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Mobile Agent Approach for Traffic Load Balancing using Sensors

by T. Karthikeyan, S. Sujatha, N. Sudha Bhuvaneswari
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 47 - Number 6
Year of Publication: 2012
Authors: T. Karthikeyan, S. Sujatha, N. Sudha Bhuvaneswari
10.5120/7190-9942

T. Karthikeyan, S. Sujatha, N. Sudha Bhuvaneswari . Mobile Agent Approach for Traffic Load Balancing using Sensors. International Journal of Computer Applications. 47, 6 ( June 2012), 6-10. DOI=10.5120/7190-9942

@article{ 10.5120/7190-9942,
author = { T. Karthikeyan, S. Sujatha, N. Sudha Bhuvaneswari },
title = { Mobile Agent Approach for Traffic Load Balancing using Sensors },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 47 },
number = { 6 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume47/number6/7190-9942/ },
doi = { 10.5120/7190-9942 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:41:09.954951+05:30
%A T. Karthikeyan
%A S. Sujatha
%A N. Sudha Bhuvaneswari
%T Mobile Agent Approach for Traffic Load Balancing using Sensors
%J International Journal of Computer Applications
%@ 0975-8887
%V 47
%N 6
%P 6-10
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The MATLB (Mobile Agent for Traffic Load Balancing) architecture proposed here is a conceptual service-oriented architecture supporting interoperability of systems implementing Ambient Intelligence (AmI) environment. The objective of the paper Mobile Agent Approach for Traffic Load Balancing using Sensors focuses on building an environment equipped with ambient intelligence that can control the traffic in metropolitan cities without crippling the mobility of users. The growing advancement in Mobile Technology and its supportive tools has a greater impact on the social living of human beings. This agent based architecture with sensors, effectors, filters and middleware is one such approach that balances the traffic load and reduces the risks associated with congestion.

References
  1. André Bottaro, Remco Poortinga, Context Management and Semantic Modelling for Ambient Intelligence, Future Research Challenges for Software and Services, Telemetica Institute
  2. Belifemmine. , A. Poggi, G. Rimassa, 2001, JADE - A FIPA2000 Compliant Agent Development Environment, Proc. of the 4th ACM, Conference on Autonomous Agents, ACM Press, June 2001.
  3. Bo Chen, Harry H. Cheng, 2010, A Review of the Applications of Agent Technology in Traffic and Transportation Systems, IEEE Transaction on Intelligent Transportation System, Volume 11, No. 2.
  4. Christensen et al. , 2004 H. B. Architecture Presentation: Experiences from Pervasive Computer Projects, Computer Science Department, University of Aarhus, Center for Pervasive Computing, Report Series, CfPC-2004-PB-1, revision 1. 4, 2004.
  5. Cucchiara, A. Prati, R. Vezzani, 2005, Ambient Intelligence for Security in Public Parks: the LAICA Project, Proceedings of IEEE International Symposium on Imaging for Crime Detection and Prevention, London, UK, pp. 139-144, June 2005.
  6. Estrin, D. Culler, K. Pister, G. Sukjatme, 2002, Connecting the Physical World with Pervasive Networks, IEEE Pervasive Computing, 1(1):59-69, Jan. 2002.
  7. D. Grether, A. Neumann, K. Nagel, 2012, Simulation of Urban Traffic Control: A Queue Model Approach, The 1st International workshop on Agent-based mobility, Traffic and transportation models, Methodologies and Applications.
  8. Henrik Petander, 2007, A Netowrk Mobility Management Architecture for a Heterogeneous Network Environment, Helsinki University of Technology.
  9. Jennings, 2001, An agent-based approach for building complex software systems, Comm. of the ACM, 44(4):35-41, April 2001.
  10. Luca Ferrari, Giacomo Cabri, Franco Zambonelli, Agents and Ambient Intelligence: the LAICA Experience,
  11. Michal Pechoucek and David Sislak, 2009, Agent-Based Approach to Free-Flight Planning, Control, and Simulation, IEEE Intelligent Systems.
  12. Nikolaos I. Spanoudakis, Pavlos Moraitis, 2006, Agent based Architecture in an ambient intelligence context
  13. Reza et. al, 2006, Ambiance: A Moile Agent Platform for End_user Programmable Ambient Systems
  14. Agent Middleware for Supporting Ambient Intelligence in Healthcare, Workshop on Agents Applied in Health Care, Valencia (E), August 2004.
  15. Roman, C. Hess, R. Cerqueira, A. Ranganathan, R. H. Campbell, K. Nahrstedt, 2002, A Middleware Infrastructure for Active Spaces, IEEE Pervasive Computing, 1(4), Oct-Dec 2002.
  16. Satoh, 2005, Mobile Agents for Ambient Intelligence, Postproceedings of International Workshop on Massively Multi-Agent Systems, Lecture Notes in Computer Science (LNCS), Springer, 2005.
  17. N. Sudha Bhuvaneswari, S. Sujatha, 2010, Vibrant Ambient Intelligent System for traffic congestion control in Coimbatore city(VAISTC4), Proceedings of the 12th International Conference on Networking, VLSI and Signal Processing, Pg. No. 288-293.
Index Terms

Computer Science
Information Sciences

Keywords

Ami Salsa Sensors Effectors Matlb

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