorithm based on Smart Campus Message System

doi:10.23940/ijpe.19.02.p34.700709

Abstract

Abstract:

In order to solve the shortcomings of the smart campus message system constructed by the current method in network indicators, data processing, business interface, human-computer interaction,and other technologies, a cloud computing algorithm-based smart campus message system construction methodwas proposed. In this method, the LAN interconnection, the network multimedia terminal, and the network architecture platform were established by the cloud computing algorithm. This method established the awareness of smart campus development, established the cloud smart campus management norm system, and constrained the network environment based on the cloud smart campus. The overall structure of the smart campus message system was constructed from the technical level, the main layer,and the constraint layer. The functional module analysis of the smart campus message system software was performed, which had two major categories, including basic function modules and extended function modules. It achieved the construction of a smart campus messaging system based on cloud computing algorithms. The experimental results showed that the proposed method had obvious advantages in network indicators, data processing, business interface, human-computer interaction and other technologies which can bring a lot of convenience to the school staff.

Key words: smart campus, message system, cloud computing algorithm

Ning Ma and Weina Fu. Analysis of Cloud Computing Algorithm based on Smart Campus Message System [J]. Int J Performability Eng, 2019, 15(2): 700-709.

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References 15

[1]	K. Kusakana , “Optimal Scheduled Power Flow for Distributed Photovoltaic/Wind/Diesel Generators with the BatteryStorage System,”IET Renewable Power Generation,Vol. 9, pp. 916-924, 2015
[2]	Y. Yu, M. H. Au, G. Ateniese, X. Huang, W. Susilo, Y. Dai , et al., “Identity-based Remote Data Integrity Checking with Perfect Data Privacy Preserving for Cloud Storage,”IEEE Transactions on Information Forensics and Security,Vol. 12, pp. 767-778, 2017 doi: 10.1109/TIFS.2016.2615853
[3]	X. Liu, “A Study on Smart Campus Model in the Era of Big Data,” in Proceedings of the 2016 2nd International Conference on Economics, Management Engineering and Education Technology (ICEMEET 2016), pp. 919-922, 2016
[4]	N. A. Kassim , “Evaluating Users’ Satisfaction on Academic Library Performance,”Malaysian Journal of Library & Information Science,Vol. 14, pp. 101-115, 2017
[5]	W.J. Shyr , L.-W. Zeng, C.-K. Lin, C.-M. Lin, and W.-Y. Hsieh, “Application of an Energy Management System via the Internet of Things on a University Campus,”Eurasia Journal of Mathematics, Science and Technology Education,Vol. 14, pp. 1759-1766, 2018
[6]	S. Liu, W. Fu, H. Deng, C. Lan, J. Zhou , “Distributional Fractal Creating Algorithm in ParallelEnvironment,”International Journal of Distributed Sensor Networks,Vol. 9, pp. 281707, 2013
[7]	Y. Huang, C. White, H. Xia, Y. Wang , “A Computational Cognitive ModellingApproach to Understand and Design Mobile Crowdsourcing for Campus Safety Reporting,”International Journal of Human-Computer Studies,Vol. 102, pp. 27-40, 2017 doi: 10.1016/j.ijhcs.2016.11.003
[8]	M. Liu, S. Liu, W. Fu, J. Zhou , “Distributional Escape Time Algorithm based on Generalized Fractal Sets in CloudEnvironment,”Chinese Journal of Electronics,Vol. 24, pp. 124-127, 2015 doi: 10.1049/cje.2015.01.020
[9]	M. Arif, M. Illahi, A. Karim, S. Shamshirband, K. A. Alam, S. Farid , et al., “An Architecture of Agent-based Multi-Layer Interactive E-Learning and E-Testing Platform,”Quality & Quantity,Vol. 49, pp. 2435-2458, 2015 doi: 10.1007/s11135-014-0121-9
[10]	D. Li, J. Cao, Y. Yao , “Big Data in Smart Cities,”Science China Information Sciences,Vol. 58, pp. 1-12, 2015
[11]	S. Ting, Y. Tse, G. Ho, S. Chung, G. Pang , “Mining Logistics Data to Assure the Quality in a Sustainable Food Supply Chain: A Case in the Red Wine Industry,”International Journal of Production Economics,Vol. 152, pp. 200-209, 2014 doi: 10.1016/j.ijpe.2013.12.010
[12]	B. Jia, S. Liu, Y. Yang , “Fractal Cross-Layer Service with Integration and Interaction in Internet of Things,”International Journal of Distributed Sensor Networks,Vol. 10, pp. 760248, 2014
[13]	X. Haiyun and F. Xiao, “Design of Digital Campus Office Automation System based on Portlet and Workflow,” Issues, 2016
[14]	P. K. Paul and M. K. Ghose, “A Novel Educational Proposal and Strategies Toward Promoting Cloud Computing, Big Data, and Human-Computer Interaction in Engineering Colleges and Universities,” in Advances in Smart Grid and Renewable Energy, ed: Springer, pp. 93-102, 2018
[15]	X. Li, J. Song, B. Huang , “A Scientific Workflow Management System Architecture and its Scheduling based on Cloud Service Platform for Manufacturing Big Data Analytics,”The International Journal of Advanced Manufacturing Technology,Vol. 84, pp. 119-131, 2016 doi: 10.1007/s00170-015-7804-9

	Proposed Method	Literature [5] method
Network composition	Network infrastructure convergence and cross-applications such as the Internet, wireless LAN and Internet of Things	Internet-based, partially independent wireless local area network.
Network architecture	Adopting a central network and a peer-to-peer network, different network nodes cooperate with each other	Mainly based on the central network, with the central gateway strictly controlling the nodes
Network application	Network-based applications, including network-based LBS.	The network is mainly used for data transmission.

	Proposed method	Literature [5] method
Interface design	The so-called interface is an independent, non-repetitive basic service module. Smart campus services are based on interface secondary packaging to form a high-level interface.	There is no definition of a unified interface. Various service interfaces are vague, scattered and repetitive. Difficult to reuse and secondary packaging.
Interface technology	Both use Web Service. Technical realization. Specification naming.	There is no unified interface technology for each application system.

data	Proposed method	Literature [5] method
data maintenance	The smart campus messaging system relies on a unified distributed database.	A single database. Different application database types are different.
Data Sources	In addition to basic business data, it also includes a variety of context-aware data.	It’s just business data, and the databases of different applications are mostly incompatible.
data processing	Includes unified data mining and analysis, big data analysis	Various types of system data mining are independent, and its mining data cannot be used by other systems.

Human interaction	Proposed method	Literature [5] method
Interactive page	Unified gateway, unified page layout	Different applications have their own separate UI design
Interactive place	The platform application can realize a unified interactive page in the desktop terminal and the mobile terminal.	Many applications do not take into account the needs of mobile end users。
Interactive place	In addition to basic entry input, it also includes perceptual-based interactions such as voice control, rejuvenation, and more.	Basic information query, delete, update and other operations.