Packet Loss Analysis of Load-Balancing Switch with ON/OFF Input Processes

Author(s):  
Yury Audzevich ◽  
Levente Bodrog ◽  
Yoram Ofek ◽  
Miklós Telek
Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary

Fog Computing is a new concept made by Cisco to provide same functionalities of Cloud Computing but near to Things to enhance performance such as reduce delay and response time. Packet loss may occur on single Fog server over a huge number of messages from Things because of several factors like limited bandwidth and capacity of queues in server. In this paper, Internet of Things based Fog-to-Cloud architecture is proposed to solve the problem of packet loss on Fog server using Load Balancing and virtualization. The architecture consists of 5 layers, namely: Things, gateway, Fog, Cloud, and application. Fog layer is virtualized to specified number of Fog servers using Graphical Network Simulator-3 and VirtualBox on local physical server. Server Load Balancing router is configured to distribute the huge traffic in Weighted Round Robin technique using Message Queue Telemetry Transport protocol. Then, maximum message from Fog layer are selected and sent to Cloud layer and the rest of messages are deleted within 1 hour using our proposed Data-in-Motion technique for storage, processing, and monitoring of messages. Thus, improving the performance of the Fog layer for storage and processing of messages, as well as reducing the packet loss to half and increasing throughput to 4 times than using single Fog server.


Author(s):  
Aulia Desy Aulia Nur Utomo

Abstract In the use of internet networks that are general in nature need to implement an appropriate network configuration to maximize the use of internet connections provided by service providers. This is important for the optimal use of internet services and in accordance with utilities that are basically general and shared can be achieved. Per Connection Classifier is a load balancing method for distributing traffic loads to more than one network connection point in a balanced way, so that traffic can run optimally. This research focuses on network configuration methods to maximize internet usage for all users. Quality of Service is used to see the performance of network traffic which is indicated by the value of the parameter delay, throughput, and packet loss. Based on the results of testing and research that have been carried out before and after using load balancing per connection clasifier, the delay value is decreased from 180.26 ms to 148.36 ms and throughput increased from 1.76% to 2.03%, then packet loss decreased from 25.37% to 18.59% according to the TIPHON standard. Keywords: Quality of Service, Per Connection Classification, load balancing, delay, throughput, packet loss


2009 ◽  
Vol 3 (1) ◽  
pp. 123 ◽  
Author(s):  
S.A. Paredes ◽  
S. Taebi ◽  
T.J. Hall

2020 ◽  
Vol 4 (1) ◽  
pp. 39-42
Author(s):  
Daud Muhammad Tulloh ◽  
M. Ficky Duskarnaen ◽  
Hamidillah Ajie

Penelitian ini bertujuan untuk mengetahui quality of service jaringan akses Internet dengan optimalisasi load balance pada Mikrotik Router OS di SMK Tunas Harapan Jakarta . Penelitian ini menggunakan metode penelitian rekayasa teknik dengan metode pengembangan sistem NDLC (Network Development Life Cycle), tahap implementasi sampai pada tahapan pengukuran meliputi throughput, jitter, packet loss, dan delay dengan melakukan transfer data dan monitoring streaming  dari laptop client ke server serta penerapan load balancing untuk optimalisasi dua ISP. Berdasarkan hasil akhir dari analisis dapat simpulkan bahwa kinerja parameter quality of service yaitu throughput, jitter, packet loss, dan delay pada jaringan akses Internet SMK Tunas Harapan termasuk dalam kategori Kurang Memuaskan menurut TIPHON.


2019 ◽  
Vol 10 (1) ◽  
pp. 171 ◽  
Author(s):  
Lizhuang Tan ◽  
Wei Su ◽  
Peng Cheng ◽  
Liangyu Jiao ◽  
Zhiyong Gai

Long flow detection and load balancing are crucial techniques for data center running and management. However, both of them have been independently studied in previous studies. In this paper, we propose a complete solution called Sonum, which can complete long flow detection and scheduling at the same time. Sonum consists of a software-defined synergetic sampling approach and an optimal network utilization mechanism. Sonum detects long flows through consolidating and processing sampling information from multiple switches. Compared with the existing prime solution, the missed detection rate of Sonum is reduced by 2.3%–5.1%. After obtaining the long flow information, Sonum minimizes the potential packet loss rate as the optimization target and then translates load balancing into an optimization problem of arranging a minimum packet loss path for long flows. This paper also introduces a heuristic algorithm for solving this optimization problem. The experimental results show that Sonum outperforms ECMP and Hedera in terms of network throughput and flow completion time.


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