scholarly journals Traffic Shaping Menggunakan Metode HTB (Hierarchical Token Bucket) pada Jaringan Nirkabel

2019 ◽  
Vol 1 (3) ◽  
pp. 144
Author(s):  
Shiha Budin ◽  
Imam Riadi
Keyword(s):  
Quality Of Service ◽  
Computer Networks ◽  
Network Traffic ◽  
Information Services ◽  
Test Results ◽  
Traffic Shaping ◽  
Token Bucket ◽  
Network Quality ◽  
Qos Index

Perkembangan zaman yang semakin pesat menuntut adanya layanan informasi yang lebih cepat, tepat, dan akurat menjadikan jaringan komputer sebagai kebutuhan utama. Traffic Shaping dengan Quality of Service (QoS) dapat digunakan dalam mengoptimalkan bandwidth suatu jaringan untuk menentukan jenis-jenis lalu lintas jaringan. Metode Hierarchical Token Bucket (HTB) dapat mengimplementasi pembagian trafik yang lebih akurat, dengan bandwidth yang tidak digunakan dapat dioptimalkan oleh pengguna lain. Hasil traffic shaping menggunakan metode HTB menghasilkan rata-rata indeks QoS yaitu 3,75 dan dapat dikategorikan Baik, dibandingkan sebelum menerapkan traffic shaping yaitu rata-rata 2,25 yang dikategorikan Kurang Baik. Berdasarkan hasil pengujian dapat disimpulkan bahwa kinerja jaringan hotspot dengan Traffic Shaping dan Quality of Service (QoS)  dapat meningkatkan kualitas jaringan daripada sebelumnya.The development of an increasingly rapid era requires the existence of information services that are faster, more precise, and accurate, making computer networks a primary need. Traffic Shaping with Quality of Service (QoS) can be used in optimizing the bandwidth of a network to determine the types of network traffic. The Hierarchical Token Bucket (HTB) method can implement more accurate traffic sharing, with unused bandwidth being optimized by other users. The results of traffic shaping using the HTB method produces an average QoS index of 3.75 and can be categorized Good, compared to before applying traffic shaping which is an average of 2.25 which is categorized as Poor. Based on the test results it can be concluded that the performance of hotspot networks with Traffic Shaping and Quality of Service (QoS) can improve network quality than before.

scholarly journals Systems approach to modeling the Token Bucket algorithm in computer networks

2002 ◽  
Vol 8 (3) ◽  
pp. 265-279 ◽  
Author(s):  
N. U. Ahmed ◽  
Qun Wang ◽  
L. Orozco Barbosa
Keyword(s):  
Quality Of Service ◽  
Feedback Control ◽  
Dynamic Model ◽  
Computer Networks ◽  
Systems Approach ◽  
Its Analysis ◽  
Network Utilization ◽  
Token Bucket ◽  
Video Traces

In this paper, we construct a new dynamic model for the Token Bucket (TB) algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service) QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

scholarly journals METHODS OF NETWORK TRAFFIC DISTRIBUTION BETWEEN USERS

2018 ◽  
Vol 1 (12) ◽  
pp. 168-173
Author(s):  
Aleksandr Chernigovskiy ◽  
Maksim Krivov
Keyword(s):  
Quality Of Service ◽  
Network Traffic ◽  
Network Control ◽  
Control Algorithms ◽  
Traffic Distribution ◽  
Network Quality ◽  
Basic Network

. In this paper based parameters of network quality of service were considered. Their relation with different traffic types was considered. Basic network control algorithms were presented

scholarly journals ANALISIS QUALITY OF SERVICE (QOS) PADA JARINGAN INTERNET DI UNIVERSITAS BINA INSAN LUBUKLINGGAU MENGGUNAKAN METODE HIERARCHICAL TOKEN BUCKET (HTB)

2020 ◽  
Vol 3 (1) ◽  
pp. 8
Author(s):  
Armanto Armanto ◽  
Nelly Khairani Daulay
Keyword(s):  
Quality Of Service ◽  
Computer Network ◽  
Internet Access ◽  
Bandwidth Management ◽  
Internet Users ◽  
Token Bucket ◽  
Index Value ◽  
Collection Methods ◽  
Qos Index

Abstract - One problem that is often faced by internet users is slow internet access. Specifically, when there are many users sharing internet bandwidth. This problem can occur because no bandwidth management system is used. Therefore it is necessary to apply the appropriate bandwidth management, one of which is HTB. Bandwidth management with queuing bandwidth lending techniques between classes or users. Which can allocate bandwidth according to user bandwidth requirements according to specified priorities. This study uses data collection methods, by observing and recording directly at the research site (observation), conducting question and answer directly to the source (Interview), and documentation by reading literary books. The results obtained from the measurement of QoS parameters using the HTB method on the Bina Insan University network, it can produce an average QoS index value of 3, and included in the category is good. It can be concluded that the HTB method is feasible to be applied at UNIBI in performing bandwidth management as evidenced by the 3 (three) QoS index value and has a  good category.  Keywords: Quality Of Service, Hierarchical Token Bucket, Computer Network

Open network quality of service and bandwidth control: Use cases, technical architecture, and business models

2011 ◽  
Vol 16 (2) ◽  
pp. 133-152 ◽  
Author(s):  
James A. Brunetti ◽  
Kanti Chakrabarti ◽  
Alina M. Ionescu-Graff ◽  
Ramesh Nagarajan ◽  
Dong Sun
Keyword(s):  
Quality Of Service ◽  
Business Models ◽  
Use Cases ◽  
Open Network ◽  
Technical Architecture ◽  
Bandwidth Control ◽  
Network Quality

scholarly journals Penerapan Manajemen Bandwidth Menggunakan Metode Hierarchical Token Bucket Pada Layanan Hotspot Mikrotik Undiksha

2020 ◽  
Vol 5 (1) ◽  
pp. 146
Author(s):  
Ketut Gede Widia Pratama Putra ◽  
Gede Saindra Santyadiputra ◽  
Made Windu Antara Kesiman
Keyword(s):  
Quality Of Service ◽  
Life Cycle ◽  
Packet Loss ◽  
Network Development ◽  
Development Life Cycle ◽  
Token Bucket

Penelitian ini bertujuan untuk mengetahui (1) Penerapan manajemen bandwidth menggunakan metode Hierarchical Token Bucket (HTB) pada layanan hotspot mikrotik Undiksha. (2) Hasil pengujian kualitas layanan internet dari parameter Quality of Service (QoS) yang sudah diterapkan menggunakan metode Hierarchical Token Bucket (HTB).Metode penelitian yang digunakan adalah menggunakan pendekatan Network Development Life Cycle (NDLC), dengan melalui beberapa tahapan yaitu analisis, desain, simulasi, implementasi, monitoring, dan manajemen. Hasil penelitian menunjukkan (1) Penerapan manajemen bandwidth HTBpada router mikrotik dengan menggabungkan layanan hotspot mikrotik, sudah berjalan dengan baik, yang dibuktikan dengan fungsi dari metode HTB bisa berjalan dengan baik. (2) Hasil pengukuran dengan menggunakan 2 metode manajemen bandwidth, diperoleh hasil rata-rata download dan upload dari metode HTB lebih besar dibandingkan dengan metode simple queue. Dan parameter packet loss, throughput, delay  dan  jitter yang dilakukan uji menggunakan aplikasi wireshark menerangkan bahwa metode HTB mendapatkan nilai rata-rata yang lebih baik dibandingkan dengan metode simple queue.

scholarly journals KLASIFIKASI PENGGUNAAN PROTOKOL KOMUNIKASI PADA TRAFIK JARINGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBOR

2016 ◽  
Vol 16 (1) ◽  
pp. 67
Author(s):  
Komang Kompyang Agus Subrata ◽  
I Made Oka Widyantara ◽  
Linawati Linawati
Keyword(s):  
Quality Of Service ◽  
Network Traffic ◽  
Network Architecture ◽  
Nearest Neighbor ◽  
Computer Network ◽  
Data Communication ◽  
Data Capture ◽  
K Nearest Neighbor ◽  
High Level

ABSTRACT—Network traffic internet is data communication in a network characterized by a set of statistical flow with the application of a structured pattern. Structured pattern in question is the information from the packet header data. Proper classification to an Internet traffic is very important to do, especially in terms of the design of the network architecture, network management and network security. The analysis of computer network traffic is one way to know the use of the computer network communication protocol, so it can be the basis for determining the priority of Quality of Service (QoS). QoS is the basis for giving priority to analyzing the network traffic data. In this study the classification of the data capture network traffic that though the use of K-Neaerest Neighbor algorithm (K-NN). Tools used to capture network traffic that wireshark application. From the observation of the dataset and the network traffic through the calculation process using K-NN algorithm obtained a result that the value generated by the K-NN classification has a very high level of accuracy. This is evidenced by the results of calculations which reached 99.14%, ie by calculating k = 3. Intisari—Trafik jaringan internet adalah lalu lintas ko­mu­nikasi data dalam jaringan yang ditandai dengan satu set ali­ran statistik dengan penerapan pola terstruktur. Pola ter­struktur yang dimaksud adalah informasi dari header paket data. Klasifikasi yang tepat terhadap sebuah trafik internet sa­ngat penting dilakukan terutama dalam hal disain perancangan arsitektur jaringan, manajemen jaringan dan keamanan jari­ngan. Analisa terhadap suatu trafik jaringan komputer meru­pakan salah satu cara mengetahui penggunaan protokol komu­nikasi jaringan komputer, sehingga dapat menjadi dasar pe­nen­tuan prioritas Quality of Service (QoS). Dasar pemberian prio­ritas QoS adalah dengan penganalisaan terhadap data trafik jaringan. Pada penelitian ini melakukan klasifikasi ter­hadap data capture trafik jaringan yang di olah menggunakan Algoritma K-Neaerest Neighbor (K-NN). Apli­kasi yang digu­nakan untuk capture trafik jaringan yaitu aplikasi wireshark. Hasil observasi terhadap dataset trafik jaringan dan melalui proses perhitungan menggunakan Algoritma K-NN didapatkan sebuah hasil bahwa nilai yang dihasilkan oleh klasifikasi K-NN memiliki tingkat keakuratan yang sangat tinggi. Hal ini dibuktikan dengan hasil perhi­tungan yang mencapai nilai 99,14 % yaitu dengan perhitungan k = 3. DOI: 10.24843/MITE.1601.10

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