Entitlement to Education: Fairness Analysis

Iris BenDavid-Hadar

doi:10.7459/es/31.3.04

A Scheduling Scheme for Autonomous Vehicle Highway Merging With an Outflow Traffic and Fairness Analysis

IEEE Access ◽

10.1109/access.2021.3066653 ◽

2021 ◽

Vol 9 ◽

pp. 49219-49232

Author(s):

Masashi Kunibe ◽

Hiromu Asahina ◽

Hiroshi Shigeno ◽

Iwao Sasase

Keyword(s):

Autonomous Vehicle ◽

Scheduling Scheme ◽

Fairness Analysis

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Fairness Analysis of Routing in Opportunistic Mobile Networks

IEEE Transactions on Vehicular Technology ◽

10.1109/tvt.2013.2282341 ◽

2014 ◽

Vol 63 (3) ◽

pp. 1282-1295 ◽

Cited By ~ 6

Author(s):

Xiaoguang Fan ◽

Victor O. K. Li ◽

Kuang Xu

Keyword(s):

Mobile Networks ◽

Opportunistic Mobile Networks ◽

Fairness Analysis

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Fairness analysis of TCP variants in asymmetric network

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.12.11287 ◽

2018 ◽

Vol 7 (2.12) ◽

pp. 231

Author(s):

Sukantkishoro Bisoy ◽

Pradeep Kumar Mallick ◽

Anjana Mishra

Keyword(s):

Simulation Experiment ◽

Queue Management ◽

Random Early Detection ◽

Fair Share ◽

Management Techniques ◽

Tcp Vegas ◽

Different Characteristics ◽

Reverse Path ◽

Tcp Reno ◽

Fairness Analysis

Conservative nature of Vegas creates less opportunity to get fair share of bandwidth then Reno in wired network. On the other hand, aggressive nature of Reno helps to achieve more share of bandwidth. Both Reno and Vegas assumes that congestion occurs in the forward rather than in reverse path. In asymmetric network the path characteristics of forward and backward is different.In this work, we propose a network model and analyzed the Inter-protocol fairness between TCP Reno and TCP Vegas with some queue management techniques such as Droptail and random early detection (RED) in asymmetric network where the forward and backward path has different characteristics. The simulation experiment results using NS2 indicates that use of RED can achieve better fairness than Droptail in asymmetric network.

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