Traffic dynamics considering packet loss in finite buffer networks

2019 ◽  
Vol 28 (4) ◽  
pp. 048901
Author(s):  
Jie Chen ◽  
Jin-Yong Chen ◽  
Ming Li ◽  
Mao-Bin Hu
Keyword(s):  
Packet Loss ◽  
Finite Buffer ◽  
Traffic Dynamics

The self-adaptive routing strategy to alleviate packet loss in finite buffer networks

2021 ◽  
Vol 2021 (12) ◽  
pp. 123402
Author(s):  
Qing Wu ◽  
Qing-Yang Liu ◽  
Xiang Ling ◽  
Li-Jun Zhang
Keyword(s):  
Heuristic Algorithm ◽  
Packet Loss ◽  
Storage Capacity ◽  
Transportation Systems ◽  
The Self ◽  
Finite Buffer ◽  
Traffic Dynamics ◽  
Shortest Path Routing ◽  
Routing Strategy ◽  
Traffic Capacity

Abstract In real communication or transportation systems, loss of agents is very common due to finite storage capacity. We study the traffic dynamics in finite buffer networks and propose a routing strategy motivated by a heuristic algorithm to alleviate packet loss. Under this routing strategy, the traffic capacity is further improved, comparing to the shortest path routing strategy and efficient routing strategy. Then we investigate the effect of this routing strategy on the betweenness of nodes. Through dynamic routing changes, the maximum node betweenness of the network is greatly reduced, and the final betweenness of each node is almost the same. Therefore, the routing strategy proposed in this paper can balance the node load, thereby effectively alleviating packet loss.

Bayesian traffic dynamics and packet loss prediction for video over IP networks

2006 ◽  
Vol 11 (5) ◽  
pp. 468-479 ◽  
Author(s):  
Andrew Backhouse ◽  
Irene Y. H. Gu
Keyword(s):  
Packet Loss ◽  
Ip Networks ◽  
Traffic Dynamics ◽  
Loss Prediction

Performance Comparison of MANET, VANET and FANET

2018 ◽  
Vol 8 (5) ◽  
pp. 132
Author(s):  
Aarti Sahu ◽  
Laxmi Shrivastava
Keyword(s):  
Fuzzy Logic ◽  
Wireless Network ◽  
Packet Loss ◽  
Ad Hoc Network ◽  
Fuzzy Logic Controller ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Performance Comparison ◽  
Fuzzy Rules ◽  
Mobile Ad Hoc

A wireless ad hoc network is a decentralized kind of wireless network. It is a kind of temporary Computer-to-Computer connection. It is a spontaneous network which includes mobile ad-hoc network (MANET), vehicular ad-hoc network (VANET) and Flying ad-hoc network (FANET). Mobile Ad Hoc Network (MANET) is a temporary network that can be dynamically formed to exchange information by wireless nodes or routers which may be mobile. A VANET is a sub form of MANET. It is an technology that uses vehicles as nodes in a network to make a mobile network. FANET is an ad-hoc network of flying nodes. They can fly independently or can be operated distantly. In this research paper Fuzzy based control approaches in wireless network detects & avoids congestion by developing the ad-hoc fuzzy rules as well as membership functions.In this concept, two parameters have been used as: a) Channel load b) The size of queue within intermediate nodes. These parameters constitute the input to Fuzzy logic controller. The output of Fuzzy logic control (sending rate) derives from the conjunction with Fuzzy Rules Base. The parameter used input channel load, queue length which are produce the sending rate output in fuzzy logic. This fuzzy value has been used to compare the MANET, FANET and VANET in terms of the parameters Throughput, packet loss ratio, end to end delay. The simulation results reveal that usage of Qual Net 6.1 simulator has reduced packet-loss in MANET with comparing of VANET and FANET.

A Groundwork Based Novel Routing Protocol for Vehicular Ad hoc Networks

2017 ◽  
Vol 7 (11) ◽  
pp. 121
Author(s):  
Amolkirat Singh ◽  
Guneet Saini
Keyword(s):  
Routing Protocol ◽  
Packet Loss ◽  
Secure Communication ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Road Traffic ◽  
Traditional Approach ◽  
Unexpected Events ◽  
The Road ◽  
On The Road

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.

Virtualized Fog Network with Load Balancing for IoT based Fog-to-Cloud

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Istabraq M. Al-Joboury ◽  
Emad H. Al-Hemiary
Keyword(s):  
Load Balancing ◽  
Packet Loss ◽  
Fog Computing ◽  
Transport Protocol ◽  
Network Simulator ◽  
Huge Number ◽  
Message Queue ◽  
Limited Bandwidth ◽  
Cloud Architecture ◽  
Fog Network

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.

Sign in / Sign up

Export Citation Format

Share Document