scholarly journals Analisis Performansi Jaringan 4G Operator Telkomsel di Kota Tanjungpinang menggunakan Metode Drive Test

2020 ◽  
Vol 9 (1) ◽  
pp. 1-7
Author(s):  
Fitri Farida ◽  
Anton Hekso Yunianto
Keyword(s):  
Network Performance ◽  
Reference Signal ◽  
Test Method ◽  
Service Users ◽  
4G Networks ◽  
Optimal Observation ◽  
Test Technology ◽  
Test Route ◽  
Network Quality

The existence of a 4G network in Tanjungpinang City has begun to be felt by the community. The number of 4G service users continues to increase, so optimal observation is needed on the quality of the 4G network. Analysis of 4G network performance can be obtained using the drive test method. This method is used to obtain network quality information in real terms in the field. In line with advances in drive test technology, it can be applied more easily, namely using G-NetTrack Pro software. The parameters measured to determine the quality of 4G networks in this study are SINR (Signal to Interference Noice Ratio), RSRP (Reference Signal Receives Power), RSRQ (Reference Signal Receives Quality). Location of the measurement in Tanjungpinang City with the drive test route is started from Ali Haji street– Basuki Rahmat street – Wiratno street  - Sekarno Hatta street - Yos Sudarso street - Usman Harun street - POS street - Bakar Batu street - Brigjen Katamso street - MT Haryono street. The result shows 4G Telkomsel has a good quality with value RSRP -83.48 dBm, RSRQ -11.18 dB, SINR 6.71 dB.

scholarly journals Analysis of Signal Quality on Intra and Inter Handover Performance on the 4G LTE Network using the SSV Method

2020 ◽  
Vol 10 (2) ◽  
pp. 107-112
Author(s):  
Ainun Nisyah ◽  
Aisah Aisah ◽  
Lis Diana Mustafa
Keyword(s):  
Network Performance ◽  
Test Method ◽  
Single Site ◽  
Signal Quality ◽  
Verification Method ◽  
Lte Network ◽  
Network Problems ◽  
4G Lte ◽  
Handover Performance

One of the advantages of mobile communication is Handover. The research data can be used to identify network problems such as weak signal level (RxLev), poor signal quality (Rx Qual), etc. which cause the handover quality at that site in certain areas to be affected as well. The purpose of this research is to determine the quality of a signal that will affect the performance of the handover frequency both intra-frequency handover and inter-frequency handover on the 4G LTE network by paying attention to the KPI Site of the relevant vendor, in this case PT.GCI Indonesia. The method used to determine the signal quality and network performance in an area, namely measuring and retrieving data with a drive test. One of the data collection techniques on the 4G network is to use the SSV (Single Site Verification) method on the drive test so that the signal quality and handover analysis are known both intra handover and inter handover using the GENEX Probe software. From the results of this study, it was found that the signal quality and handover quality of the 4G LTE network met the standardization given by the KPI, for the requirements for the success of the handover, which was 100% with the signal quality of the RSRP and SINR parameters resulting in a percentage of 73% and 91.21% according to the standards desired by the operator. and vendors using the Single Site Verification (SSV) drive test method.

WiFiMon

2019 ◽  
Vol 8 (1) ◽  
pp. 1-18
Author(s):  
Christos Bouras ◽  
Kurt Baumann ◽  
Vasileios Kokkinos ◽  
Nikolaos Papachristos ◽  
Kostas Stamos
Keyword(s):  
Network Performance ◽  
Research Work ◽  
End Users ◽  
Clear Understanding ◽  
End User ◽  
Additional Information ◽  
Log Files ◽  
Measuring Network ◽  
Network Quality

Measuring network quality of a wireless network as experienced by end-users is quite difficult, as there is not a single tool available that can record measurements on all sides of the system. The approach presented in this research work is based on the end-user feedback, giving the opportunity of visualization of network performance in real time. This paper initially presents an overview of the developed tool, called WiFiMon, which has the ability to capture, record measurements and export statistics on the quality of Wi-Fi network as perceived by the end-users. The measurements are initiated by the end-users—without their intervention—after they visit a webpage or use a mobile application. WiFiMon aims to give a clear understanding of the Wi-Fi network conditions by measuring specific parameters of the network, such as download/upload throughput, and correlate these measurements with raw data from various log files to obtain additional information regarding the performance of specific access points. The results reveal the functionality of the proposed tool and its scalability.

scholarly journals Improving network performance with an integrated priority queue and weighted fair queue scheduling

2020 ◽  
Vol 19 (1) ◽  
pp. 241
Author(s):  
Tsehay Admassu Assegie ◽  
Haymanot Derebe Bizuneh
Keyword(s):  
Network Traffic ◽  
Traffic Congestion ◽  
Network Performance ◽  
Packet Scheduling ◽  
Priority Queue ◽  
Congestion Management ◽  
Service Users ◽  
Network Service ◽  
Communication Traffic

<p>Quality of service (QoS) is the measure of network service availability and transmission. There are many factors influencing QoS among which one is the increasing number of network service users. The increase in the number of network service users and communication traffic causes network congestion. And the traffic congestion results in delay or packet loss and jitter variation. As a result, an organization’s network quality deteriorates and or even becomes unavailable. Therefore, to deliver a high quality network service to the users, a solution that avoids network traffic congestion is needed. In this study, the causes for network traffic congestion and the best solutions to eliminate traffic congestion in a network with congestion management and avoidance using an integrated priority queue (PQ) and weighted fair queue (WFQ) packet scheduling algorithms is proposed.</p>

scholarly journals Enhancement of Computer Network Performance with VLAN

2021 ◽  
Vol 328 ◽  
pp. 02004
Author(s):  
Achmad Ubaidillah ◽  
Koko Joni ◽  
Mohammad Iqbal Bachtiar ◽  
S. Ida Kholida
Keyword(s):  
Quality Of Service ◽  
Service Quality ◽  
Service Provider ◽  
Network Performance ◽  
Computer Network ◽  
Service Users ◽  
Good Service ◽  
Network Service ◽  
Network Service Provider

The computer network service provider must provide a good network service. Service quality is the most important factor and must always be maintained properly. The quality of service can change depending on the number and characteristics of service users. This study optimizes the performance of existing computer networks, namely ordinary LAN networks with the application of VLANs. It is very important because the number of network users is increasing and will continue to increase, while the need for good service quality is very urgent. The results showed that VLANs can improve computer network performance from the system existing, namely LAN network.

Customer’s satisfaction on service quality at Vietnam Technological and Commercial Joint Stock Bank – An Giang Branch

2020 ◽  
Vol 4 (3) ◽  
pp. First
Author(s):  
Tran Minh Hieu ◽  
Nguyen Duong Ngoc Mai Chi
Keyword(s):  
Customer Satisfaction ◽  
Service Quality ◽  
Test Method ◽  
Quality Of Services ◽  
Factors Affecting ◽  
Factors Influencing ◽  
Alpha Reliability ◽  
Survey Results ◽  
Development Orientation

This study applied SERVQUAL scale of Parasuraman et al to measure factors affecting customer satisfaction on service quality at Vietnam Technological and Commercial Joint Stock Bank - An Giang Branch (Techcombank An Giang). The study was conducted to survey 207 customers who have been using the service at Techcombank An Giang. The survey results were analyzed by the Cronbach's Alpha reliability test method, then used Exploratory factor analysis (EFA) to verify and evaluate the scale of service quality. The results of the regression analysis show that customer's satisfaction about service quality at Techcombank An Giang includes four factors: The factor with the highest level is the Empathy with Beta = 0.253, the second of factor is the Responsibility with Beta = 0.248, ranked third in the influence level is the Tangible with Beta = 0.235, and the lowest impact level is the Reliability with Beta = 0.144. The research also uses statistical methods to describe and test the differences of demographic factors with customer's satisfactionon service quality.The analysis results show that there is no difference between customer's satisfaction on service quality and factors such as gender, age, income, number of transaction banks, regular transaction banks, and time to use the service at Techcombank An Giang. Through the research results, the author would like to propose some ideas to improve the quality of services, thereby attracting new customers and importantly, keeping traditional customers because the development orientation of Techcombank is to take care of old customers to cross sell other products of the bank. The Stud results offer a basis for the branch to identify the factors influencing customer satisfaction on their service quality, thereby having an appropriate strategy to improve customer satisfaction.

Demand of Wireless Network and Security in Current Research

2015 ◽  
Vol 14 (6) ◽  
pp. 5809-5813
Author(s):  
Abhishek Prabhakar ◽  
Amod Tiwari ◽  
Vinay Kumar Pathak
Keyword(s):  
Wireless Networks ◽  
Quality Of Service ◽  
Wireless Network ◽  
Network Performance ◽  
Wireless Security ◽  
Human Intervention ◽  
Unauthorized Access ◽  
Quality Of Service Parameters ◽  
Wireless Infrastructure

Wireless security is the prevention of unauthorized access to computers using wireless networks .The trends in wireless networks over the last few years is same as growth of internet. Wireless networks have reduced the human intervention for accessing data at various sites .It is achieved by replacing wired infrastructure with wireless infrastructure. Some of the key challenges in wireless networks are Signal weakening, movement, increase data rate, minimizing size and cost, security of user and QoS (Quality of service) parameters... The goal of this paper is to minimize challenges that are in way of our understanding of wireless network and wireless network performance.

scholarly journals A Survey on Machine Learning-Based Performance Improvement of Wireless Networks: PHY, MAC and Network Layer

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 318
Author(s):  
Merima Kulin ◽  
Tarik Kazaz ◽  
Eli De Poorter ◽  
Ingrid Moerman
Keyword(s):  
Machine Learning ◽  
Wireless Networks ◽  
Performance Improvement ◽  
Quality Of Experience ◽  
Data Driven ◽  
Protocol Stack ◽  
Comprehensive Survey ◽  
Network Prediction ◽  
Network Quality

This paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY, MAC and network. First, the related work and paper contributions are discussed, followed by providing the necessary background on data-driven approaches and machine learning to help non-machine learning experts understand all discussed techniques. Then, a comprehensive review is presented on works employing ML-based approaches to optimize the wireless communication parameters settings to achieve improved network quality-of-service (QoS) and quality-of-experience (QoE). We first categorize these works into: radio analysis, MAC analysis and network prediction approaches, followed by subcategories within each. Finally, open challenges and broader perspectives are discussed.

scholarly journals Estimating PQoS of Video Streaming on Wi-Fi Networks Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 621
Author(s):  
Maghsoud Morshedi ◽  
Josef Noll
Keyword(s):  
Machine Learning ◽  
Video Streaming ◽  
Network Performance ◽  
Service Providers ◽  
Perceived Quality ◽  
Internet Service Providers ◽  
Performance Parameters ◽  
Internet Service ◽  
Access Points

Video on demand (VoD) services such as YouTube have generated considerable volumes of Internet traffic in homes and buildings in recent years. While Internet service providers deploy fiber and recent wireless technologies such as 802.11ax to support high bandwidth requirement, the best-effort nature of 802.11 networks and variable wireless medium conditions hinder users from experiencing maximum quality during video streaming. Hence, Internet service providers (ISPs) have an interest in monitoring the perceived quality of service (PQoS) in customer premises in order to avoid customer dissatisfaction and churn. Since existing approaches for estimating PQoS or quality of experience (QoE) requires external measurement of generic network performance parameters, this paper presents a novel approach to estimate the PQoS of video streaming using only 802.11 specific network performance parameters collected from wireless access points. This study produced datasets comprising 802.11n/ac/ax specific network performance parameters labelled with PQoS in the form of mean opinion scores (MOS) to train machine learning algorithms. As a result, we achieved as many as 93–99% classification accuracy in estimating PQoS by monitoring only 802.11 parameters on off-the-shelf Wi-Fi access points. Furthermore, the 802.11 parameters used in the machine learning model were analyzed to identify the cause of quality degradation detected on the Wi-Fi networks. Finally, ISPs can utilize the results of this study to provide predictable and measurable wireless quality by implementing non-intrusive monitoring of customers’ perceived quality. In addition, this approach reduces customers’ privacy concerns while reducing the operational cost of analytics for ISPs.

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