Consensus Congestion Control in Multirouter Networks Based on Multiagent System

被引：6

作者：

Yang, Xinhao ^{[1
]}

Xu, Sheng ^{[2
,3
]}

Li, Ze ^{[4
]}

机构：

[1] Soochow Univ, Dept Mech & Elect Engn, Suzhou 215006, Peoples R China

[2] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai Key Lab Power Stn Automat Technol, Shanghai 200072, Peoples R China

[3] Nantong Vocat Univ, Sch Elect & Informat Engn, Nantong 226007, Peoples R China

[4] Suzhou Univ Sci & Technol, Sch Elect & Informat Engn, Suzhou 215009, Peoples R China

来源：

COMPLEXITY | 2017年

基金：

中国国家自然科学基金;

关键词：

SWITCHING TOPOLOGY; CONTROL MODEL; TIME-DELAY; INTERNET; TCP; MANAGEMENT; ALGORITHMS; AGENTS;

D O I：

10.1155/2017/3574712

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

Due to the unbalance distribution of network resources and network traffic, congestion is an inherent property of the Internet. The consensus congestion controller based on the multiagent system theory is designed for the multirouter topology, which improves the performance of the whole networks. Based on the analysis of the causes of congestion, the topology of multirouter networks is modeled based on the graph theory and the network congestion control problemis described as a consensus problem in multiagent systems. Simulation results by MATLAB and Ns2 indicate that the proposed algorithm maintains a high throughput and a low packet drip ratio and improves the quality of the service in the complex network environment.

引用

页数：10

共 38 条

[1] Multi-agent systems for reactive power control in smart grids [J].

Ansari, Javad ;

Gholami, Amin ;

Kazemi, Ahad .

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2016, 83 :411-425

[2]

Chuan-chen W., 2011, ACTA ELECT SINICA, V39, P1858

[3] Stabilization of max-min fair networks without per-flow state [J].

Cobb, Jorge A. ;

Gouda, Mohamed G. .

THEORETICAL COMPUTER SCIENCE, 2011, 412 (40) :5562-5579

[4] Agent-based simulation on tourists' congestion control during peak travel period using Logit model [J].

Du, Siyuan ;

Guo, Chunxiang ;

Jin, Maozhu .

CHAOS SOLITONS & FRACTALS, 2016, 89 :187-194

[5] Random Early Detection Gateways for Congestion Avoidance [J].

Floyd, Sally ;

Jacobson, Van .

IEEE-ACM TRANSACTIONS ON NETWORKING, 1993, 1 (04) :397-413

[6] A hybrid routing model for mitigating congestion in networks [J].

He, Kun ;

Xu, Zhongzhi ;

Wang, Pu .

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2015, 431 :1-17

[7]

Hespanha J. P., 2001, Hybrid Systems: Computation and Control. 4th International Workshop, HSCC 2001. Proceedings (Lecture Notes in Computer Science Vol.2034), P291

[8] A multi-agent system for distribution grid congestion management with electric vehicles [J].

Hu, Junjie ;

Saleem, Arshad ;

You, Shi ;

Nordstrom, Lars ;

Lind, Morten ;

Ostergaard, Jacob .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2015, 38 :45-58

[9] Self-clocking principle for congestion control in the Internet [J].

Hu, Wuhua ;

Xiao, Gaoxi .

AUTOMATICA, 2012, 48 (02) :425-429

[10] Switch Bandwidth Congestion Prediction in Cloud Environment [J].

Kuppusamy, Sivakumar ;

Kaniappan, Vivekanandan ;

Thirupathi, Devi ;

Ramasubramanian, T. .

BIG DATA, CLOUD AND COMPUTING CHALLENGES, 2015, 50 :235-243

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