Modeling 5G wireless network service reliability prediction with bayesian network

2016 ◽  
Author(s):  
Bilgehan Erman ◽  
Simon Yiu
Keyword(s):  
Bayesian Network ◽  
Wireless Network ◽  
Reliability Prediction ◽  
Service Reliability ◽  
Network Service

scholarly journals Competition of Duopoly MVNOs for IoT Applications through Wireless Network Virtualization

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Wanli Zhang ◽  
Xianwei Li ◽  
Liang Zhao ◽  
Xiaoying Yang
Keyword(s):  
Radio Frequency ◽  
Wireless Network ◽  
Network Performance ◽  
Stackelberg Game ◽  
Network Virtualization ◽  
Network Services ◽  
Network Service ◽  
Iot Applications ◽  
Wireless Network Virtualization ◽  
Iot Devices

Network performance is of great importance for processing Internet of Things (IoT) applications in the fifth-generation (5G) communication system. With the increasing number of the devices, how network services should be provided with better performances is becoming a pressing issue. The static resource allocation of wireless networks is becoming a bottleneck for the emerging IoT applications. As a potential solution, network virtualization is considered a promising approach to enhancing the network performance and solving the bottleneck issue. In this paper, the problem of wireless network virtualization is investigated where one wireless infrastructure provider (WIP), mobile virtual network operators (MVNOs), and IoT devices coexist. In the system model under consideration, with the help of a software-defined network (SDN) controller, the WIP can divide and reconfigure its radio frequency bands to radio frequency slices. Then, two MVNOs, MVNO1 and MVNO2, can lease these frequency slices from the WIP and then provide IoT network services to IoT users under competition. We apply a two-stage Stackelberg game to investigate and analyze the relationship between the two MVNOs and IoT users, where MVNO1 and MVNO2 firstly try to maximize their profits by setting the optimal network service prices. Then, IoT users make decisions on which network service they should select according to the performances and prices of network services. Two competition cases between MVNO1 and MVNO2 are considered, namely, Stackelberg game (SG) where MVNO1 is the leader whose price of network service is set firstly and MVNO2 is the follower whose network service price is set later and noncooperative strategic game (NSG) under which the service prices of MVNO1 and MVNO2 are simultaneously set. Each IoT user decides whether and which MVNO to select on the basis of the network service prices and qualities. The numerical results are provided to show the effectiveness of our game model and the proposed solution method.

Reliability Evaluation System of Electronics Components

2006 ◽  
Vol 326-328 ◽  
pp. 569-572 ◽  
Author(s):  
Seung Woo Lee ◽  
Seung Woo Han ◽  
Jun Yeob Song ◽  
Wan Doo Kim ◽  
Hwa Ki Lee
Keyword(s):  
Evaluation System ◽  
Reference Model ◽  
Reliability Evaluation ◽  
Reliability Prediction ◽  
Service Reliability ◽  
Electronic Components ◽  
Reliability Data ◽  
Physics Of Failure ◽  
Printed Circuits

The reliability, that is long-term quality, requires a different approaching from short-term quality which is used before. As the electronic components are to be easily normalized on the reliability evaluation, many reliability prediction methodologies are used. In this study, integrated reference model of reliability prediction is serviced for existing PRISM and Bellcore which is related on reliability prediction about electronic components, and will service reliability data based on PoF (Physics of Failure) from domestic research center. The constructed frame of reliability evaluation system, which can predict and evaluate reliability of electronic components and MEMS, is designed by using online service of the reliability data accumulated on web. To evaluate proposed system, the reliability evaluation of PCB (Printed Circuits Boards), which is used in NC controller of machine tools, is introduced according to PRISM, the representative reference model of reliability prediction about electronic components based on MIL-HDBK-217F.

The Intelligent Fault Diagnosis Based on Bayesian Network Inference Algorithm Solution

2015 ◽  
Vol 727-728 ◽  
pp. 884-887 ◽  
Author(s):  
Hao Wang ◽  
Sha Sha
Keyword(s):  
Fault Diagnosis ◽  
Bayesian Network ◽  
Wireless Network ◽  
Data Transmission ◽  
Network Inference ◽  
Inference Algorithm ◽  
Intelligent Fault Diagnosis ◽  
Fault Diagnosis System ◽  
Diagnosis Model ◽  
Bayesian Network Inference

In this thesis a remote intelligent fault diagnosis system based on wireless network is put forward. A method of data-transmission based on wireless network is analyzed and a scheme for intelligent fault diagnosis on the basis of Bayesian network is laid out.This thesis also researches on how to build a fault diagnosis model taking advantage of Bayesian network and how to improve the system's resolving ability and reasoning quality in the process of intelligent fault diagnosis.

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