scholarly journals An Empirical Study on Peer-to-Peer Sharing of Resources in Mobile Cloud Environment

2018 ◽  
Vol 8 (3) ◽  
pp. 1933
Author(s):  
R. K. Nadesh ◽  
M. Aramudhan
Keyword(s):  
Real World ◽  
Large Scale ◽  
Cloud Model ◽  
Cloud Service ◽  
Mobile User ◽  
Peer To Peer ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Real World Application ◽  
File Formats

The increase usage of mobile users with internet and interoperability among the cloud services intensifies the role of distributed environemtnt in today’s real world application. Modern technologies are important for building rich, scalable and interoperable applications. To meet the requirements of client,the cloud service provider should offer adequate infrastructure especially under heavy multi-client load.To provide solution for large scale requirements and to statisfy the mobile client from the critical situation like lacking with bandwidth,connectivity issues,service completion ratio, we present adhoc virtual cloud model  for different scenarios that include single and multiple client configurations with various file sizes of various file formats for retrieving files in the mobile cloud environement.We evaluate the strategies with the socket and RMI implemented using java and identify the best model for real world applications. Performance evaluation is done with the results obtained and recommends that when sockets and RMI can be appropriately used in peer-to-peer environment when the mobile user cannot connect directly to the cloud services.

GOVERNMENT REGULATIONS OF THE USING CLOUD SERVICES

2022 ◽  
Author(s):  
Olexander Melnikov ◽  
◽  
Konstantin Petrov ◽  
Igor Kobzev ◽  
Viktor Kosenko ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Service Providers ◽  
Cloud Service ◽  
Cloud Services ◽  
Government Agencies ◽  
Remote Work ◽  
Cloud Infrastructure ◽  
Wide Range ◽  
Technological Base

The article considers the development and implementation of cloud services in the work of government agencies. The classification of the choice of cloud service providers is offered, which can serve as a basis for decision making. The basics of cloud computing technology are analyzed. The COVID-19 pandemic has identified the benefits of cloud services in remote work Government agencies at all levels need to move to cloud infrastructure. Analyze the prospects of cloud computing in Ukraine as the basis of e-governance in development. This is necessary for the rapid provision of quality services, flexible, large-scale and economical technological base. The transfer of electronic information interaction in the cloud makes it possible to attract a wide range of users with relatively low material costs. Automation of processes and their transfer to the cloud environment make it possible to speed up the process of providing services, as well as provide citizens with minimal time to obtain certain information. The article also lists the risks that exist in the transition to cloud services and the shortcomings that may arise in the process of using them.

Operational Cost of Running Real-Time Mobile Cloud Applications

2015 ◽  
pp. 294-321 ◽  
Author(s):  
Ovunc Kocabas ◽  
Regina Gyampoh-Vidogah ◽  
Tolga Soyata
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Service Level ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Cost Models ◽  
Operational Cost ◽  
Resource Requirements ◽  
The Cost ◽  
Cloud Applications

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.

Research on the Frame System of Digital Library Mobile Cloud Service Platform

2014 ◽  
Vol 1061-1062 ◽  
pp. 1079-1082
Author(s):  
Min Yao
Keyword(s):  
Digital Library ◽  
Information Service ◽  
Cloud Service ◽  
Mobile Terminal ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Main Function ◽  
Computing Platform ◽  
Mobile Cloud Service ◽  
Frame System

Mobile cloud computing provides a deeper hierarchical tangibility for the construction and environment of digital library and mobile cloud services will certainly become the service mode of the future digital library. From three aspects: information resources integration, the expansion of mobile terminal device capability, information service innovation, this paper discusses upgrade of overall strength of mobile cloud design to digital library information service. At the same time, it also detailed introduces the main function of mobile computing platform layer, mobile cloud library platform layer and mobile terminal application layer.

scholarly journals A Hybrid Deep Learning System for Real-World Mobile User Authentication Using Motion Sensors

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3876 ◽  
Author(s):  
Tiantian Zhu ◽  
Zhengqiu Weng ◽  
Guolang Chen ◽  
Lei Fu
Keyword(s):  
Feature Extraction ◽  
Deep Learning ◽  
Mobile Devices ◽  
Real World ◽  
Large Scale ◽  
User Authentication ◽  
Mobile User ◽  
Learning System ◽  
Support Vector ◽  
Motion Sensors

With the popularity of smartphones and the development of hardware, mobile devices are widely used by people. To ensure availability and security, how to protect private data in mobile devices without disturbing users has become a key issue. Mobile user authentication methods based on motion sensors have been proposed by many works, but the existing methods have a series of problems such as poor de-noising ability, insufficient availability, and low coverage of feature extraction. Based on the shortcomings of existing methods, this paper proposes a hybrid deep learning system for complex real-world mobile authentication. The system includes: (1) a variational mode decomposition (VMD) based de-noising method to enhance the singular value of sensors, such as discontinuities and mutations, and increase the extraction range of the feature; (2) semi-supervised collaborative training (Tri-Training) methods to effectively deal with mislabeling problems in complex real-world situations; and (3) a combined convolutional neural network (CNN) and support vector machine (SVM) model for effective hybrid feature extraction and training. The training results under large-scale, real-world data show that the proposed system can achieve 95.01% authentication accuracy, and the effect is better than the existing frontier methods.

Digital Library Knowledge Service Model Research Based on Mobile Cloud Computing

2014 ◽  
Vol 631-632 ◽  
pp. 200-203
Author(s):  
Min Yao
Keyword(s):  
Digital Library ◽  
Mobile Cloud Computing ◽  
Cloud Service ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Service Model ◽  
Knowledge Processing ◽  
Model Research ◽  
Technology Services ◽  
Knowledge Services

Digital library cloud service is the development and extension of traditional digital library knowledge services under the environment of mobile cloud. Meanwhile, it’s also the new stage of knowledge services development. Based on the analysis of mobile cloud technology services model and its advantages, taking “end”, ”tube”, ”cloud” as the main line, this paper build up digital library mobile cloud knowledge services model from three aspects: knowledge collecting, knowledge processing and knowledge using. Thus, it point out the opportunities and challenges faced by mobile cloud services and present the strategies of implementing knowledge cloud services.

scholarly journals Context-Aware Cloud Service Selection Model for Mobile Cloud Computing Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xu Wu
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Relational Degree ◽  
Computing Environments ◽  
Traditional Approaches ◽  
Trustworthy Service

Mobile cloud computing (MCC) has attracted extensive attention in recent years. With the prevalence of MCC, how to select trustworthy and high quality mobile cloud services becomes one of the most urgent problems. Therefore, this paper focuses on the trustworthy service selection and recommendation in mobile cloud computing environments. We propose a novel service selection and recommendation model (SSRM), where user similarity is calculated based on user context information and interest. In addition, the relational degree among services is calculated based on PropFlow algorithm and we utilize it to improve the accuracy of ranking results. SSRM supports a personalized and trusted selection of cloud services through taking into account mobile user’s trust expectation. Simulation experiments are conducted on ns3 simulator to study the prediction performance of SSRM compared with other two traditional approaches. The experimental results show the effectiveness of SSRM.

scholarly journals A Dimension Separation Based Hybrid Classifier Ensemble for Locating Faults in Cloud Services

2016 ◽  
Vol 11 (4) ◽  
pp. 493
Author(s):  
Min-jing Peng ◽  
Yun Yue ◽  
Bo Li ◽  
Chun-yang Wang
Keyword(s):  
Neural Network ◽  
Data Fusion ◽  
Large Scale ◽  
Fault Location ◽  
Service System ◽  
Cloud Service ◽  
Cloud Services ◽  
Classifier Ensemble ◽  
Neural Network Ensemble ◽  
The Neural Network

<p>Cloud services provide Internet users with various services featured with data fusion through the dynamic and expandable virtual resources. Because a large amount of data runs in different modules of the cloud service systems, it will inevitably produce all kinds of failures when the data is processed in and transferred between modules. Therefore the job of rapid fault location has an important role in improving the quality of cloud services. Because of the features of large scale and data fusion of data in the cloud service system, it is difficult to use the conventional fault locating method to locate the faults quickly. Taking the requirements on the speed of locating faults into account, we will make a clear division to all possible failure causes according to the business phases, and quickly locate the faults by implementing a cascading structure of the neural network ensemble. At last, we conducted an experiment of locating faults in a cloud service system runned by a telecom operator, comparing the proposed hybird classifier ensemble with neural networks trained by separated data subsets and a conventional neural network ensemble based on bagging algorithm. The experiment proved that the neural network ensemble based on dimension separation is effective for locating faults in cloud services.</p>

scholarly journals Context-aware resource allocation and scheduling of hybrid mobile cloud

2021 ◽  
Author(s):  
Hager M. Ghouma
Keyword(s):  
Resource Allocation ◽  
Resource Constraints ◽  
Cloud Service ◽  
Mobile User ◽  
Cloud Services ◽  
User Mobility ◽  
Context Aware ◽  
Resource Allocation Algorithm ◽  
User Context ◽  
Earliest Deadline

Cloud services can compensate for the resource constraints of mobile devices. However, challenges of utilizing the cloud service by mobile users arise from inherent characteristics such as user mobility and device energy. In this paper, we propose a scheme to monitor the energy level and communication quality as a part of a mobile user context information, and develop a resource allocation and scheduling scheme to adapt to the context changes by exploiting the slack time. The objective is to reduce the execution cost of the jobs while meeting the jobs deadlines set by the users. We developed Simulated Annealing based resource allocation algorithm and Earliest Deadline First scheduling. Simulation of our scheme using CloudSim and synthetic workload based on Google Cluster Traces shows benefits in reducing execution cost and improving resource utilization.

Operational Cost of Running Real-Time Mobile Cloud Applications

2016 ◽  
pp. 1111-1137
Author(s):  
Ovunc Kocabas ◽  
Regina Gyampoh-Vidogah ◽  
Tolga Soyata
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Service Level ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Cost Models ◽  
Operational Cost ◽  
Resource Requirements ◽  
The Cost ◽  
Cloud Applications

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.

An analysis of QoS ranking prediction framework techniques

2019 ◽  
Vol 33 (01) ◽  
pp. 1850420 ◽  
Author(s):  
Harsimran Kaur ◽  
Anurag Rai ◽  
Sarvjit Singh Bhatia
Keyword(s):  
Real World ◽  
Cloud Service ◽  
Cloud Services ◽  
Cloud Service Provider ◽  
The Real ◽  
Functional Activities ◽  
On Demand ◽  
The Right ◽  
Demand Service

In the real world, building the high quality cloud computing framework is the challenge for the researcher in the present scenario where on demand service is required. The services which are performing the non-functional activities are referred to as Quality-of Service (QoS). The experience of real-world usage services are generally required to obtain the QoS. Many organizations offer various cloud services, such as Amazon, HP and IBM, to the customers. No technique is available to measure the real-world usage and estimate the ranking of the cloud services. From the customer side, it is a very tough job to choose the right cloud service provider (SP), which fulfills all the requirements of the customers. To avoid the confusion to select the right CSP, this paper proposes QoS ranking prediction methods such as Cloud Rank1, Cloud Rank2 and Cloud Rank3. Various experiments are done on the real-world QoS data by using EC2 services of Amazon and providing healthy results and solutions.

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